A curated list of 
| Papers & Code | Short for Schemes | Notes |
|---|---|---|
| Automated Selection of Standardized Planes from Ultrasound Volume [MICCAI-MLMI 2011] | 2STC | Sliding Window, Haar, AdaBoost, AS Detection, SP Classification |
| Learning-based scan plane identification from fetal head ultrasound images [Medical Imaging 2012] | - | Template Matching, Active Appearance Models, AS Detection, LDA, SP Classification |
| Intelligent Scanning: Automated Standard Plane Selection and Biometric Measurement of Early Gestational Sac in Routine Ultrasound Examination [Medical Physics 2012] | IS | Sliding Window, Haar, Cascade AdaBoost, AS Localization, Relative Position, Local Context Information, SP Classification |
| Selective Search and Sequential Detection for Standard Plane Localization in Ultrasound [MICCAI-CCCAI 2013] | SSSD | Haar, AdaBoost, Segmentation, Accumulative Vessel Probability Map, Selective Search, Geometric Relationship, Sequence AS Detection, SP Localization |
| Standard Plane Localization in Ultrasound by Radial Component [ISBI 2014] | RCD | Random Forest, Geometric Constrain, Radial Component, AS Detection, SVM, SP Localization |
| Automatic Recognition of Fetal Standard Plane in Ultrasound Image [ISBI 2014] | FV-Aug | AdaBoost, Dense Sampling Feature Transform Descriptor, Fish Vector, Spatial Pyramid Coding, Gaussian Mixture Model, SVM, SP Classification |
| Standard Plane Localization in Ultrasound by Radial Component Model and Selective Search [Ultrasound in Medicine and Biology 2014] | RVD | Random Forest, Geometric Constrain, Radial Component, Vessel Probability Map, Selective Search, AS Detection, SVM, SP Localization |
| Diagnostic Plane Extraction from 3D Parametric Surface of the Fetal Cranium [MIUA 2014] | - | Topological Manifold Representation, Landmark Alignment, 3D Parametric Surface Model, SP Localization |
| A Constrained Regression Forests Solution to 3D Fetal Ultrasound Plane Localization for Longitudinal Analysis of Brain Growth and Maturation [MICCAI-MLMI 2014] | CRF-FA-Dist | Informative Voxels, Reference Plane, Constrained Regression Forest, SP Localization |
| Automatic Recognition of Fetal Facial Standard Plane in Ultrasound Image via Fisher Vector [PLOS ONE 2015] | FV-Chi2-SDCA | Spatial Stacking, Densely Sampled Root Scale Invariant Feature Transform, Gaussian Mixture Model, Fisher Vector, Multilayer Fisher Network, SVM, SP Classification |
| Plane Localization in 3-D Fetal Neurosonography for Longitudinal Analysis of the Developing Brain [JBHI 2015] | CRF-FA-Dist-M | Informative Voxels, Manual Reference Plane, Constrained Regression Forest, SP Localization |
| Standard Plane Localization in Fetal Ultrasound via Domain Transferred Deep Neural Networks [JBHI 2015] | T-CNN | Knowledge Transfer, CNN, SP Localization |
| Automatic Fetal Ultrasound Standard Plane Detection Using Knowledge Transferred Recurrent Neural Networks [MICCAI 2015] | T-RNN | CNN, Knowledge Transfer, Joint Learning, Spatio-temporal Feature, RNN, SP Classification |
| Fetal Facial Standard Plane Recognition via Very Deep Convolutional Networks [EMBC 2016] | - | DCNN, SP Classification |
| Real-Time Standard Scan Plane Detection and Localisation in Fetal Ultrasound Using Fully Convolutional Neural Networks [MICCAI 2016] | - | CNN, Unsupervision, Saliency Maps, AS Localization, SP Classification |
| Ultrasound Standard Plane Detection Using a Composite Neural Network Framework [Transactions on Cybernetics 2017] | T-RNN | CNN, RNN, Composite Framework, SP Classification |
| SonoNet: Real-Time Detection and Localisation of Fetal Standard Scan Planes in Freehand Ultrasound [TMI 2017] [Official Code] [Third-Party Code] | SonoNet | CNN, SP Classification, Weakly Supervision, AS Localization |
| Automatic Detection of Standard Sagittal Plane in the First Trimester of Pregnancy Using 3-D Ultrasound Data [Ultrasound in Medicine and Biology 2017] | - | Deep Belief Network, Circle Detection, SP Classification |
| Attention-Gated Networks for Improving Ultrasound Scan Plane Detection [MIDL 2018] [Official Code] | AG-SonoNet | CNN, Attention, SP Classification, Weakly Supervision, AS Localization |
| Standard Plane Localisation in 3D Fetal Ultrasound Using Network with Geometric and Image Loss [MIDL 2018] | - | CNN, Rigid Transformation, Geometric Loss, Image Loss, SP Localization |
| Standard Plane Detection in 3D Fetal Ultrasound Using an Iterative Transformation Network [MICCAI 2018] [Official Code] | ITN | CNN, Rigid Transformation, SP Localization |
| Automatic and Efficient Standard Plane Recognition in Fetal Ultrasound Images via Multi-scale Dense Networks [MICCAI-DATRA/PIPPI 2018] | MSDNet | Multi-scale, Cascade, Dense Connection, CNN, SP Classification |
| SonoEyeNet: Standardized fetal ultrasound plane detection informed by eye tracking [ISBI 2018] | SonoEyeNet | CNN, Eye Tracking, Visual Heatmap, Information Fusion, SP Classification |
| Multi-task SonoEyeNet: Detection of Fetal Standardized Planes Assisted by Generated Sonographer Attention Maps [MICCAI 2018] | M-SonoEyeNet | Multi-task, CNN, Eye Tracking, GAN, Generator, Sonographer Attention, Discriminator, Predicted Attention, SP Classification |
| Agent with Warm Start and Active Termination for Plane Localization in 3D Ultrasound [MICCAI 2019] | DDQN-AT | Landmark Alignment, Reinforcement Learning, CNN, RNN, SP Localization |
| SPRNet: Automatic Fetal Standard Plane Recognition Network for Ultrasound Images [MICCAI-PIPPI/SUSI 2019] | SPRNet | CNN, Weight-share, Transfer Learning, SP Classification |
| Deep Learning-Based Methodology for Recognition of Fetal Brain Standard Scan Planes in 2D Ultrasound Images [IEEE Access 2019] | - | Data Augmentation, DCNN, Domain Transfer, SP Classification |
| Standard Plane Identification in Fetal Brain Ultrasound Scans Using A Differential Convolutional Neural Network [IEEE Access 2020] | Different-CNN | Differential Operator, Differential CNN, SP Classification |
| Evaluation of Deep Convolutional Neural Networks for Automatic Classification of Common Maternal Fetal Ultrasound Planes [Scientific Reports 2020] [Third-Party Code] | - | Data Augmentation, PCA, Hog, Boosting, VGG, MobileNet, Inception-v3, ResNet, SENet, SE-ResNet, DenseNet, SP Classification |
| Automatic Fetal Middle Sagittal Plane Detection in Ultrasound Using Generative Adversarial Network [Diagnostics 2020] | - | Segmentation, Object Detection, Seed Point, GAN, SP Localization |
| Recognition of Fetal Facial Ultrasound Standard Plane Based on Texture Feature Fusion [CMMM 2021] | LH-SVM | Local Binary Pattern, Histogram of Oriented Gradient, Feature Fusion, SVM, SP Classification |
| Principled Ultrasound Data Augmentation for Classification of Standard Planes [IPMI 2021] | - | Data Augmentation, Augmentation Policy Search, CNN, SP Classification |
| Generative Adversarial Networks to Improve Fetal Brain Fine-Grained Plane Classification [Sensors 2021] | - | GAN, Data Augmentation, CNN, SP Classification |
| Agent with Warm Start and Adaptive Dynamic Termination for Plane Localization in 3D Ultrasound [TMI 2021] [Official Code] | AgentSPL | Landmark Alignment, Reinforcement Learning, CNN, RNN, SP Localization |
| Autonomous Navigation of An Ultrasound Probe Towards Standard Scan Planes with Deep Reinforcement Learning [ICRA 2021] | SonoRL | Reinforcement Learning, Probe Navigation, Confidence-aware Agent, CNN, SP Localization |
| Searching Collaborative Agents for Multi-plane Localization in 3D Ultrasound [MIA 2021] | MARL | Multi-agent, Reinforcement Learning, RNN, NAS, SP Localization |
| Automatic Fetal Ultrasound Standard Plane Recognition Based on Deep Learning and IIoT [Transactions on Industrial Informatics 2021] | FUSPR | CNN, RNN, Spatial-temporal Feature, SP Classification |
| Automatic quality assessment for 2D fetal sonographic standard plane based on multitask learning [Medicine 2021] | - | CNN, AS Classification, Object Detection, AS Localization, SP Quality Control |
| Statistical Dependency Guided Contrastive Learning for Multiple Labeling in Prenatal Ultrasound [MICCAI-MLMI 2021] | MLL-GCN-CRC | Word Embedding, GCN, CNN, Cluster Relabeled Contrastive Learning, Multi-label, AS Classification, SP Classification |
| Agent with Tangent-based Formulation and Anatomical Perception for Standard Plane Localization in 3D Ultrasound [MICCAI 2022] | - | Reinforcement Learning, Restructure the Action Space, Content-aware Regression Auxiliary Task, Spatial-anatomical Reward, CNN, Landmark Heatmap, SP Localization |
Tags: Standard Plane --> SP | Anatomical Structure --> AS
- 6 Classes:
- Fetal Anatomical Planes: Abdomen, Brain (Further categorized into the 3 most common fetal brain planes: Trans-thalamic, Trans-cerebellum, Trans-ventricular), Femur, Thorax.
- Mother’s Cervix.
- General Category: Including any other less common image plane.
- Meta Information: Patient number, US machine, Operator.
- Training-test split used in the Nature Sci Rep paper.
- Practice: infer.py
- Practice: train_FPD_Classification.py
- Practice: main.py
Thanks to the contributors of all the above papers, code, public datasets, and other resources.
Contributing
If you have any suggestions or improvements, please feel free to create issues or pull requests.