base models in 'From CNN to Transformer: a Review of Medical Image Segmentation Models'

[IEEE JBHI, 2023] Towards Connectivity-Aware Pulmonary Airway Segmentation

NaviAirway: a Bronchiole-sensitive Deep Learning-based Airway Segmentation Pipeline

Airway segmentation from chest CTs using deep Convolutional Neural Networks

Pytorch implementation for Semantic Segmentation with multi models (Deeplabv3, Deeplabv3_plus, PSPNet, UNet, UNet_AutoEncoder, UNet_nested, R2AttUNet, AttentionUNet, RecurrentUNet,, SEGNet, CENet, …

[IEEE TMI] Official Implementation for UNet++

Use of Attention Gates in a Convolutional Neural Network / Medical Image Classification and Segmentation

Official repository for reproducing COVID and Lung segmentation prediction (old version of MEDPSeg)

pyTorch implementation of clDice

[MedIA 2023/MICCAI 2022 Grand Challenge]: Airway Tree Modeling (ATM'22) Related Work Collections, also includes the state-of-the-art works on pulmonary airway segmentation and related works.

🧑‍🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), ga…

🎨 Semantic segmentation models, datasets and losses implemented in PyTorch.

A pytorch-based deep learning framework for multi-modal 2D/3D medical image segmentation

PyTorch深度学习快速入门教程（绝对通俗易懂！）

Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media

《利用Python进行数据分析·第2版》

Implementation of cats-vs-dogs based on CNN.