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 201–210 of 424 papers

Title	Date	Tasks	Status
Benchmarking MedMNIST dataset on real quantum hardware	Feb 18, 2025	Benchmarkingimage-classification	—Unverified
Data Augmentation using Feature Generation for Volumetric Medical Images	Sep 28, 2022	ClassificationData Augmentation	—Unverified
Curriculum Fine-tuning of Vision Foundation Model for Medical Image Classification Under Label Noise	Nov 29, 2024	image-classificationImage Classification	—Unverified
Aligning Human Knowledge with Visual Concepts Towards Explainable Medical Image Classification	Jun 8, 2024	Decision MakingDiagnostic	—Unverified
Active Globally Explainable Learning for Medical Images via Class Association Embedding and Cyclic Adversarial Generation	Jun 12, 2023	counterfactualExplainable Artificial Intelligence (XAI)	—Unverified
4S-DT: Self Supervised Super Sample Decomposition for Transfer learning with application to COVID-19 detection	Jun 26, 2020	General Classificationimage-classification	—Unverified
Cross-Modal Information Maximization for Medical Imaging: CMIM	Oct 20, 2020	image-classificationImage Classification	—Unverified
Covid-19: Automatic detection from X-Ray images utilizing Transfer Learning with Convolutional Neural Networks	Mar 25, 2020	image-classificationImage Classification	—Unverified
CoRPA: Adversarial Image Generation for Chest X-rays Using Concept Vector Perturbations and Generative Models	Feb 4, 2025	Adversarial AttackDiagnostic	—Unverified
CopilotCAD: Empowering Radiologists with Report Completion Models and Quantitative Evidence from Medical Image Foundation Models	Apr 11, 2024	Diagnosticimage-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