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 61–70 of 424 papers

Title	Date	Tasks	Status	Hype
Deep Multimodal Guidance for Medical Image Classification	Mar 10, 2022	Brain Tumor ClassificationClassification	CodeCode Available	1
MONICA: Benchmarking on Long-tailed Medical Image Classification	Oct 2, 2024	BenchmarkingClassification	CodeCode Available	1
CheXFusion: Effective Fusion of Multi-View Features using Transformers for Long-Tailed Chest X-Ray Classification	Aug 8, 2023	ClassificationDiagnostic	CodeCode Available	1
Counterfactual Explanations for Medical Image Classification and Regression using Diffusion Autoencoder	Aug 2, 2024	counterfactualimage-classification	CodeCode Available	1
Co-Correcting: Noise-tolerant Medical Image Classification via mutual Label Correction	Sep 11, 2021	ClassificationDeep Learning	CodeCode Available	1
Evaluating histopathology transfer learning with ChampKit	Jun 14, 2022	BenchmarkingCell Detection	CodeCode Available	1
Densely Connected Convolutional Networks	Aug 25, 2016	Breast Tumour ClassificationClassification	CodeCode Available	1
CASS: Cross Architectural Self-Supervision for Medical Image Analysis	Jun 8, 2022	ClassificationMedical Image Analysis	CodeCode Available	1
Federated Model Aggregation via Self-Supervised Priors for Highly Imbalanced Medical Image Classification	Jul 27, 2023	Federated Learningimage-classification	CodeCode Available	1
How Does Pruning Impact Long-Tailed Multi-Label Medical Image Classifiers?	Aug 17, 2023	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