uncbiag-non-dlbp-pubs.bib

@article{kwak2022differential,
  title={Differential Role for hippocampal subfields in Alzheimer’s disease progression revealed with deep learning},
  author={Kwak, Kichang and Niethammer, Marc and Giovanello, Kelly S and Styner, Martin and Dayan, Eran and Alzheimer's Disease Neuroimaging Initiative and others},
  journal={Cerebral Cortex},
  volume={32},
  number={3},
  pages={467--478},
  year={2022},
  publisher={Oxford Academic},
  abstract={Mild cognitive impairment (MCI) is often considered the precursor of Alzheimer’s disease. However, MCI is associated with substantially variable progression rates, which are not well understood. Attempts to identify the mechanisms that underlie MCI progression have often focused on the hippocampus but have mostly overlooked its intricate structure and subdivisions. Here, we utilized deep learning to delineate the contribution of hippocampal subfields to MCI progression. We propose a dense convolutional neural network architecture that differentiates stable and progressive MCI based on hippocampal morphometry with an accuracy of 75.85\%. A novel implementation of occlusion analysis revealed marked differences in the contribution of hippocampal subfields to the performance of the model, with presubiculum, CA1, subiculum, and molecular layer showing the most central role. Moreover, the analysis reveals that 10.5\% of the volume of the hippocampus was redundant in the differentiation between stable and progressive MCI.},
  doi={https://doi.org/10.1093/cercor/bhab223},
  keywords={brain,Alzheimers}
}

@article{liu2021perfusion,
  title={Perfusion Imaging: An Advection Diffusion Approach},
  author={Peirong Liu and
  Yueh Z Lee and
  Stephen R Aylward and
  Marc Niethammer},
  journal={IEEE Transactions on Medical Imaging},
  year={2021},
  publisher={IEEE},
  abstract={Perfusion imaging is of great clinical importance and is used to assess a wide range of diseases including strokes and brain tumors. Commonly used approaches for the quantitative analysis of perfusion images are based on measuring the effect of a contrast agent moving through blood vessels and into tissue. Contrast-agent free approaches, for example, based on intravoxel incoherent motion and arterial spin labeling, also exist, but are so far not routinely used clinically. Existing contrast-agent-dependent methods typically rely on the estimation of the arterial input function (AIF) to approximately model tissue perfusion. These approaches neglect spatial dependencies. Further, as reliably estimating the AIF is non-trivial, different AIF estimates may lead to different perfusion measures. In this work we therefore propose PIANO, an approach that provides additional insights into the perfusion process. PIANO estimates the velocity and diffusion fields of an advection-diffusion model best explaining the contrast dynamics without using an AIF. PIANO accounts for spatial dependencies and neither requires estimating the AIF nor relies on a particular contrast agent bolus shape. Specifically, we propose a convenient parameterization of the estimation problem, a numerical estimation approach, and extensively evaluate PIANO. Simulation experiments show the robustness and effectiveness of PIANO, along with its ability to distinguish between advection and diffusion. We further apply PIANO on a public brain magnetic resonance (MR) perfusion dataset of acute stroke patients, and demonstrate that PIANO can successfully resolve velocity and diffusion field ambiguities and results in sensitive measures for the assessment of stroke, comparing favorably to conventional measures of perfusion.},
  url={https://drive.google.com/file/d/1KJ0oxeZiuDN3TpFGlb_iJ-sopOkLcUKP},
  doi={10.1109/TMI.2021.3085828},
  keyowrds={stroke,CT,perfusion}
}

@article{abumoussa2020computational,
  title={Computational methods for visualizing and measuring verapamil efficacy for cerebral vasospasm},
  author={Andrew Abumoussa and
  Alex Flores and
  James Ho and
  Marc Niethammer and
  Deanna Sasaki-Adams and
  Yueh Z Lee},
  journal={Scientific Reports},
  volume={10},
  number={1},
  pages={1--8},
  year={2020},
  publisher={Nature Publishing Group},
  abstract={Cerebral vasospasm is a dreaded sequelae of aneurysmal subarachnoid hemorrhage (aSAH), requiring timely intervention with therapeutic goals of improving brain perfusion. There are currently no standardized real-time, objective assessments of the interventional procedures performed to treat vasospasm. Here we describe real-time techniques to quantify cerebral perfusion during interventional cerebral angiography. We retrospectively analyzed 39 consecutive cases performed to treat clinical vasospasm and quantified the changes in perfusion metrics between pre- and post- verapamil administrations. With Digital Subtraction Angiography (DSA) perfusion analysis, we are able to identify hypoperfused territories and quantify the exact changes in cerebral perfusion for each individual case and vascular territory. We demonstrate that perfusion analysis for DSA can be performed in real time. This provides clinicians with a colorized map which directly visualizes hypoperfused tissue, combined with associated perfusion statistics. Quantitative thresholds and analysis based on DSA perfusion may assist with real-time dosage estimation and help predict response to treatment, however future prospective analysis is required for validation.},
  url={https://www.nature.com/articles/s41598-020-75365-2},
  doi={10.1038/s41598-020-75365-2},
  keywords={vasospasm}
}

@article{han2021deep,
  title={Deep-learning-based image registration and automatic segmentation of organs-at-risk in cone-beam CT scans from high-dose radiation treatment of pancreatic cancer},
  author={Xu Han and
  Jun Hong and
  Marsha Reyngold and
  Christopher Crane and
  John Cuaron and
  Carla Hajj and
  Justin Mann and
  Melissa Zinovoy and
  Hastings Greer and
  Ellen Yorke and
  Gig Mageras and
  Marc Niethammer},
  journal={Medical Physics},
  year={2021},
  publisher={Wiley Online Library},
  url={https://aapm.onlinelibrary.wiley.com/doi/full/10.1002/mp.14906},
  doi={10.1002/mp.14906},
  abstract={Purpose: Accurate deformable registration between computed tomography (CT) and cone-beam CT (CBCT) images of pancreatic cancer patients treated with high biologically effective radiation doses is essential to assess changes in organ-at-risk (OAR) locations and shapes and to compute delivered dose. This study describes the development and evaluation of a deep-learning (DL) registration model to predict OAR segmentations on the CBCT derived from segmentations on the planning CT. Methods: The DL model is trained with CT-CBCT image pairs of the same patient, on which OAR segmentations of the small bowel, stomach, and duodenum have been manually drawn. A transformation map is obtained, which serves to warp the CT image and segmentations. In addition to a regularity loss and an image similarity loss, an OAR segmentation similarity loss is also used during training, which penalizes the mismatch between warped CT segmentations and manually drawn CBCT segmentations. At test time, CBCT segmentations are not required as they are instead obtained from the warped CT segmentations. In an IRB-approved retrospective study, a dataset consisting of 40 patients, each with one planning CT and two CBCT scans, was used in a fivefold cross-validation to train and evaluate the model, using physician-drawn segmentations as reference. Images were preprocessed to remove gas pockets. Network performance was compared to two intensity-based deformable registration algorithms (large deformation diffeomorphic metric mapping [LDDMM] and multimodality free-form [MMFF]) as baseline. Evaluated metrics were Dice similarity coefficient (DSC), change in OAR volume within a volume of interest (enclosing the low-dose PTV plus 1 cm margin) from planning CT to CBCT, and maximum dose to 5 cm3 of the OAR [D(5cc)]. Results: Processing time for one CT-CBCT registration with the DL model at test time was less than 5 seconds on a GPU-based system, compared to an average of 30 minutes for LDDMM optimization. For both small bowel and stomach/duodenum, the DL model yielded larger median DSC and smaller interquartile variation than either MMFF (paired t-test P < 10−4 for both type of OARs) or LDDMM (P < 10−3 and P = 0.03 respectively). Root-mean-square deviation (RMSD) of DL-predicted change in small bowel volume relative to reference was 22\% less than for MMFF (P = 0.007). RMSD of DL-predicted stomach/duodenum volume change was 28\% less than for LDDMM (P = 0.0001). RMSD of DL-predicted D(5cc) in small bowel was 39\% less than for MMFF (P = 0.001); in stomach/duodenum, RMSD of DL-predicted D(5cc) was 18\% less than for LDDMM (P < 10−3). Conclusions: The proposed deep network CT-to-CBCT deformable registration model shows improved segmentation accuracy compared to intensity-based algorithms and achieves an order-of-magnitude reduction in processing time.},
  keywords={Medical Physics,pancreas,cancer,registration}
}

@article{young2021general,
  title={General anaesthesia during infancy reduces white matter micro-organisation in developing rhesus monkeys},
  author={Jeffrey T Young and
  Roza M Vlasova and
  Brittany R Howell and
  Rebecca C Knickmeyer and
  Elyse Morin and
  Kaela I Kuitchoua and
  Gabriele R Lubach and
  Jean Noel and
  Xiaoping Hu and
  Yundi Shi and
  Gibson Caudill and
  Andrew L Alexander and
  Marc Niethammer and
  Merle G Paule and
  Christopher L Coe and
  Mar Sanchez and
  Martin Styner},
  journal={British Journal of Anaesthesia},
  volume={126},
  number={4},
  pages={845--853},
  year={2021},
  publisher={Elsevier},
  abstract={Background: Non-human primates are commonly used in neuroimaging research for which general anaesthesia or sedation is typically required for data acquisition. In this analysis, the cumulative effects of exposure to ketamine, Telazol® (tiletamine and zolazepam), and the inhaled anaesthetic isoflurane on early brain development were evaluated in two independent cohorts of typically developing rhesus macaques. Methods: Diffusion MRI scans were analysed from 43 rhesus macaques (20 females and 23 males) at either 12 or 18 months of age from two separate primate colonies. Results: Significant, widespread reductions in fractional anisotropy with corresponding increased axial, mean, and radial diffusivity were observed across the brain as a result of repeated anaesthesia exposures. These effects were dose dependent and remained after accounting for age and sex at time of exposure in a generalised linear model. Decreases of up to 40\% in fractional anisotropy were detected in some brain regions. Conclusions: Multiple exposures to commonly used anaesthetics were associated with marked changes in white matter microstructure. This study is amongst the first to examine clinically relevant anaesthesia exposures on the developing primate brain. It will be important to examine if, or to what degree, the maturing brain can recover from these white matter changes.},
  keywords={anesthesia,DWI},
  url={https://www.sciencedirect.com/science/article/abs/pii/S0007091220310515},
  doi={10.1016/j.bja.2020.12.029}
}

@inproceedings{pre-liu2021-cvpr,
 abstract = {Transport processes are ubiquitous. They are, for example, at the heart of optical flow approaches; or of perfusion imaging, where blood transport is assessed, most commonly by injecting a tracer. An advection-diffusion equation is widely used to describe these transport phenomena. Our goal is estimating the underlying physics of advection-diffusion equations, expressed as velocity and diffusion tensor fields. We propose a learning framework (YETI) building on an auto-encoder structure between 2D and 3D image time-series, which incorporates the advection-diffusion model. To help with identifiability, we develop an advection-diffusion simulator which allows pre-training of our model by supervised learning using the velocity and diffusion tensor fields. Instead of directly learning these velocity and diffusion tensor fields, we introduce representations that assure incompressible flow and symmetric positive semi-definite diffusion fields and demonstrate the additional benefits of these representations on improving estimation accuracy. We further use transfer learning to apply YETI on a public brain magnetic resonance (MR) perfusion dataset of stroke patients and show its ability to successfully distinguish stroke lesions from normal brain regions via the estimated velocity and diffusion tensor fields.},
 author = {Peirong Liu and Lin Tian and Yubo Zhang and Stephen Aylward and Yueh Lee and Marc Niethammer},
 booktitle = {IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2021},
 keywords = {PDEs,perfusion,stroke,brain,CVPR}, 
 publisher = {Computer Vision Foundation / IEEE}, 
 title = {Discovering Hidden Physics Behind Transport Dynamics},
 url = {https://drive.google.com/file/d/1-YzalmclgVEkzBjq3-_pq3VRgv-pKTf-},
 year = {2021}
}

@article{pre-couture2018image,
  title={Image analysis with deep learning to predict breast cancer grade, ER status, histologic subtype, and intrinsic subtype},
  author={Heather D. Couture and Lindsay A. Williams and Joseph Geradts and Sarah J. Nyante and Ebonee N. Butler and J. S. Marron and Charles M. Perou and Melissa A. Troester and Marc Niethammer},
  journal={NPJ breast cancer},
  volume={4},
  number={1},
  pages={1--8},
  year={2018},
  publisher={Nature Publishing Group},
  abstract={RNA-based, multi-gene molecular assays are available and widely used for patients with ER-positive/HER2-negative breast cancers. However, RNA-based genomic tests can be costly and are not available in many countries. Methods for inferring molecular subtype from histologic images may identify patients most likely to benefit from further genomic testing. To identify patients who could benefit from molecular testing based on H&E stained histologic images, we developed an image analysis approach using deep learning. A training set of 571 breast tumors was used to create image-based classifiers for tumor grade, ER status, PAM50 intrinsic subtype, histologic subtype, and risk of recurrence score (ROR-PT). The resulting classifiers were applied to an independent test set (n = 288), and accuracy, sensitivity, and specificity of each was assessed on the test set. Histologic image analysis with deep learning distinguished low-intermediate vs. high tumor grade (82\% accuracy), ER status (84\% accuracy), Basal-like vs. non-Basal-like (77\% accuracy), Ductal vs. Lobular (94\% accuracy), and high vs. low-medium ROR-PT score (75\% accuracy). Sampling considerations in the training set minimized bias in the test set. Incorrect classification of ER status was significantly more common for Luminal B tumors. These data provide proof of principle that molecular marker status, including a critical clinical biomarker (i.e., ER status), can be predicted with accuracy >75\% based on H&E features. Image-based methods could be promising for identifying patients with a greater need for further genomic testing, or in place of classically scored variables typically accomplished using human-based scoring.},
  keywords={cancer,breast,NPJ},
  doi={10.1038/s41523-018-0079-1},
  url={https://www.nature.com/articles/s41523-018-0079-1.pdf}
}

@article{liu2015low,
  title={Low-rank atlas image analyses in the presence of pathologies},
  author={Liu, Xiaoxiao and Niethammer, Marc and Kwitt, Roland and Singh, Nikhil and McCormick, Matt and Aylward, Stephen},
  journal={IEEE transactions on medical imaging},
  volume={34},
  number={12},
  pages={2583--2591},
  year={2015},
  publisher={IEEE},
  abstract={We present a common framework, for registering images to an atlas and for forming an unbiased atlas, that tolerates the presence of pathologies such as tumors and traumatic brain injury lesions. This common framework is particularly useful when a sufficient number of protocol-matched scans from healthy subjects cannot be easily acquired for atlas formation and when the pathologies in a patient cause large appearance changes. Our framework combines a low-rank-plus-sparse image decomposition technique with an iterative, diffeomorphic, group-wise image registration method. At each iteration of image registration, the decomposition technique estimates a “healthy” version of each image as its low-rank component and estimates the pathologies in each image as its sparse component. The healthy version of each image is used for the next iteration of image registration. The low-rank and sparse estimates are refined as the image registrations iteratively improve. For unbiased atlas formation, at each iteration, the average of the low-rank images from the patients is used as the atlas image for the next iteration, until convergence. Since each iteration's atlas is comprised of low-rank components, it provides a population-consistent, pathology-free appearance. Evaluations of the proposed methodology are presented using synthetic data as well as simulated and clinical tumor MRI images from the brain tumor segmentation (BRATS) challenge from MICCAI 2012.},
  url={https://drive.google.com/file/d/1epFJu4_gS2nMvwhD9G2PJ6tKPnw7Jl3P}
}

@article {non_dblp_young2017,
	title = {The {UNC-Wisconsin} Rhesus Macaque Neurodevelopment Database: A Structural {MRI} and {DTI} Database of Early Postnatal Development},
	journal = {Frontiers in Neuroscience},
	year = {2017},
	abstract = {<p>Rhesus macaques are commonly used as a translational animal model in neuroimaging and neurodevelopmental research. In this report, we present longitudinal data from both structural and diffusion MRI images generated on a cohort of 34 typically developing monkeys from two weeks to 36 months of age. All images have been manually skull stripped and are being made freely available via an online repository for use by the research community. Additionally, this database will continue to be updated as we process the data, create atlases, and perform fiber tracking on the DTI data.</p>
},
	doi = {10.3389/fnins.2017.00029},
	url = {http://journal.frontiersin.org/article/10.3389/fnins.2017.00029/abstract},
	author = {Jeffrey T. Young and Yundi Shi and Marc Niethammer and Michael Grauer and Christopher L. Coe and Gabriele R. Lubach and Bradley Davis and Francois Budin and Rebecca C. Knickmeyer and Andrew L. Alexander and Martin A. Styner},
	keywords = {brain,Frontiers}
}

@article {non_dblp_zdanski2015,
	title = {Quantitative assessment of the upper airway in infants and children with subglottic stenosis},
	journal = {The Laryngoscope},
	year = {2015},
	doi = {10.1002/lary.25482},
	url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5257243/},
	abstract = {OBJECTIVES: Determine whether geometric measures and computational fluid dynamic modeling (CFD) derived from medical imaging are effective diagnostic and treatment planning tools for pediatric subglottic stenosis (SGS). STUDY DESIGN: Retrospective chart and imaging review. SETTING: Tertiary Care Hospital SUBJECTS AND METHODS: CT scans of children (n=17) with SGS were analyzed by geometric and (CFD) methods. Polysomnograms (n=15) were also analyzed. CT\&rsquo;s were also analyzed by age/weight flow normalization and comparison to an Atlas created from normal CT\&rsquo;s. Five geometric, seven CFD, and five PSG measures were analyzed to determine their correlation with which patients received surgery subsequent to the CT/PSG dataset versus those who did not. Statistical analysis was performed using a two-sample t-test with Bonferroni correction and area under the curve analysis. RESULTS: Two geometric indices and one CFD measure were significant for determining which children with SGS received surgery. Polysomnography was less helpful in this determination. Optimal cutoffs for these values were determined from this dataset. CONCLUSIONS: A number of geometric and CFD variables were sensitive at determining which patients with SGS received surgical intervention versus those who did not. Polysomnography was less helpful in making this determination. Discrete, quantitative assessment of the pediatric airway was performed, yielding preliminary data regarding possible objective thresholds for surgical versus non-surgical treatment of disease. This study is limited by its small, retrospective, single institution nature; further studies to validate these findings and possibly optimize treatment threshold recommendations are warranted.},
	author = {Carlton J. Zdanski and Stephanie D. Davis and Yi Hong and Di Miao and Cory Quammen and Sorin Mitran and Bradley Davis and Marc Niethammer and Julia S. Kimbell and Elizabeth Pitkin and Jason Fine and Lynn Fordham and Bradley Vaughn and Richard Superfine},
	keywords = {airway,Laryngoscope}
}

@article {non_dblp_lyu2015,
	title = {Robust estimation of group-wise cortical correspondence with an application to macaque and human neuroimaging studies},
	journal = {Frontiers in Neuroscience},
	volume = {9},
	number = {210},
	year = {2015},
	url = {http://dx.doi.org/10.3389/fnins.2015.00210},
	abstract = {We present a novel group-wise registration method for cortical correspondence for local cortical thickness analysis in human and non-human primate neuroimaging studies. The proposed method is based on our earlier template based registration that estimates a continuous, smooth deformation field via sulcal curve-constrained registration employing spherical harmonic decomposition of the deformation field. This pairwise registration though results in a well-known template selection bias, which we aim to overcome here via a group-wise approach. We propose the use of an unbiased ensemble entropy minimization following the use of the pairwise registration as an initialization. An individual deformation field is then iteratively updated onto the unbiased average. For the optimization, we use metrics specific for cortical correspondence though all of these are straightforwardly extendable to the generic setting: The first focused on optimizing the correspondence of automatically extracted sulcal landmarks and the second on that of sulcal depth property maps. We further propose a robust entropy metric and a hierarchical optimization by employing spherical harmonic basis orthogonality. We also provide the detailed methodological description of both our earlier work and the proposed method with a set of experiments on a population of human and non-human primate subjects. In the experiment, we have shown that our method achieves superior results on consistency through quantitative and visual comparisons as compared to the existing methods.},
	doi = {10.3389/fnins.2015.00210},
	author = {Ilwoo Lyu and Sun H. Kim and Joon-Kyung Seong and Sang W. Yoo and Alan Evans and Yundi Shi and Mar Sanchez and Marc Niethammer and Martin A. Styner},
	keywords = {registration,brain,Frontiers}
}

@mastersthesis {non_dblp_shan2014automatic,
	title = {Automatic localized analysis of longitudinal cartilage changes},
	year = {2014},
	school = {The university of North Carolina at Chapel Hill},
	type = {phd},
	abstract = {<p>Osteoarthritis (OA) is the most common form of arthritis; it is characterized by the loss of cartilage. Automatic quantitative methods are needed to screen large image databases to assess changes in cartilage morphology. This dissertation presents an automatic analysis method to quantitatively analyze longitudinal cartilage changes from knee magnetic resonance (MR) images. A novel robust automatic cartilage segmentation method is proposed to overcome the limitations of existing cartilage segmentation methods. The dissertation presents a new and general convex three-label segmentation approach to ensure the separation of touching objects, i.e., femoral and tibial cartilage. Anisotropic spatial regularization is introduced to avoid over-regularization by isotropic regularization on thin objects. Temporal regularization is further incorporated to encourage temporally-consistent segmentations across time points for longitudinal data. The state-of-the-art analysis of cartilage changes relies on the subdivision of cartilage, which is coarse and purely geometric whereas cartilage loss is a local thinning process and exhibits spatial nonuniformity. A statistical analysis method is proposed to study localized longitudinal cartilage thickness changes by establishing spatial correspondences across time and between subjects. The method is general and can be applied to nonuniform morphological changes in other diseases.</p>
},
	url = {http://dc.lib.unc.edu/cdm/ref/collection/etd/id/5965},
	author = {Shan, Liang},
	keywords={knee}
}

@article {funkhouser2013,
	title = {A new tool improves diagnostic test performance for transmission EM evaluation of axonemal dynein arms.},
	journal = {Ultrastructural Pathology},
	year = {2013},
	volume = {38},
	issue = {4},
	pages = {248-255},
	abstract = {Abstract Diagnosis of primary ciliary dyskinesia (PCD) by identification of dynein arm loss in transmission electron microscopy (TEM) images can be confounded by high background noise due to random electron-dense material within the ciliary matrix, leading to diagnostic uncertainty even for experienced morphologists. The authors developed a novel image analysis tool to average the axonemal peripheral microtubular doublets, thereby increasing microtubular signal and reducing random background noise. In a randomized, double-blinded study that compared two experienced morphologists and three different diagnostic approaches, they found that use of this tool led to improvement in diagnostic TEM test performance.},
	url = {http://www.tandfonline.com/doi/full/10.3109/01913123.2013.815081},
	author = {William K. Funkhouser and Marc Niethammer and Johnny L. Carson and Kimberlie A Burns and Michael R. Knowles and Margaret W. Leigh and Maimoona A. Zariwala and William K. Funkhouser},
	keywords={microscopy,Ultrastructural Pathology,pathology}
}

@conference {niethammer_fx_2013,
	title = {Riemannian metrics for statistics on shapes: parallel transport and scale invariance},
	booktitle = {Proceedings of the 4th MICCAI workshop on Mathematical Foundations of Computational Anatomy (MFCA)},
	year = {2013},
	pages = {1-13},
	url = {https://drive.google.com/file/d/1xP5nOhDZE6q2oX9WdB96mTAcMXVqmWIm},
	abstract = {To be able to statistically compare evolutions of image timeseries data requires a method to express these evolutions in a common coordinate system. This requires a mechanism to transport evolutions between coordinate systems: e.g., parallel transport has been used for large displacement diffeomorphic metric mapping (LDDMM) approaches. A common purpose to study evolutions is to assess local tissue growth or decay as observed in the context of neurodevelopment or neurodegeneration. Hence, preserving this information under transport is important to allow for faithful statistical analysis in the common coordinate system. Most basically, we require scale invariance. Here, we show that a scale invariant metric does not exist in the LDDMM setting. We illustrate the impact of this non-invariance on parallel transport. We also propose a new class of Riemannian metrics on shapes which preserves the variation of a global indicator such as volume under parallel transport.},
	author = {Marc Niethammer and Francois-Xavier Vialard},
	keywords={LDDMM,MICCAI,registration,parallel transport}
}

@article {miedema2011,
	title = {Image and Statistical Analysis of Melanocytic Histology},
	journal = {Histopathology},
	volume = {61},
	year = {2012},
	pages = {436-444},
	abstract = {Aims: We apply digital image analysis techniques to study selected types of melanocytic lesions. Methods and Results: We use advanced digital image analysis to compare melanocytic lesions. All comparisons were statistically significant (p \&lt; 0.0001) and we highlight four: 1) melanoma to nevi, 2) melanoma subtypes to nevi, 3) severely dysplastic nevi to other nevi, and 4) melanoma to severely dysplastic nevi. We were successful in differentiating melanoma from nevi (ROC area 0.95) using image-derived features. Analysis revealed features related to nuclear size, shape, and distance between nuclei most important. Dividing melanoma into subtypes, even greater separation was obtained (ROC area 0.98 for superficial spreading melanoma; 0.95 for lentigo maligna melanoma; and 0.99 for unclassified). Severely dysplastic nevi were best differentiated from conventional and mildly dysplastic nevi by differences in cellular staining qualities (ROC area 0.84). We found that melanoma were separated from severely dysplastic nevi by features related to cell shape and cellular staining qualities (ROC area 0.95). Conclusions: We offer a unique perspective into the evaluation of melanocytic lesions and demonstrate a technological application with increasing prevalence, with potential use as an adjunct to traditional diagnosis in the future.},
	doi = {10.1111/j.1365-2559.2012.04229.x},
	url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3425719/},
	author = {Jason Miedema and J.S. Marron and Marc Niethammer and David Borland and Joseph Woosley and Jason Coposky and Susan Wei and Nancy E. Thomas},
	keywords={histology,cancer,skin,Histopathology}
}

@article {caplan2011,
	title = {The power of correlative microscopy: multi-modal, multi-scale, multi-dimensional},
	journal = {Current Opinion in Structural Biology},
	volume = {21},
	issue = {5},
	year = {2011},
	pages = {686-693},
	abstract = {Correlative microscopy is a sophisticated approach that combines the capabilities of typically separate, but powerful microscopy platforms: often including, but not limited, to conventional light, confocal and super-resolution microscopy, atomic force microscopy, transmission and scanning electron microscopy, magnetic resonance imaging and micro/nano CT (computed tomography). When targeting rare or specific events within large populations or tissues, correlative microscopy is increasingly being recognized as the method of choice. Furthermore, this multi-modal assimilation of technologies provides complementary and often unique information, such as internal and external spatial, structural, biochemical and biophysical details from the <i>same</i> targeted sample. The development of a continuous stream of cutting-edge applications, probes, preparation methodologies, hardware and software developments will enable realization of the full potential of correlative microscopy.},
	issn = {0959-440X},
	doi = {10.1016/j.sbi.2011.06.010},
	url = {http://www.sciencedirect.com/science/article/pii/S0959440X11001035},
	author = {Jeffrey Caplan and Marc Niethammer and Russell M Taylor II and Kirk J Czymmek},
	keywords={microscopy,Current Opinions in Structural Biology}
}

@article {walterfang2011,
	title = {Shape alterations in the striatum in chorea-acanthocytosis},
	journal = {Psychiatry Research: NeuroImaging},
	volume = {192},
	year = {2011},
	pages = {29-36},
	url = {https://drive.google.com/file/d/1sBpHBNhfAbpA15GDeQYxYkH0wIzS2aOn},
	doi = {10.1016/j.pscychresns.2010.10.006},
	abstract = {Chorea-acanthocytosis (ChAc) is an uncommon autosomal recessive disorder due to mutations of the VPS13A gene, which encodes for the membrane protein chorein. ChAc presents with progressive limb and orobuccal chorea, but there is often a marked dysexecutive syndrome. ChAc may first present with neuropsychiatric disturbance such as obsessive-compulsive disorder (OCD), suggesting a particular role for disruption to striatal structures involved in non-motor frontostriatal loops, such as the head of the caudate nucleus. Two previous studies have suggested a marked reduction in volume in the caudate nucleus and putamen, but did not examine morphometric change. We investigated morphometric change in 13 patients with genetically or biochemically confirmed ChAc and 26 age- and gender-matched controls. Subjects underwent magnetic resonance imaging and manual segmentation of the caudate nucleus and putamen, and shape analysis using a non-parametric spherical harmonic technique. Both structures showed significant and marked reductions in volume compared with controls, with reduction greatest in the caudate nucleus. Both structures showed significant shape differences, particularly in the head of the caudate nucleus. No significant correlation was shown between duration of illness and striatal volume or shape, suggesting that much structural change may have already taken place at the time of symptom onset. Our results suggest that striatal neuron loss may occur early in the disease process, and follows a dorsal-ventral gradient that may correlate with early neuropsychiatric and cognitive presentations of the disease.},
	author = {Mark Walterfang and Jeffrey C. L. Looi and Martin Styner and Ruth H. Walker and Adrian Danek and Marc Niethammer and Andrew Evans and Katya Kotschet and Guilherme R. Rodrigues and Andrew Hughes and Dennis Velakoulis},
	keywords = {shape,brain}
}

@conference {niethammer2010h,
	title = {{DTI} Longitudinal Atlas Construction as an Average of Growth Models},
	booktitle = {MICCAI, International Workshop on Spatio-Temporal Image Analysis for Longitudinal and Time-Series Image Data},
	year = {2010},
	url = {https://drive.google.com/file/d/1IRRFhlpydZpfinPnFo8rHGJQZ5CroSRo},
	abstract = {Existing atlas-building methods for diusion-tensor images are not designed for longitudinal data. This paper proposes a novel longitudinal atlas-building framework explicitly accounting for temporal dependencies of longitudinal MRI data. Subject-specic growth modeling, cross-sectional atlas-building and growth modeling in atlas space are combined with statistical longitudinal modeling, resulting in a longitudinal diffusion tensor atlas. The method captures changes in morphology, while modeling temporal changes and allowing to account for covariates. The component algorithms are based on large-displacement metric mapping formulations. To effectively account for measurements sparse in time, a continuous-discrete growth model is proposed. The method is applied to a longitudinal dataset of diffusion-tensor magnetic resonance brain images of developing macaque monkeys with time-points at ages 2 weeks, 3 months, and 6 months.},
	author = {Gabriel Hart and Yundi Shi and Hongtu Zhu and Mar Sanchez and Martin Styner and Marc Niethammer},
	keywords={MICCAI,diffusion,brain,registration,longitudinal}
}

@conference {niethammer2010d,
	title = {Prediction-driven Respiratory Motion Atlas Formation for 4D Image-guided Radiation Therapy in Lung},
	booktitle = {MICCAI, International Workshop on Pulmonary Image Analysis},
	year = {2010},
	url = {https://drive.google.com/file/d/1qgUBbtV9rhpxoss71E2LqWMbBQ4cQmgq},
	abstract = {Respiratory motion challenges lung radiation therapy with uncertainties of the location of important anatomical structures in the thorax. To capture the trajectory of the motion, dense image matching methods and learning-based motion prediction methods have been commonly used. However, both methods have limitations. Serious motion artifacts in treatment-guidance images, such as streak artifacts in respiration-correlated cone-beam CT, challenge the intensity-based image matching; the learning-based prediction methods require consistency between the training data for planning and the data for treatment. This paper proposes a prediction-driven motion atlas framework for motion estimation with artifact-laden images, using a Frechet-mean-image matching scheme that is softly constrained by deformation predictions. In this framework, all the respiration phase-stamped images within a breathing cycle are diffeomorphically deformed to their Frechet mean. The iterative optimization is driven by both intensity matching forces and the prediction forces trained from patient-specific planning images. The effectiveness of the framework is demonstrated with computational phantom and real cone-beam CT images.},
	author = {Xiaoxiao Liu and Bradley C. Davis and Marc Niethammer and Stephen M. Pizer and Gigkas S. Mageras},
	keywords = {lung,registration,MICCAI}
}
@conference {niethammer2010f,
	title = {Robust model-based transformation and averaging of diffusion weighted images - applied to diffusion weighted atlas construction},
	booktitle = {MICCAI, International Workshop on Computational Diffusion MRI (CDMRI10)},
	year = {2010},
	url = {https://drive.google.com/file/d/1-RvZKjnPOfa9HfcWyRk6bwUV3vPwXInu},
	abstract = {This paper describes a method for model-based averaging of sets of diffusion weighted magnetic resonance images (DW-MRI) under space transformations (resulting for example from registration methods). A robust weighted least squares method is developed. Synthetic validation experiments show the improvement of the proposed estimation method in comparison to standard least squares estimation. The developed method is applied to construct an atlas of diffusion weighted images for a set of macaques, allowing for a more flexible representation of average diffusion information compared to standard diffusion tensor atlases.},
	author = {Marc Niethammer and Yundi Shi and Sami Benzaid and Mar Sanchez and Martin Styner},
	keywords = {diffusion,atlas,MICCAI}
}
@article {looi2010,
	title = {Shape analysis of the neostriatum in subtypes of frontotemporal lobar degeneration: neuroanatomically significant regional morphologic change},
	journal = {Psychiatry Research -  Neuroimaging},
	url = {https://www.sciencedirect.com/science/article/abs/pii/S0925492710003252},
	doi = {10.1016/j.pscychresns.2010.09.014},
	year = {2011},
	volume = {191},
	issue = {2},
	pages = {98-111},
	abstract = {Frontostriatal circuit mediated cognitive dysfunction has been implicated in frontotemporal lobar degeneration (FTLD) and may differ across subtypes of FTLD. We manually segmented the neostriatum (caudate nucleus and putamen) in FTLD subtypes: behavioral variant frontotemporal dementia, FTD, n=12; semantic dementia, SD, n=13; and progressive nonfluent aphasia, PNFA, n=9); in comparison with controls (n=27). Diagnoses were based on international consensus criteria. Manual bilateral segmentation of the caudate nucleus and putamen was conducted blind to diagnosis by a single analyst, on MRI scans using a standardized protocol. Intra-cranial volume was calculated via a stereological point counting technique and was used for normalizing the shape analysis. Segmented binaries were analyzed using the SPHARM Shape Analysis tools (University of North Carolina) to perform comparisons between FTLD subtypes and controls for global shape difference, local significance maps and mean magnitude maps of shape displacement. Shape analysis revealed that there was significant shape difference between FTLD subtypes and controls, consistent with the predicted frontostriatal dysfunction and of significant magnitude, as measured by displacement maps. These differences were not significant for SD compared to controls; lesser for PNFA compared to controls; whilst FTD showed a more specific pattern in regions relaying fronto- and cortico-striatal circuits. Shape analysis shows regional specificity of atrophy, manifest as shape deflation, with a differential between FTLD subtypes, compared to controls.},
	author = {Jeffrey C. L. Looi and Mark Walterfang and Martin Styner and Marc Niethammer and Leif Svensson and Olof Lindberg and Per Ostberg and Lisa Botes and Eva Orndahl and Phyllis Chua and Dennis Velakoulis and Lars-Oluf Wahlund},
	keywords = {shape,brain}
}

@article {kaplan2009,
	title = {Calcium and cyclic nucleotides affect TNF-alpha-induced stem cell migration.},
	journal = {Biochemical and biophysical research communications},
	volume = {382},
	year = {2009},
	month = {5},
	pages = {241-6},
	abstract = {The purpose of this study was to study the effect of calcium, cyclic AMP (cAMP) and cyclic GMP (cGMP) on embryonic stem cell (ESC) motility during TNF-alpha-induced chemotaxis. ESCs were monitored using a chemotaxis chamber, with different concentrations of calcium or cAMP or cGMP added to the medium. Changes in intracellular calcium ([Ca(2+)](i)) were measured with the fluorescent dye fura-2/AM. We combined migratory parameters in a mathematical model and described it as mobility;. After adding calcium, a dose-dependant increase in cell speed was found. Cyclic AMP increased mobility as well as the [Ca(2+)](i). In contrast, adding dbcGMP resulted in a significant decrease in the mobility of the ESCs. During migration ESCs showed an increase in [Ca(2+)](i). Furthermore, TNF-alpha dramatically increased the movement as well as the directionality of ESCs. These results demonstrate that ESCs are highly motile and respond to different concentrations of calcium in a dose-related manner.},
	author = {Kaplan, Emel and Min, Jiang-Yong and Ke, Qingen and Chen, Yu and Niethammer, Marc and Rana, Jamal S and Malek, Sohail and Verheugt, Freek W A and Morgan, James P}
}

@article {levitt2009,
	title = {Shape abnormalities of caudate nucleus in schizotypal personality disorder.},
	journal = {Schizophrenia research},
	volume = {110},
	year = {2009},
	month = {5},
	pages = {127-39},
	abstract = {BACKGROUND: Previously, we reported abnormal volume and global shape in the caudate nucleus in schizotypal personality disorder (SPD). Here, we use a new shape measure which importantly permits local in addition to global shape analysis, as well as local correlations with behavioral measures. METHODS: Thirty-two female and 15 male SPDs, and 29 female and 14 male normal controls (NCLs), underwent brain magnetic resonance imaging (MRI). We assessed caudate shape measures using spherical harmonic-point distribution model (SPHARM-PDM) methodology. RESULTS: We found more pronounced global shape differences in the right caudate in male and female SPD, compared with NCLs. Local shape differences, principally in the caudate head, survived statistical correction on the right. Also, we performed correlations between local surface deformations with clinical measures and found significant correlations between local shape deflated deformations in the anterior medial surface of the caudate with verbal learning capacity in female SPD. CONCLUSIONS: Using SPHARM-PDM methodology, we found both global and local caudate shape abnormalities in male and female SPD, particularly right-sided, and largely restricted to limbic and cognitive anterior caudate. The most important and novel findings were bilateral statistically significant correlations between local surface deflations in the anterior medial surface of the head of the caudate and verbal learning capacity in female SPD. By extension, these local caudate correlation findings implicate the ventromedial prefrontal cortex (vmPFC), which innervates that area of the caudate, and demonstrate the utility of local shape analysis to investigate the relationship between specific subcortical and cortical brain structures in neuropsychiatric conditions.},
	author = {Levitt, James J and Styner, Martin and Niethammer, Marc and Bouix, Sylvain and Koo, Min-Seong and Voglmaier, Martina M and Dickey, Chandlee C and Niznikiewicz, Margaret A and Kikinis, Ron and McCarley, Robert W and Shenton, Martha E},
	keywords = {shape,brain}
}

@conference {kim2008,
	title = {SPHARM detects hippocampal subfield pathology in temporal lobe epilepsy},
	booktitle = {Proceedings of the ISMRM},
	year = {2008},
	abstract = {Our purpose was to detect volume changes in the hippocampal subfields of patients with pharmacoresistant temporal lobe epilepsy (TLE) using SPHARM, a surface-based shape analysis method. We studied 95 TLE patients with unilateral hippocampal atrophy on MR volumetry and 46 controls. SPHARM applied to manual hippocampal labels measured a distance at each vertex between groups. In more than 40\% of patients, we found a bilateral CA1 inward deformation more marked ipsilateral to the focus. These changes were negatively correlated with disease duration. Predominant CA1 atrophy with relative sparing of other subfields is in agreement with histopathological hippocampal sclerosis.},
	author = {Hosung Kim and Marc Niethammer and Boris C. Bernhardt and Sylvain Bouix and Neda Bernasconi and Andrea Bernasconi},
	keywords = {shape}
}
@conference {niethammer2008conf,
	title = {Tubular Fiber Bundle Segmentation for Diffusion Weighted Imaging},
	booktitle = {Diffusion Weighted Imaging Workshop, MICCAI},
	year = {2008},
	pages = {265-276},
	url = {https://drive.google.com/file/d/13KKhNM4r1Onq61BpO_dHY8SADnNtU2w-},
	abstract = {This paper proposes a methodology to segment tubular fiber bundles from diffusion weighted magnetic resonance images (DW-MRI). Segmentation is simplified by locally reorienting diffusion information based on large-scale fiber bundle geometry. Segmentation is achieved through simple global statistical modeling of diffusion orientation. Utilizing a modification of a recent segmentation approach by Bresson et al. [19] allows for a convex optimization formulation of the segmentation problem, combining orientation statistics and spatial regularization. The approach compares favorably with segmentation by full-brain streamline tractography.}
},
	author = {Marc Niethammer and Christopher Zach and John Melonakos and Allen Tannenbaum},
	keywords = {segmentation,MICCAI,shape}
}
@conference {mohan2008,
	title = {Tubular Surface Evolution for Segmentation of the Cingulum Bundle from DW-MRI},
	booktitle = {Foundations of Computational Anatomy Workshop, MICCAI},
	year = {2008},
	pages = {150-159},
	abstract = {This work provides a framework for modeling and extracting the Cingulum Bundle (CB) from Diffusion-Weighted Imagery (DW-MRI) of the brain. The CB is a tube-like structure in the brain that is of potentially of tremendous importance to clinicians since it may be helpful in diagnosing Schizophrenia. This structure consists of a collection of fibers in the brain that have locally similar diffusion patterns, but vary globally. Standard region-based segmentation techniques adapted to DW-MRI are not suitable here because the diffusion pattern of the CB cannot be described by a global set of simple statistics. Active surface models extended to DW-MRI are not suitable since they allow for arbitrary deformations that give rise to unlikely shapes, which do not respect the tubular geometry of the CB. In this work, we explicitly model the CB as a tube-like surface and construct a general class of energies defined on tube-like surfaces. An example energy of our framework is optimized by a tube that encloses a region that has locally similar diffusion patterns, which differ from the diffusion patterns immediately outside. Modeling the CB as a tube-like surface is a natural shape prior. Since a tube is characterized by a center-line and a radius function, the method is reduced to a 4D (center-line plus radius) curve evolution that is computationally much less costly than an arbitrary surface evolution. The method also provides the center-line of CB, which is potentially of clinical significance.},
	url = {https://hal.inria.fr/inria-00632883},
	author = {Vasana Mohan and Ganesh Sundaramoorthi and John Melonakos and Marc Niethammer and Marek Kubicki and Allen Tannenbaum},
	keywords = {diffusion,segmentation,MICCAI}
}

@conference {niethammer2006,
	title = {On Diffusion Tensor Estimation},
	booktitle = {Proceedings of the International Engineering in Medicine and Biology Conference (EMBC)},
	year = {2006},
	pages = {2622-2625},
	url = {https://drive.google.com/file/d/1NA2GxsWhQxcABz7giW4PYkr9bHO6FMWF},
	abstract = {In this paper we propose a formal formulation for the estimation of Diffusion Tensors in the space of symmetric positive semidefinite (PSD) tensors. Traditionally, diffusion tensor model estimation has been carried out imposing tensor symmetry without constraints for negative eigenvalues. When diffusion weighted data does not follow the diffusion model, due to noise or signal drop, negative eigenvalues may arise. An estimation method that accounts for the positive definiteness is desirable to respect the underlying principle of diffusion. This paper proposes such an estimation method and provides a theoretical interpretation of the result. A closed-form solution is derived that is the optimal data-fit in the matrix 2-norm sense, removing the need for optimization-based tensor estimation.},
	author = {Marc Niethammer and Raul San Jose Estepar and Sylvain Bouix and Martha Shenton and Carl-Fredrik Westin},
	keywords={diffusion,EMBC}
}

@article {kotte2005,
	title = {Lamb Wave Characterization by Differential Reassignment and Nonlinear Anisotropic Diffusion},
	journal = {NDT \& E International},
	volume = {39},
	year = {2006},
	pages = {96-105},
	url = {https://drive.google.com/file/d/1AOvtW0YUHHZqbvM6Rfp6Vx6GvzP9H_Ut},
	abstract = {This research develops an algorithm which provides excellent localization of Lamb wave dispersion curves while eliminating spurious components. This result is achieved by combining a differential reassignment procedure with non-linear anisotropic diffusion. This study examines the reassignment and diffusion components individually, before developing a combined algorithm. This combined algorithm is then applied to experimentally measured Lamb waves to develop an image of the dispersion curves of a plate with excellent clarity and definition. These dispersion curves are then used to increase the accuracy of a previously developed procedure to locate a notch.},
	author = {Oliver Kotte and Marc Niethammer and Laurence J. Jacobs},
	keywords = {Lamb waves}
}

@article {kuttig2006,
	title = {Model-based analysis of dispersion curves using chirplets},
	journal = {The Journal of the Acoustical Society of America},
	volume = {119},
	year = {2006},
	month = {4},
	pages = {2122-2130},
	url = {https://drive.google.com/file/d/18-0WpuuHxHfp6jgJgDIuS5HUCyrzc4k2},
	abstract = {Time-frequency representations, like the spectrogram or the scalogram, are widely used to characterize dispersive waves. The resulting energy distributions, however, suffer from the uncertainty principle, which complicates the allocation of energy to individual propagation modes (especially when the dispersion curves of these modes are close to each other in the time-frequency domain). This research applies the chirplet as a tool to analyze dispersive wave signals based on a dispersion model. The chirplet transform, a generalization of both the wavelet and the short-time Fourier transform, enables the extraction of components of a signal with a particular instantaneous frequency and group delay. An adaptive algorithm identifies frequency regions for which quantitative statements can be made about an individual model's energy, and employs chirplets (locally adapted to a dispersion curve model) to extract the (proportional) energy distribution of that single mode from a multimode dispersive wave signal. The effectiveness of this algorithm is demonstrated on a multimode synthetic Lamb wave signal for which the ground-truth energy distribution is known for each mode. Finally, the robustness of this algorithm is demonstrated on real, experimentally measured Lamb wave signals by an adaption of a correlation technique developed in previous research.},
	issn = {0001-4966},
	url = {http://link.aip.org/link/?jas/119/2122\&agg=MEDLINE_JAS},
	author = {Kuttig, Helge and Niethammer, Marc and Hurlebaus, Stefan and Jacobs, Laurence J.},
	keywords = {lamb waves}
}

@conference {vela2005,
	title = {Closed Loop Visual Tracking Using Observer-Based Dynamic Active Contours},
	booktitle = {Proceedings of the Conference on Guidance Navigation and Control},
	year = {2005},
	url = {https://drive.google.com/file/d/1pSyOci2M303ExFzJ7Y9b2g1qRVwjeLE9},
	abstract = {This paper describes and demonstrates an algorithm to visually track ying vehicles in a leader-follower scenario. The algorithm consists of two nested control loops. One that assures a proper position estimation for the object(s) to be followed (the visual observer) and one that exploits this position estimation to control the maneuvers of the follower such that it pursues the leader. The visual observer is based on some novel geometric principles tailored to controlled active vision. In particular, we describe the use of dynamic active contours as motion priors for such geometrically motivated observers.},
	author = {Patricio A. Vela and Marc Niethammer and James Malcolm and Allen Tannenbaum}
}

@conference {niethammer2005,
	title = {Geometric Observers for Dynamically Evolving Curves},
	booktitle = {Proceedings of the Conference on Decision and Control},
	year = {2005},
	pages = {6071-6077},
	url = {https://drive.google.com/file/d/1LzsVs5Iyiu90umxyA8ev2vs62OlqkqBa},
	abstract = {This paper proposes a deterministic observer framework for visual tracking based on non-parametric implicit (level-set) curve descriptions. The observer is continuousdiscrete, with continuous-time system dynamics and discretetime measurements. Its state-space consists of an estimated curve position augmented by additional states (e.g., velocities) associated with every point on the estimated curve. Multiple simulation models are proposed for state prediction. Measurements are performed through standard static segmentation algorithms and optical-flow computations. Special emphasis is given to the geometric formulation of the overall dynamical system. The discrete-time measurements lead to the problem of geometric curve interpolation and the discrete-time filtering of quantities propagated along with the estimated curve. Interpolation and filtering are intimately linked to the correspondence problem between curves. Correspondences are established by a Laplace-equation approach. The proposed scheme is implemented completely implicitly (by Eulerian numerical solutions of transport equations) and thus naturally allows for topological changes and subpixel accuracy on the computational grid.},
	author = {Marc Niethammer and Patricio A. Vela and Allen Tannenbaum},
	keyword = {curves}
}
@conference {ha2004,
	title = {Active Contours and Optical Flow for Automatic Tracking of Flying Vehicles},
	booktitle = {Proceedings of the American Control Conference},
	volume = {4},
	year = {2004},
	pages = {3441-3446},
	abstract = {In this paper, we describe fast implementations of optical flow and geometric active contours to reliably track flying vehicles. Given the position of the vehicle at time t - 1, optical flow information is used to initially place an active contour in the basin of attraction of a region of interest in a given dynamical image at time t. For real-time tracking, fast convergence of the active contour as wen as rapid computation of the optical flow are crucial. In this note, we will describe algorithms that make fast tracking possible in this framework using only standard computing platforms.},
	author = {Jincheol Ha and Christopher Alvino and Gallagher Pryor and Marc Niethammer and Eric Johnson and Allen Tannenbaum}
}

@conference {niethammer2003_2,
	title = {Dynamic level sets for visual tracking},
	booktitle = {Proceedings of the Conference on Decision and Control},
	volume = {5},
	year = {2003},
	pages = {4883-4888},
	url = {https://drive.google.com/file/d/1jVnuQrLepZvbk7-SHGizvGxMQ3olPr_7},
	abstract = {In this paper we describe two methods for tracking planar curves which are allowed to change topology. In contrast to previous approaches a level set formulation is used that allows for the propagation of state information (here a velocity vector) with every point on a curve. The curve dynamics are derived by minimizing an action integral (based on Hamilton\&$\#$39;s principle). Incorporating velocity information for every point on a curve lifts the originally two dimensional problem to four dimensions, and thus to a codimeusion three problem. Since basic level set approaches implicitly describe codimension one hypersurfaces, we introduce two methods suitable for codimension three problems within a level set framework. The partial level set approach, which propagates velocity information along with the curve by solving two additional transport equations, and the full level set approach, which is formulated by means of a vector distance function evolution equation. The full level set approach allow for complete topological flexibility (including intersecting curves in the image plane). However, it is computationally expensive. The partial level set approach compromises the topological flexibility for computational efficiency. In particular, the full level set ap proacb has the potential for tracking objects throughout occlusions, when combined with a suitable collision detection algorithm.},
	author = {Niethammer, Marc and Tannenbaum, Allen},
	keywords = {curves}
}
@article {benz2003,
	title = {Localization of notches with Lamb waves},
	journal = {The Journal of the Acoustical Society of America},
	volume = {114},
	year = {2003},
	month = {8},
	pages = {677-85},
	url = {https://drive.google.com/file/d/1ucfzY6lYwgWLqzuu9pEstr_9CYS0HE4-},
	abstract = {A time-frequency representation (TFR) is used to analyze the interaction of a multimode and dispersive Lamb wave with a notch, and then serves as the basis for a correlation technique to locate the notch. The experimental procedure uses a laser source and a dual-probe laser interferometer to generate and detect Lamb waves in a notched plate. The high fidelity, broad-bandwidth, point-like and noncontact nature of laser ultrasonics are critical to the success of this study, making it possible to experimentally measure transient Lamb waves without any frequency biases. A specific TFR, the reassigned spectrogram, is used to resolve the dispersion curves of the individual modes of the plate, and then the slowness-frequency representation (SFR) of the plate is calculated from this reassigned spectrogram. By considering the notch to be an additional (second) source, the reflected and transmitted contributions of each Lamb mode are automatically identified using the SFRs. These results are then used to develop a quantitative understanding of the interaction of an incident Lamb wave with a notch, helping to identify mode conversion. Finally, two complementary, automated localization techniques are developed based on this understanding of scattering of Lamb waves.},
	issn = {0001-4966},
	url = {http://link.aip.org/link/?jas/114/677\&agg=MEDLINE_JAS},
	attachments = {https://wwwx.cs.unc.edu/~mn/sites/default/files/benz2003_JASA_localization_of_notches_with_lamb_waves.pdf},
	author = {Benz, Ruediger and Niethammer, Marc and Hurlebaus, Stefan and Jacobs, Laurence J.},
	keywords = {Lamb waves}
}

@article {hurlebaus2001,
	title = {Automated methodology to locate notches with Lamb waves},
	journal = {Acoustic Research Letters Online},
	volume = {2},
	number = {4},
	year = {2001},
	pages = {97-102},
	url = {https://drive.google.com/file/d/1Ea4jrBJ1lffu2v1guqtaoJGaYzJlqTkJ},
	abstract = {This study develops an automated method capable of detecting notches in isotropic plates. Laser ultrasonic techniques are used to generate and detect Lamb waves in perfect and notched plates. These signals are first transformed into the time-frequency domain using a short time Fourier transform (STFT) and subsequently into the group velocity-frequency domain. Finally, the notch is located with an autocorrelation in the group velocity-frequency domain. A verification of the proposed methodology shows excellent agreement with the actual location of the notch.},
	author = {Hurlebaus, Stefan and Niethammer, Marc and Jacobs, Laurance J. and Christine Valle},
	keywords={Lamb waves}
}

@article {valle2001,
	title = {Crack characterization using guided circumferential waves},
	journal = {Journal of the Acoustical Society of America},
	volume = {110},
	number = {3},
	year = {2001},
	pages = {1282-1290},
	url = {https://drive.google.com/file/d/1kLPHb1qtA7-fyz9NBCgUWPPryKdXgBB8},
	abstract = {This paper examines the propagation of guided circumferential waves in a hollow isotropic cylinder that contains a crack, with the goal of using these guided waves to both locate and size the crack. The crack is sized using a modified Auld's formula, which relates the crack's length to a reflected energy coefficient. The crack is then located by operating on the backscattered signal with a time-frequency digital signal processing (DSP) technique, and then comparing these results to those obtained if the cylinder is perfect. The guided circumferential waves are generated with a commercial finite element method (FEM) code. One objective of this work is to demonstrate the effectiveness of using sophisticated DSP techniques to describe the effect of scattering on dispersive waves, showing it is possible to characterize cracks systematically and accurately by quantifying this scattering effect. The results show that the need for high frequency signals to detect small cracks is significantly decreased by using these techniques.},
	author = {Christine Valle and Marc Niethammer and Jianmin Qu and Laurence J. Jacobs},
}
@conference {niethammer2001_2,
	title = {Parameter and derivative estimation for nonlinear continuous-time system identification},
	booktitle = {Proceedings of the 5 th IFAC Symposium on Nonlinear Systems, (NOLCOS 01)},
	year = {2001},
	pages = {691-696},
	url = {https://drive.google.com/file/d/1p8W0wZcMo_7NwkIalsfWIkr9j3OaaK3W},
	abstract = {In this note we investigate parameter identification for nonlinear continuous-time SISO systems, based on input/output data, where the output is assumed to be noise corrupted. Continuous-time identification requires (i) the estimation of derivatives of the output (which is nontrivial due to the influence of noise), a suitable measure thereof or a way to avoid them and (ii) methods for parameter estimation based on the measured data. Problem (i) is addressed by reviewing modulating functions and the concept of delayed state variable filters; furthermore a high-gain observer is introduced as an approach to provide the necessary derivative information. Its performance is investigated with respect to the modulating function and the delayed state variable filter approaches. Least-squares methods are assessed for continuous-time nonlinear identification (problem (ii)). It is shown that parameter identification based in modulating functions and a standard least-squares method does not guarantee bias-free estimates for some systems. Whereas ordinary (or weighted) least-squares is sufficient for parameter identification by means of modulating functions it is not for the delayed state variable filter and the high-gain observer approaches (due to dependencies between error terms). Requirements on least-squares methods for nonlinear continuous-time system identification are discusses and a solution for bilinear systems is given. The importance of an appropriate least-squares method is underlined by parameter identification for a simulated bilinear example system.
},
	author = {Marc Niethammer and Patrick H. Menold and Frank Allgower}
}

@article {niethammer2001,
	title = {Time-frequency representations of Lamb waves},
	journal = {Journal of the Acoustical Society of America},
	volume = {109},
	number = {5},
	year = {2001},
	pages = {1841-1847},
	url = {https://drive.google.com/file/d/1cpnlDXjf0PHFg4irfLFxQ0LxIOxk6ftn},
	abstract = {The objective of this study is to establish the effectiveness of four different time-frequency representations (TFRs): the reassigned spectrogram, the reassigned scalogram, the smoothed Wigner-Ville distribution, and the Hilbert spectrum by comparing their ability to resolve the dispersion relationships for Lamb waves generated and detected with optical techniques. This paper illustrates the utility of using TFRs to quantitatively resolve changes in the frequency content of these nonstationary signals, as a function of time. While each technique has certain strengths and weaknesses, the reassigned spectrogram appears to be the best choice to characterize multimode Lamb waves.
},
	author = {Niethammer, Marc and Jacobs, Laurence J. and Jianmin Qu and Jacek Jarzynski},
	keywords = {Lamb waves}
}

@article {niethammer2000,
	title = {Time-frequency representation of Lamb waves using the reassigned spectrogram},
	journal = {Acoustic Research Letters Online},
	volume = {107},
	year = {2000},
	pages = {L19-L24},
	url = {https://drive.google.com/file/d/15kE45MEj5EglZij79zp-jl7eJ41CpllN},
	abstract = {This brief note reports on a study that applies the reassigned spectrogram (the reassigned energy density spectrum of the short-time Fourier transform [STFT]) to develop the dispersion curves for multimode Lamb waves propagating in an aluminum plate. The proposed procedure first uses the spectrogram to operate on a single, laser-generated and detected waveform to develop the dispersion relationship for this plate. Next, a reassignment procedure is used to refine the time-frequency resolution of the calculated dispersion curves. This reassignment operation clarifies the definition of the measured modes. This study demonstrates that the reassigned spectrogram is capable of distinguishing multiple, closely spaced Lamb modes in the ultrasonic frequency range.},
	author = {Niethammer, Marc and Jacobs, Laurence J. and Jianmin Qu and Jacek Jarzynski},
	keywords = {Lamb waves}
}