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 41–50 of 424 papers

Title	Date	Tasks	Status	Hype	Score
CheXFusion: Effective Fusion of Multi-View Features using Transformers for Long-Tailed Chest X-Ray Classification	Aug 8, 2023	ClassificationDiagnostic	CodeCode Available	1	5
Categorical Relation-Preserving Contrastive Knowledge Distillation for Medical Image Classification	Jul 7, 2021	Classificationimage-classification	CodeCode Available	1	5
Achieving Fairness Through Channel Pruning for Dermatological Disease Diagnosis	May 14, 2024	Fairnessimage-classification	CodeCode Available	1	5
A Single Graph Convolution Is All You Need: Efficient Grayscale Image Classification	Feb 1, 2024	AllClassification	CodeCode Available	1	5
Federated Model Aggregation via Self-Supervised Priors for Highly Imbalanced Medical Image Classification	Jul 27, 2023	Federated Learningimage-classification	CodeCode Available	1	5
Astroformer: More Data Might not be all you need for Classification	Apr 3, 2023	AllAstronomy	CodeCode Available	1	5
A survey on attention mechanisms for medical applications: are we moving towards better algorithms?	Apr 26, 2022	image-classificationImage Classification	CodeCode Available	1	5
A high-order focus interaction model and oral ulcer dataset for oral ulcer segmentation	Aug 29, 2024	Image SegmentationLesion Segmentation	CodeCode Available	1	5
Boosting Memory Efficiency in Transfer Learning for High-Resolution Medical Image Classification	Aug 5, 2024	image-classificationImage Classification	CodeCode Available	1	5
Densely Connected Convolutional Networks	Aug 25, 2016	Breast Tumour ClassificationClassification	CodeCode Available	1	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