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

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Showing 401–410 of 424 papers

Title	Date	Tasks	Status
Expert-Like Reparameterization of Heterogeneous Pyramid Receptive Fields in Efficient CNNs for Fair Medical Image Classification	May 19, 2025	Fairnessimage-classification	—Unverified
Simple black-box universal adversarial attacks on medical image classification based on deep neural networks	Aug 11, 2021	image-classificationImage Classification	—Unverified
Data Augmentation using Feature Generation for Volumetric Medical Images	Sep 28, 2022	ClassificationData Augmentation	—Unverified
Explaining Clinical Decision Support Systems in Medical Imaging using Cycle-Consistent Activation Maximization	Oct 9, 2020	Breast Cancer DetectionDecision Making	—Unverified
Explanations of Classifiers Enhance Medical Image Segmentation via End-to-end Pre-training	Jan 16, 2024	image-classificationImage Classification	—Unverified
Exploring Low-Resource Medical Image Classification with Weakly Supervised Prompt Learning	Feb 6, 2024	Few-Shot Learningimage-classification	—Unverified
Exploring the Transferability of a Foundation Model for Fundus Images: Application to Hypertensive Retinopathy	Jan 27, 2024	image-classificationImage Classification	—Unverified
Exploring the Versatility of Zero-Shot CLIP for Interstitial Lung Disease Classification	Jun 1, 2023	ClassificationDiagnostic	—Unverified
Curriculum Fine-tuning of Vision Foundation Model for Medical Image Classification Under Label Noise	Nov 29, 2024	image-classificationImage Classification	—Unverified
Cross-Modal Information Maximization for Medical Imaging: CMIM	Oct 20, 2020	image-classificationImage Classification	—Unverified

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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