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 31–40 of 424 papers

Title	Date	Tasks	Status
Hierarchical Vision Transformer with Prototypes for Interpretable Medical Image Classification	Feb 13, 2025	image-classificationImage Classification	—Unverified
Long-tailed Medical Diagnosis with Relation-aware Representation Learning and Iterative Classifier Calibration	Feb 5, 2025	Classifier calibrationDiagnostic	CodeCode Available
Hybrid Deep Learning Framework for Classification of Kidney CT Images: Diagnosis of Stones, Cysts, and Tumors	Feb 5, 2025	Deep Learningimage-classification	—Unverified
CoRPA: Adversarial Image Generation for Chest X-rays Using Concept Vector Perturbations and Generative Models	Feb 4, 2025	Adversarial AttackDiagnostic	—Unverified
ViT-2SPN: Vision Transformer-based Dual-Stream Self-Supervised Pretraining Networks for Retinal OCT Classification	Jan 28, 2025	Data AugmentationDiagnostic	CodeCode Available
Generating customized prompts for Zero-Shot Rare Event Medical Image Classification using LLM	Jan 27, 2025	DescriptiveEvent Detection	CodeCode Available
Rethinking Foundation Models for Medical Image Classification through a Benchmark Study on MedMNIST	Jan 24, 2025	Classificationimage-classification	—Unverified
Estimating the Conformal Prediction Threshold from Noisy Labels	Jan 22, 2025	Conformal Predictionimage-classification	CodeCode Available
CBVLM: Training-free Explainable Concept-based Large Vision Language Models for Medical Image Classification	Jan 21, 2025	Disease Predictionimage-classification	—Unverified
KPL: Training-Free Medical Knowledge Mining of Vision-Language Models	Jan 20, 2025	Classificationimage-classification	CodeCode Available

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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