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 261–270 of 424 papers

Title	Date	Tasks	Status
Medical Image Classification Using Transfer Learning and Chaos Game Optimization on the Internet of Medical Things	Dec 12, 2023	feature selectionimage-classification	—Unverified
Medical Image Classification via SVM using LBP Features from Saliency-Based Folded Data	Sep 15, 2015	ClassificationGeneral Classification	—Unverified
CBVLM: Training-free Explainable Concept-based Large Vision Language Models for Medical Image Classification	Jan 21, 2025	Disease Predictionimage-classification	—Unverified
The GraphNet Zoo: An All-in-One Graph Based Deep Semi-Supervised Framework for Medical Image Classification	Mar 13, 2020	AllClassification	—Unverified
Medical Knowledge-Guided Deep Learning for Imbalanced Medical Image Classification	Nov 20, 2021	ClassificationDeep Learning	—Unverified
Causality-Driven One-Shot Learning for Prostate Cancer Grading from MRI	Sep 19, 2023	Decision Makingimage-classification	—Unverified
Medi-CAT: Contrastive Adversarial Training for Medical Image Classification	Oct 31, 2023	Contrastive Learningimage-classification	—Unverified
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
CAIPI in Practice: Towards Explainable Interactive Medical Image Classification	Apr 6, 2022	BIG-bench Machine LearningClassification	—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