LiTS - Liver Tumor Segmentation Challenge

💥 Command line tool for automatic liver parenchyma and liver vessel segmentation in CT using a pretrained deep learning model

R Data: Single cell RNA sequencing of human liver reveals distinct intrahepatic macrophage populations

a PyQt5 Implementation

3D Slicer extension for liver analysis and therapy planning

Fatty Liver Level Recognition Using Particle Swarm optimization (PSO) Image Segmentation and Analysis

MultiResDenseUNet (SVOISP-2021-KH&KTMT-125) - Winner (3rd Prize) of The 10th Science and Technology Symposium for OISP Students. Ho Chi Minh City University Of Technology, Vietnam.

End-to-end AI Liver Segmentation Network on CT

Evaluation of volume-to-surface non-rigid registration using the PBSM method

大学本科毕业设计

sadly not an actual .exe

A Model to Detect liver Tumor From CT scans.

Codes for my project called " Fatty Liver Classification and Scaling: from 0 to 2 using CNN." In this project, I've created my own neural network and trained it with the images of the kidneys with the fat level scaling from 0 to 2. With each given new data to the network, the programme indicates which level of fatness the liver is categorized.

Gut microbiota fuels HCC development by shaping the hepatic inflammatory microenvironment

Generate expression matrix from microarray data derived from BXD liver

Computer Vision with PyTorch for Medical Image Analysis

It is a standalone application that can help radiologist in segmenting liver (DICOM image) using a region growing function and contouring to find the area of the segmented liver along with manual segmentation where the radiologist can segment the diseased liver manually along with providing notes for the segmented region.

This project is a Content Management System made for the King's College Hospital.

Hepatocyte-specific NRF2 activation controls fibrogenesis and carcinogenesis in steatohepatitis