The official GitHub repository of the survey paper "A Systematic Review of Deep Learning-based Research on Radiology Report Generation".

Understanding Deep Learning - Simon J.D. Prince

Released assignments for the Stanford's CS131 course on Computer Vision.

Abdominal Organ Segmentation of UK Biobank and GNC Studies

[NeurIPS 2023] AbdomenAtlas

This repository is for the first comprehensive survey on Meta AI's Segment Anything Model (SAM).

Grounded-SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything

Rank first in Medical Segmentation Decathlon (MSD) Competition.

UniverSeg: Universal Medical Image Segmentation

A collection of literature after or concurrent with Masked Autoencoder (MAE) (Kaiming He el al.).

public code repository for paper "Health system scale language models are general purpose clinical prediction engines"

[ISBI'21, CBM'22] TRFE-Net for thyroid nodule segmentation

ChatGLM-6B：开源双语对话语言模型 | An Open Bilingual Dialogue Language Model

A playbook for systematically maximizing the performance of deep learning models.

[MICCAI, 2022, Challenge]: Airway Tree Modeling (ATM'22) Related Work Collections

12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

10 Weeks, 20 Lessons, Data Science for All!

AMOS: A Large-Scale Abdominal Multi-Organ Benchmark for Versatile Medical Image Segmentation

Subject-Specific Lesion Generation and Pseudo-Healthy Synthesis for Multiple Sclerosis Brain Images

The official Pytorch implementation of OCNet series and SegFix.

Code used in the lifespan brainchart project

PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more

A resource repository for 3D machine learning

Implementation of "Pix2Vox: Context-aware 3D Reconstruction from Single and Multi-view Images". (Xie et al., ICCV 2019)

The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.

This is an official pytorch implementation of Lite-HRNet: A Lightweight High-Resolution Network.