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 151–160 of 424 papers

Title	Date	Tasks	Status
A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges	Nov 12, 2020	Decision MakingEnsemble Learning	—Unverified
Classification of Medical Images and Illustrations in the Biomedical Literature Using Synergic Deep Learning	Jun 28, 2017	General Classificationimage-classification	—Unverified
Classification of COVID-19 from CXR Images in a 15-class Scenario: an Attempt to Avoid Bias in the System	Sep 25, 2021	Decision Makingimage-classification	—Unverified
A review of deep learning-based information fusion techniques for multimodal medical image classification	Apr 23, 2024	image-classificationImage Classification	—Unverified
Adversarial Attacks and Defences for Skin Cancer Classification	Dec 13, 2022	Adversarial AttackAdversarial Defense	—Unverified
Class Attention to Regions of Lesion for Imbalanced Medical Image Recognition	Jul 19, 2023	image-classificationImage Classification	—Unverified
Chest X-rays Classification: A Multi-Label and Fine-Grained Problem	Jul 19, 2018	General Classificationimage-classification	—Unverified
Applications of Sequential Learning for Medical Image Classification	Sep 26, 2023	Classificationimage-classification	—Unverified
A ChatGPT Aided Explainable Framework for Zero-Shot Medical Image Diagnosis	Jul 5, 2023	Diagnosticimage-classification	—Unverified
Federated Distillation for Medical Image Classification: Towards Trustworthy Computer-Aided Diagnosis	Jul 2, 2024	ClassificationFederated Learning	—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