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 251–260 of 424 papers

Title	Date	Tasks	Status
Med-IC: Fusing a Single Layer Involution with Convolutions for Enhanced Medical Image Classification and Segmentation	Sep 27, 2024	image-classificationImage Classification	—Unverified
MedKAN: An Advanced Kolmogorov-Arnold Network for Medical Image Classification	Feb 25, 2025	image-classificationImage Classification	—Unverified
MED-TEX: Transferring and Explaining Knowledge with Less Data from Pretrained Medical Imaging Models	Aug 6, 2020	image-classificationImage Classification	—Unverified
Meta Ordinal Regression Forest for Medical Image Classification with Ordinal Labels	Mar 15, 2022	Classificationfeature selection	—Unverified
Meta-Transfer Derm-Diagnosis: Exploring Few-Shot Learning and Transfer Learning for Skin Disease Classification in Long-Tail Distribution	Apr 25, 2024	Data AugmentationFew-Shot Learning	—Unverified
MIC: Medical Image Classification Using Chest X-ray (COVID-19 and Pneumonia) Dataset with the Help of CNN and Customized CNN	Nov 2, 2024	image-classificationImage Classification	—Unverified
MixModule: Mixed CNN Kernel Module for Medical Image Segmentation	Oct 19, 2019	image-classificationImage Classification	—Unverified
Mix-up Self-Supervised Learning for Contrast-agnostic Applications	Apr 2, 2022	image-classificationImage Classification	—Unverified
Modality-bridge Transfer Learning for Medical Image Classification	Aug 10, 2017	ClassificationGeneral Classification	—Unverified
More for Less: Compact Convolutional Transformers Enable Robust Medical Image Classification with Limited Data	Jul 1, 2023	Image Captioningimage-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