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 51–60 of 424 papers

Title	Date	Tasks	Status	Hype
Astroformer: More Data Might not be all you need for Classification	Apr 3, 2023	AllAstronomy	CodeCode Available	1
DiffMIC: Dual-Guidance Diffusion Network for Medical Image Classification	Mar 19, 2023	ClassificationDiabetic Retinopathy Grading	CodeCode Available	1
Uncertainty-informed Mutual Learning for Joint Medical Image Classification and Segmentation	Mar 17, 2023	ClassificationDecoder	CodeCode Available	1
Pretrained ViTs Yield Versatile Representations For Medical Images	Mar 13, 2023	image-classificationImage Classification	CodeCode Available	1
Standardized Medical Image Classification across Medical Disciplines	Oct 20, 2022	Classificationimage-classification	CodeCode Available	1
Multiple Instance Learning via Iterative Self-Paced Supervised Contrastive Learning	Oct 17, 2022	Contrastive Learningimage-classification	CodeCode Available	1
Long-Tailed Classification of Thorax Diseases on Chest X-Ray: A New Benchmark Study	Aug 29, 2022	Classificationimage-classification	CodeCode Available	1
PatchDropout: Economizing Vision Transformers Using Patch Dropout	Aug 10, 2022	image-classificationImage Classification	CodeCode Available	1
Self-Ensembling Vision Transformer (SEViT) for Robust Medical Image Classification	Aug 4, 2022	image-classificationImage Classification	CodeCode Available	1
Regression Metric Loss: Learning a Semantic Representation Space for Medical Images	Jul 12, 2022	image-classificationImage Classification	CodeCode Available	1

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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