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 121–130 of 424 papers

Title	Date	Tasks	Status	Score
Attention Gated Networks: Learning to Leverage Salient Regions in Medical Images	Aug 22, 2018	Computational EfficiencyGeneral Classification	CodeCode Available	5
KPL: Training-Free Medical Knowledge Mining of Vision-Language Models	Jan 20, 2025	Classificationimage-classification	CodeCode Available	5
Connecting the Dots: Graph Neural Network Powered Ensemble and Classification of Medical Images	Nov 13, 2023	BenchmarkingClassification	CodeCode Available	5
Deep Residual Network based Automatic Image Grading for Diabetic Macular Edema	Jul 1, 2018	Fovea Detectionimage-classification	CodeCode Available	5
L3DMC: Lifelong Learning using Distillation via Mixed-Curvature Space	Jul 31, 2023	image-classificationImage Classification	CodeCode Available	5
ConDiSR: Contrastive Disentanglement and Style Regularization for Single Domain Generalization	Mar 14, 2024	ClassificationDisentanglement	CodeCode Available	5
Asymmetrical Reciprocity-based Federated Learning for Resolving Disparities in Medical Diagnosis	Dec 27, 2024	DiagnosticFederated Learning	CodeCode Available	5
Joint Acne Image Grading and Counting via Label Distribution Learning	Oct 1, 2019	Acne Severity GradingMedical Image Classification	CodeCode Available	5
On Fairness of Medical Image Classification with Multiple Sensitive Attributes via Learning Orthogonal Representations	Jan 4, 2023	Fairnessimage-classification	CodeCode Available	5
Comparative Analysis of ImageNet Pre-Trained Deep Learning Models and DINOv2 in Medical Imaging Classification	Feb 12, 2024	image-classificationImage Classification	CodeCode Available	5

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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