Medical Image Classification

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.

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 51–60 of 424 papers

Title	Date	Tasks	Status	Hype
ACPL: Anti-curriculum Pseudo-labelling for Semi-supervised Medical Image Classification	Nov 25, 2021	image-classificationImage Classification	CodeCode Available	1
Categorical Relation-Preserving Contrastive Knowledge Distillation for Medical Image Classification	Jul 7, 2021	Classificationimage-classification	CodeCode Available	1
Contrastive Learning of Medical Visual Representations from Paired Images and Text	Oct 2, 2020	Contrastive LearningDescriptive	CodeCode Available	1
CASS: Cross Architectural Self-Supervision for Medical Image Analysis	Jun 8, 2022	ClassificationMedical Image Analysis	CodeCode Available	1
Big Self-Supervised Models Advance Medical Image Classification	Jan 13, 2021	ClassificationContrastive Learning	CodeCode Available	1
Interpretable Medical Image Classification using Prototype Learning and Privileged Information	Oct 24, 2023	image-classificationImage Classification	CodeCode Available	1
Joint Learning of Localized Representations from Medical Images and Reports	Dec 6, 2021	Contrastive Learningimage-classification	CodeCode Available	1
Learning Concept-Driven Logical Rules for Interpretable and Generalizable Medical Image Classification	May 20, 2025	image-classificationImage Classification	CodeCode Available	1
Counterfactual Explanations for Medical Image Classification and Regression using Diffusion Autoencoder	Aug 2, 2024	counterfactualimage-classification	CodeCode Available	1
CheXFusion: Effective Fusion of Multi-View Features using Transformers for Long-Tailed Chest X-Ray Classification	Aug 8, 2023	ClassificationDiagnostic	CodeCode Available	1

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All datasets NCT-CRC-HE-100K IDRiD ImageNet PCOS Classification CheXphoto Galaxy10 DECals ISIC 2017 ISIC 2020 Challenge Dataset Malaria Dataset OASIS 3

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	Efficientnet-b0	Accuracy (%)	95.59	—	Unverified
2	ResNeXt-50-32x4d	Accuracy (%)	95.46	—	Unverified
3	RegNetY-3.2GF	Accuracy (%)	95.42	—	Unverified
4	ResNet-50	Accuracy (%)	94.72	—	Unverified
5	DenseNet-169	Accuracy (%)	94.41	—	Unverified
6	Res2Net-50	Accuracy (%)	93.37	—	Unverified
7	ResNet-18	Accuracy (%)	92.66	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ResNet-152	Accuracy (% )	86.56	—	Unverified
2	Beta-Rank	Accuracy	81.88	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DaViT-S	GFLOPs	8.8	—	Unverified
2	DaViT-T	GFLOPs	4.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	InceptionV3	1:1 Accuracy	90.2	—	Unverified
2	EfficientNet B7	1:1 Accuracy	88.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	PTRN	Mean AUC	0.85	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Astroformer	Top-1 Accuracy (%)	94.87	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Beta-Rank	Accuracy	72.44	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	EfficientNet Ensemble	AUC	0.95	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SNAPSHOT ENSEMBLE	F1 score	99.37	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	3D CNN	AUC	87	—	Unverified