Contijoch Research Laboratory
Research Website for Contijoch Research Lab at UC San Diego
United States of America
Pinned Repositories
2DUNet_CT_Seg_Final_v_ZC
a 2D U-Net pipeline to segment heart chambers in CT 3D volumes. Author: Zhennong Chen, PhD.
AI_chamber_segmentation_plane_re-slicing
A deep learning (DL) pipeline to simultaneously predict multi-chamber segmentation and all cardiac imaging planes. Author: Zhennong Chen, PhD
autoseg_deploy
BaseDockerImages
Base Docker Images build on top of NVIDIA CUDA XX.X and includes anaconda, other useful packages.
DL_WMA_by_VR_Final_v_ZC
A deep learning pipeline to detect Left Ventricle Wall Motion Abnormality from volume-rendered 4DCT data. Author: Zhennong Chen, PhD
med-img-octnet-adaptation
Adaptation of OctNet for use in Medical Images
NeuralCT_new_seg_Final_v_ZC
An implicit neural representation framework to correct motion artifacts from CT. Author: Zhennong Chen, PhD
PSM-Work-Mapping
Patient-specific modeling assessment of myocardial work with simple and robust clinical datasets
Pytorch-UNet
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
UNet_image_to_image
A image-to-image UNet, tensorflow 2.4.1
Contijoch Research Laboratory's Repositories
ucsd-fcrl/AI_chamber_segmentation_plane_re-slicing
A deep learning (DL) pipeline to simultaneously predict multi-chamber segmentation and all cardiac imaging planes. Author: Zhennong Chen, PhD
ucsd-fcrl/2DUNet_CT_Seg_Final_v_ZC
a 2D U-Net pipeline to segment heart chambers in CT 3D volumes. Author: Zhennong Chen, PhD.
ucsd-fcrl/DL_WMA_by_VR_Final_v_ZC
A deep learning pipeline to detect Left Ventricle Wall Motion Abnormality from volume-rendered 4DCT data. Author: Zhennong Chen, PhD
ucsd-fcrl/med-img-octnet-adaptation
Adaptation of OctNet for use in Medical Images
ucsd-fcrl/NeuralCT_new_seg_Final_v_ZC
An implicit neural representation framework to correct motion artifacts from CT. Author: Zhennong Chen, PhD
ucsd-fcrl/.github
ucsd-fcrl/autoseg_deploy
ucsd-fcrl/BaseDockerImages
Base Docker Images build on top of NVIDIA CUDA XX.X and includes anaconda, other useful packages.
ucsd-fcrl/DL_CT_GLS_Final
Code used to measure GLS from long-axis segmentations
ucsd-fcrl/PSM-Work-Mapping
Patient-specific modeling assessment of myocardial work with simple and robust clinical datasets
ucsd-fcrl/Pytorch-UNet
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
ucsd-fcrl/UNet_image_to_image
A image-to-image UNet, tensorflow 2.4.1
ucsd-fcrl/CatSim
Simulation and Reconstruction Package
ucsd-fcrl/DL_CT_Seg-Plane_Prediction_Final_v_ZC
Use trained deep learning (DL) model (modified 3D U-Net) to predict chamber segmentation and cardiac imaging planes on new cases. Author: Zhennong Chen, PhD
ucsd-fcrl/dv-commandline-utils
ucsd-fcrl/dvpy
ucsd-fcrl/fcrl-filt-back-proj
Filtered backprojection in python without explicit use of Radon transform functions
ucsd-fcrl/hexblender
A Blender addon that allows for working with hexahedral elements
ucsd-fcrl/rv-rmwct-study
Data and analysis scripts for MWCT paper
ucsd-fcrl/unet_deploy