Medical Semantic Segmentation

Medical semantic segmentation uses deep learning to automatically identify and delineate anatomical structures in medical images, aiming for accurate and reliable computer-aided diagnosis and treatment planning. Current research emphasizes improving model robustness and interpretability, exploring techniques like masked autoencoders with refined masking strategies, and incorporating uncertainty quantification through confidence contours to enhance clinical trust. These advancements, along with the development of efficient architectures like U-Net variations and transformers, are crucial for overcoming limitations in labeled data availability and improving the accuracy and explainability of medical image analysis.

Papers

September 30, 2024

Leveraging CAM Algorithms for Explaining Medical Semantic Segmentation
Tillmann Rheude, Andreas Wirtz, Arjan Kuijper, Stefan Wesarg
Convolutional Neural Network Semantic Segmentation Segmentation Task Class Activation Grad CAM Medical Semantic Segmentation

August 15, 2023

Confidence Contours: Uncertainty-Aware Annotation for Medical Semantic Segmentation
Andre Ye, Quan Ze Chen, Amy Zhang
Segmentation Model Confidence Map Medical Semantic Segmentation

May 10, 2023

Medical supervised masked autoencoders: Crafting a better masking strategy and efficient fine-tuning schedule for medical image classification
Jiawei Mao, Shujian Guo, Yuanqi Chang, Xuesong Yin, Binling Nie
Fine Tuning Supervised Autoencoder Medical Image Classification Masked Autoencoders Random Masking Medical Semantic Segmentation

March 10, 2023

Explainable Semantic Medical Image Segmentation with Style
Wei Dai, Siyu Liu, Craig B. Engstrom, Shekhar S. Chandra
Segmentation Model Manifold Learning Style Consistency Interpretable Segmentation Medical Semantic Segmentation

February 23, 2023

PLU-Net: Extraction of multi-scale feature fusion
Weihu Song
Medical Image Segmentation Process Extraction Multi Scale Feature Fusion Spatial Pyramid Pooling Poor Segmentation Medical Semantic Segmentation

December 17, 2022

Annotation by Clicks: A Point-Supervised Contrastive Variance Method for Medical Semantic Segmentation
Qing En, Yuhong Guo
Contrastive Learning Loss Function Segmentation Model Annotation Rather Accidental Click Medical Semantic Segmentation

July 31, 2022

FixMatchSeg: Fixing FixMatch for Semi-Supervised Semantic Segmentation
Pratima Upretee, Bishesh Khanal
Semantic Segmentation Semi Supervised Semantic Segmentation Semi Supervised Segmentation Semi Supervised Classification Medical Semantic Segmentation

July 28, 2022

A Transformer-based Generative Adversarial Network for Brain Tumor Segmentation
Liqun Huang, Long Chen, Baihai Zhang, Senchun Chai
Brain Tumor Segmentation Medical Image Segmentation Task Multi Modal MRI Transformer Based Generative Adversarial Medical Semantic Segmentation

April 2, 2022

Histogram of Oriented Gradients Meet Deep Learning: A Novel Multi-task Deep Network for Medical Image Semantic Segmentation
Binod Bhattarai, Ronast Subedi, Rebati Raman Gaire, Eduard Vazquez, Danail Stoyanov
Semantic Segmentation Medical Image Segmentation Multi Task Learning Multi Task Semantic Segmentation Network Histogram Layer Semantic Segmentation Mask Medical Semantic Segmentation

March 28, 2022

Translation Consistent Semi-supervised Segmentation for 3D Medical Images
Yuyuan Liu, Yu Tian, Chong Wang, Yuanhong Chen, Fengbei Liu, Vasileios Belagiannis, Gustavo Carneiro
Medical Image Segmentation Segmentation Based Approach Brain Tumor Segmentation 3D Medical Image Consistency Learning Medical Semantic Segmentation

January 8, 2022

A Baseline Statistical Method For Robust User-Assisted Multiple Segmentation
Huseyin Afser
Segmentation Method Image Region Statistical Method Medical Semantic Segmentation

December 1, 2021

Reference-guided Pseudo-Label Generation for Medical Semantic Segmentation
Constantin Seibold, Simon Reiß, Jens Kleesiek, Rainer Stiefelhagen
Pseudo Label Supervised Learning Pseudo Labeling Semi Supervised Semantic Segmentation Retinal Lesion Segmentation Medical Semantic Segmentation