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 221–230 of 424 papers

Title	Date	Tasks	Status
Imbalanced Classification in Medical Imaging via Regrouping	Oct 21, 2022	Classificationimage-classification	—Unverified
Improved EATFormer: A Vision Transformer for Medical Image Classification	Mar 19, 2024	Classificationimage-classification	—Unverified
Statistical Dependency Guided Contrastive Learning for Multiple Labeling in Prenatal Ultrasound	Aug 11, 2021	Contrastive LearningDiagnostic	—Unverified
CLOG-CD: Curriculum Learning based on Oscillating Granularity of Class Decomposed Medical Image Classification	May 3, 2025	image-classificationImage Classification	—Unverified
Improving Medical Image Classification with Label Noise Using Dual-uncertainty Estimation	Feb 28, 2021	BenchmarkingGeneral Classification	—Unverified
Improving Robustness and Reliability in Medical Image Classification with Latent-Guided Diffusion and Nested-Ensembles	Oct 24, 2023	Data Augmentationimage-classification	—Unverified
Improving Sample Complexity with Observational Supervision	Mar 25, 2019	image-classificationImage Classification	—Unverified
Active Globally Explainable Learning for Medical Images via Class Association Embedding and Cyclic Adversarial Generation	Jun 12, 2023	counterfactualExplainable Artificial Intelligence (XAI)	—Unverified
InceptionCapsule: Inception-Resnet and CapsuleNet with self-attention for medical image Classification	Feb 3, 2024	Classificationimage-classification	—Unverified
In-context learning enables multimodal large language models to classify cancer pathology images	Mar 12, 2024	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