readme.md

Awesome medical image papers

This repository contains the medical image paper reading lists.

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Overview

• introduction
• Self-supervised learning
  • Classification
  • Segmentation
• Transformer
  • Segmentation

Introduction

This paper list contains papers related to the deep-learning approach to solve problems in the medical image domain.

• Other awesome paper lists:
  • Medical awesome SSL github

Self-supervised learning

Papers about self-supervised learning (SSL) in the medical image domain.

Classification

Apply SSL to improve classification performance in the medical image domain.

• MICLe: "Big Self-Supervised Models Advance Medical Image Classification", ICCV, 2021 [paper] [code] [summary]

Segmentation

Apply SSL to improve segmentation performance in the medical image domain.

• SwinUNETR: "Self-Supervised Pre-Training of Swin Transformers for 3D Medical Image Analysis", CVPR, 2022 [paper] [code] [summary]

Transformer

Papers about transformer architecture in the medical image domain.

Classification

Apply Transformer architecture to improve classification performance in the medical image domain.

• AnaXNet: "Anatomy Aware Multi-label Finding Classicationin Chest X-ray", MICCAI, 2021 [paper] [not available] [summary]
• Cross-View Transformer: "Multi-view Analysis of Unregistered Medical Images Using Cross-View Transformers", MICCAI, 2021 [paper] [not available] [summary]
• MICLe: "Big Self-Supervised Model Advance Medical Image Classification", MICCAI, 2021 [paper] [not available] [summary]

Segmentation

Apply Transformer architecture to improve segmentation performance in the medical image domain.

• TransUNet: "Transformers Make Strong Encoders for Medical Image Segmentation", ArXiv, 2021 [paper] [code] [summary]
• Swin-Unet: "Unet-like Pure Transformer for Medical Image Segmentation", ArXiv, 2021 [paper] [code] [summary]