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 1–10 of 424 papers

Title	Date	Tasks	Status	Hype
MONAI: An open-source framework for deep learning in healthcare	Nov 4, 2022	Deep LearningMedical Image Classification	CodeCode Available	5
MedMamba: Vision Mamba for Medical Image Classification	Mar 6, 2024	Classificationimage-classification	CodeCode Available	4
RegNet: Self-Regulated Network for Image Classification	Jan 3, 2021	ClassificationGeneral Classification	CodeCode Available	4
Deep Residual Learning for Image Recognition	Dec 10, 2015	Classification	CodeCode Available	4
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks	May 28, 2019	Action RecognitionDomain Generalization	CodeCode Available	3
MedViT: A Robust Vision Transformer for Generalized Medical Image Classification	Feb 19, 2023	image-classificationImage Classification	CodeCode Available	2
MedFMC: A Real-world Dataset and Benchmark For Foundation Model Adaptation in Medical Image Classification	Jun 16, 2023	Diabetic Retinopathy Gradingimage-classification	CodeCode Available	2
DaViT: Dual Attention Vision Transformers	Apr 7, 2022	Computational EfficiencyImage Classification	CodeCode Available	2
HiFuse: Hierarchical Multi-Scale Feature Fusion Network for Medical Image Classification	Sep 21, 2022	Classificationimage-classification	CodeCode Available	2
Medical Image Classification with KAN-Integrated Transformers and Dilated Neighborhood Attention	Feb 19, 2025	image-classificationImage Classification	CodeCode Available	2

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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