Yun Wang's repositories
Baby_CNN
Unet--baby MRI brain segmenation
fastai-v3
Starter app for fastai v3 model deployment on Render
fastbook
The fastai book, published as Jupyter Notebooks
hypothalamus_seg
a tool to segment the hypothalamus and associated subunits on T1-weighted MRI scans
Infant-DWI-April
Complete pipeline to perform tractography from infant diffusion MRI data. 2024 April version
MFSDA_Python
Multivariate Functional Shape Data Analysis in Python (MFSDA_Python) is a Python based package for statistical shape analysis. A multivariate varying coefficient model is introduced to build the association between the multivariate shape measurements and demographic information and other clinical, biological variables. Statistical inference, i.e., hypothesis testing, is also included in this package, which can be used in investigating whether some covariates of interest are significantly associated with the shape information. The hypothesis testing results are further used in clustering based analysis, i.e., significant suregion detection. This MFSDA package is developed by Chao Huang and Hongtu Zhu from the BIG-S2 lab.
MRIDoc
Share MRI knowledge through this github
quickNAT_pytorch
PyTorch Implementation of QuickNAT and Bayesian QuickNAT, a fast brain MRI segmentation framework with segmentation Quality control using structure-wise uncertainty
SeBRe
Developing Brain Atlas through Deep Learning
shap
A game theoretic approach to explain the output of any machine learning model.