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paper.md

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 Understanding diffusion processes is particularly important for clinical imaging to distinguish between healthy and pathological tissues or between benign and malignant lesions. Computational models of diffusion allow us to predict specific architectural properties of biological tissues which correlate to the measured values of diffusion imaging, thus providing a deeper understanding of certain pathologies *in vivo*. Here we present a free and open-source MATLAB tool developed for that purpose.
 
-In homogeneous and isotropic media, diffusion has a Gaussian behavior and is statistically described  by the Einstein's Brownian motion equation. A probability density function (PDF) of the proportion of particles displaced in a given direction [@einstein1956investigations]. In complex heterogeneous environments such as biological tissues, the movement of water molecules is highly constrained by barriers such as those related to cellular components: membranes, organelles and large proteins, in which case, diffusion has a non-gaussian behavior, and tissue micro-structural complexity is characterized by observing the deviation from a normal distribution [@jensen2010mri].
+In homogeneous and isotropic media, diffusion has a Gaussian behavior and is statistically described  by Einstein's Brownian motion equation. A probability density function (PDF) of the proportion of particles displaced in a given direction [@einstein1956investigations]. In complex heterogeneous environments such as biological tissues, the movement of water molecules is highly constrained by barriers such as those related to cellular components: membranes, organelles and large proteins, in which case, diffusion has a non-gaussian behavior, and tissue micro-structural complexity is characterized by observing the deviation from a normal distribution [@jensen2010mri].
 
 Diffusion-Weighted Imaging (DWI), Diffusion Kurtosis Imaging (DKI) and Diffusion Tensor Imaging (DTI), are different Magnetic Resonance Imaging (MRI) techniques which take advantage of water diffusion properties in biological tissues for the purpose of characterizing tissue micro-structural complexity *in vivo*. These techniques have shown to be very useful in quantifying the complexity of tissue barriers, and for characterizing microstructural changes due to injury, treatment, disease or even normal physiological changes such as aging, including in cases of anisotropic diffusion, namely the case of white matter in the brain, where diffusion is essentially parallel to axonal membranes but highly restricted in the directions perpendicular to axons [@jensen2005diffusional; @fieremans2011white; @henriques2015exploring; @basser1994estimation; @basser1994mr].
 
@@ -51,4 +51,4 @@ The MATLAB toolbox `MCSD` is available at https://github.com/davidnsousa/mcsd. I
 
 In the MATLAB/Octave command line type `help` followed by the name of each one of the functions above for further details about input and output parameters. In the github repository, at `tutorial/`, the user can also find a tutorial with more details and various examples. A replication script of the tutorial examples is also provided for MATLAB users.
 
-Combining theoretical and computational insights about diffusion processes with the knowledge acquired from imaging techniques has proved to be an important research direction for understanding the micro-structural complexity of biological tissues. But, as yet, no simple and free open-source tools are available for researchers in this field to test their basic predictions. `MCSD` offers such possibility. The functions provided by `MCSD` are highly flexible and useful for the design of complex random walk environments such as biological tissues. In fact, although `MCSD` was developed specifically to simulate diffusion processes in such environments, researchers from other fields might find this package useful as well.
+Combining theoretical and computational insights about diffusion processes with the knowledge acquired from imaging techniques has proved to be an important research direction for understanding the micro-structural complexity of biological tissues. But, as yet, no simple and free open-source tools are available for researchers in this field to test their basic predictions. `MCSD` offers such possibility. The functions provided by `MCSD` are highly flexible and useful for the design of complex random walk environments such as biological tissues. In fact, although `MCSD` was developed specifically to simulate diffusion processes in such environments, researchers from other fields might find this package useful as well.