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Medical Image Classification

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하위 태스크: 1
평가표: 11
보존된 평가 기록: 20

Medical Image Classification is a task in medical image analysis that involves classifying medical images, such as X-rays, MRI scans, and CT scans, into different categories based on the type of image or the presence of specific structures or diseases. The goal is to use computer algorithms to automatically identify and classify medical images based on their content, which can help in diagnosis, treatment planning, and disease monitoring.

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://bitbucket.org/raghavian/lotenet_pytorch

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Tensor Networks for Medical Image Classification

https://github.com/ATHdevs/Auto-PCOS

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Leveraging AI for Automatic Classification of PCOS Using Ultrasound Imaging

https://github.com/Adnan-Sadi/LMFLOSS

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LMFLOSS: A Hybrid Loss For Imbalanced Medical Image Classification

https://github.com/AriChow/EL

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Emergent symbolic language based deep medical image classification

https://github.com/Bidur-Khanal/imbalanced-medical-active-label-cleaning

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Active Label Refinement for Robust Training of Imbalanced Medical Image Classification Tasks in the Presence of High Label Noise

https://github.com/BioIntelligence-Lab/IntelligentStreaming

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ISLE: An Intelligent Streaming Framework for High-Throughput AI Inference in Medical Imaging

https://github.com/FBLADL/ACPL

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ACPL: Anti-curriculum Pseudo-labelling for Semi-supervised Medical Image Classification

https://github.com/JackqqWang/fedhelp

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Asymmetrical Reciprocity-based Federated Learning for Resolving Disparities in Medical Diagnosis

https://github.com/JoohyungLee0106/rectal_MR_volume_classification

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Moving from 2D to 3D: volumetric medical image classification for rectal cancer staging

https://github.com/Jwicaksana/FedNPR

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Non-parametric regularization for class imbalance federated medical image classification

https://github.com/KaimingHe/resnet-1k-layers

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Deep Residual Learning for Image Recognition

https://github.com/LeapLabTHU/CheXWorld

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CheXWorld: Exploring Image World Modeling for Radiograph Representation Learning

https://github.com/NAVER-INTEL-Co-Lab/gaudi-byzantine

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Embedding Byzantine Fault Tolerance into Federated Learning via Virtual Data-Driven Consistency Scoring Plugin

https://github.com/Omid-Nejati/MedViT

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MedViT: A Robust Vision Transformer for Generalized Medical Image Classification

https://github.com/Omid-Nejati/MedViTV2

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Medical Image Classification with KAN-Integrated Transformers and Dilated Neighborhood Attention

https://github.com/Optimization-AI/LibAUC

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Large-scale Robust Deep AUC Maximization: A New Surrogate Loss and Empirical Studies on Medical Image Classification

https://github.com/Prasanna1991/LatentMixing

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Semi-supervised Medical Image Classification with Global Latent Mixing

https://github.com/Project-MONAI/MONAI

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MONAI: An open-source framework for deep learning in healthcare

https://github.com/Rishit-dagli/Astroformer

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Astroformer: More Data Might not be all you need for Classification

https://github.com/TUM-AIMED/2.5DAttention

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Private, fair and accurate: Training large-scale, privacy-preserving AI models in medical imaging

https://github.com/Talented-Q/MSMAE

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Medical supervised masked autoencoders: Crafting a better masking strategy and efficient fine-tuning schedule for medical image classification

https://github.com/TiagoFilipeSousaGoncalves/survey-attention-medical-imaging

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A survey on attention mechanisms for medical applications: are we moving towards better algorithms?

https://github.com/YubiaoYue/MedMamba

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MedMamba: Vision Mamba for Medical Image Classification

https://github.com/abrahamgenetu/Automated_Malaria_Detection_System

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Automated Web-Based Malaria Detection System with Machine Learning and Deep Learning Techniques: A Comparative Analysis

https://github.com/agaldran/balanced_mixup

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Balanced-MixUp for Highly Imbalanced Medical Image Classification

https://github.com/aipmlab/facmic

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FACMIC: Federated Adaptative CLIP Model for Medical Image Classification

https://github.com/aipmlab/skincancersimulation

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Deep Modeling and Optimization of Medical Image Classification

https://github.com/ameliajimenez/capsule-networks-medical-data-challenges

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Capsule Networks against Medical Imaging Data Challenges

https://github.com/ameliajimenez/shortcuts-chest-xray

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Detecting Shortcuts in Medical Images -- A Case Study in Chest X-rays

https://github.com/andreanne-lemay/gray_zone_assessment

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Improving the repeatability of deep learning models with Monte Carlo dropout

https://github.com/aryan-at-ul/aics_2023_submission

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Connecting the Dots: Graph Neural Network Powered Ensemble and Classification of Medical Images

https://github.com/basiralab/unifed

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UniFed: A Universal Federation of a Mixture of Highly Heterogeneous Medical Image Classification Tasks

https://github.com/bayu-ladom-ipok/weOpen

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An Aggregate Method for Thorax Diseases Classification

https://github.com/bbrattoli/JigsawPuzzlePytorch

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Improving Medical Image Classification in Noisy Labels Using Only Self-supervised Pretraining

https://github.com/biomedia-mbzuai/condisr

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ConDiSR: Contrastive Disentanglement and Style Regularization for Single Domain Generalization

https://github.com/biomedia-mira/subgroup-separability

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The Role of Subgroup Separability in Group-Fair Medical Image Classification

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