Pinned Repositories
2
ADHD200
scripts to process the ADHD200 dataset
brain-tumor-mri-dataset
Utilities to download and load an MRI brain tumor dataset with Python, providing 2D slices, tumor masks and tumor classes.
DeepLearningInMedicalImagingAndMedicalImageAnalysis
examples
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
HCP_Dataset_Download_Automatically_Script
This script can download the HCP dataset automatically from amazon s3 browser by using python. You can download tfMRI, rfMRI, dfMRI, MEG etc. dataset from amazon s3 of HCP.
HCP_download
Script to download data from the Human Connectome Project, HCP-1200 subjects release.
IPN_tensorflow
This is an implementation of "Image Projection Network: 3D to 2D Image Segmentation in OCTA Images". IPN is proposed for 3D to 2D segmentation. Our key insight is to build a projection learning module(PLM) which uses a unidirectional pooling layer to conduct effective features selection and dimension reduction concurrently.By combining multiple PLMs, the proposed network can input 3D data and output 2D segmentation results.
Models
Project-PPMI
Analyze Data from a Large Parkinson's Clinical Study
lyp201806011002's Repositories
lyp201806011002/DeepLearningInMedicalImagingAndMedicalImageAnalysis
lyp201806011002/2
lyp201806011002/ADHD200
scripts to process the ADHD200 dataset
lyp201806011002/brain-tumor-mri-dataset
Utilities to download and load an MRI brain tumor dataset with Python, providing 2D slices, tumor masks and tumor classes.
lyp201806011002/examples
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
lyp201806011002/HCP_Dataset_Download_Automatically_Script
This script can download the HCP dataset automatically from amazon s3 browser by using python. You can download tfMRI, rfMRI, dfMRI, MEG etc. dataset from amazon s3 of HCP.
lyp201806011002/HCP_download
Script to download data from the Human Connectome Project, HCP-1200 subjects release.
lyp201806011002/IPN_tensorflow
This is an implementation of "Image Projection Network: 3D to 2D Image Segmentation in OCTA Images". IPN is proposed for 3D to 2D segmentation. Our key insight is to build a projection learning module(PLM) which uses a unidirectional pooling layer to conduct effective features selection and dimension reduction concurrently.By combining multiple PLMs, the proposed network can input 3D data and output 2D segmentation results.
lyp201806011002/Models
lyp201806011002/Project-PPMI
Analyze Data from a Large Parkinson's Clinical Study
lyp201806011002/PyTorch-Course
JULYEDU PyTorch Course
lyp201806011002/vision
Datasets, Transforms and Models specific to Computer Vision