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 231–240 of 424 papers

Title	Date	Tasks	Status	Hype
A Test Statistic Estimation-based Approach for Establishing Self-interpretable CNN-based Binary Classifiers	Mar 13, 2023	Binary ClassificationDecoder	—Unverified	0
Optimizing Federated Learning for Medical Image Classification on Distributed Non-iid Datasets with Partial Labels	Mar 10, 2023	Federated Learningimage-classification	—Unverified	0
AnoMalNet: Outlier Detection based Malaria Cell Image Classification Method Leveraging Deep Autoencoder	Mar 10, 2023	image-classificationImage Classification	—Unverified	0
Pyramid Pixel Context Adaption Network for Medical Image Classification with Supervised Contrastive Learning	Mar 3, 2023	Contrastive LearningDecision Making	—Unverified	0
Spatio-Temporal Structure Consistency for Semi-supervised Medical Image Classification	Mar 3, 2023	image-classificationImage Classification	—Unverified	0
Cluster-Guided Semi-Supervised Domain Adaptation for Imbalanced Medical Image Classification	Mar 2, 2023	ClusteringDomain Adaptation	—Unverified	0
MedViT: A Robust Vision Transformer for Generalized Medical Image Classification	Feb 19, 2023	image-classificationImage Classification	CodeCode Available	2
A Comprehensive Study of Modern Architectures and Regularization Approaches on CheXpert5000	Feb 13, 2023	image-classificationImage Classification	—Unverified	0
CECT: Controllable Ensemble CNN and Transformer for COVID-19 Image Classification	Feb 5, 2023	ClassificationCOVID-19 Diagnosis	CodeCode Available	0
Private, fair and accurate: Training large-scale, privacy-preserving AI models in medical imaging	Feb 3, 2023	Computed Tomography (CT)Diagnostic	CodeCode Available	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