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 71–80 of 424 papers

Title	Date	Tasks	Status	Hype
An ensemble framework approach of hybrid Quantum convolutional neural networks for classification of breast cancer images	Sep 24, 2024	image-classificationImage Classification	—Unverified	0
Enhancing Image Classification in Small and Unbalanced Datasets through Synthetic Data Augmentation	Sep 16, 2024	Data AugmentationDiagnostic	—Unverified	0
Can language-guided unsupervised adaptation improve medical image classification using unpaired images and texts?	Sep 3, 2024	image-classificationImage Classification	CodeCode Available	0
A high-order focus interaction model and oral ulcer dataset for oral ulcer segmentation	Aug 29, 2024	Image SegmentationLesion Segmentation	CodeCode Available	1
Visual Prompt Engineering for Medical Vision Language Models in Radiology	Aug 28, 2024	Classificationimage-classification	—Unverified	0
Text-guided Foundation Model Adaptation for Long-Tailed Medical Image Classification	Aug 27, 2024	DiagnosticGPU	—Unverified	0
Uncertainties of Latent Representations in Computer Vision	Aug 26, 2024	image-classificationImage Classification	—Unverified	0
Cervical Cancer Detection Using Multi-Branch Deep Learning Model	Aug 20, 2024	ClassificationDeep Learning	—Unverified	0
Predictive uncertainty estimation in deep learning for lung carcinoma classification in digital pathology under real dataset shifts	Aug 15, 2024	Decision MakingDiagnostic	—Unverified	0
A Novel Momentum-Based Deep Learning Techniques for Medical Image Classification and Segmentation	Aug 11, 2024	Benchmarkingimage-classification	—Unverified	0

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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