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 301–310 of 424 papers

Title	Date	Tasks	Status
On evaluating CNN representations for low resource medical image classification	Mar 26, 2019	ClassificationGeneral Classification	—Unverified
Towards Privacy-Preserving Medical Imaging: Federated Learning with Differential Privacy and Secure Aggregation Using a Modified ResNet Architecture	Dec 1, 2024	Federated Learningimage-classification	—Unverified
Only My Model On My Data: A Privacy Preserving Approach Protecting one Model and Deceiving Unauthorized Black-Box Models	Feb 14, 2024	Adversarial AttackClassification	—Unverified
Assessing Robustness to Noise: Low-Cost Head CT Triage	Mar 17, 2020	Computed Tomography (CT)image-classification	—Unverified
OpenMedIA: Open-Source Medical Image Analysis Toolbox and Benchmark under Heterogeneous AI Computing Platforms	Aug 11, 2022	image-classificationImage Classification	—Unverified
Optimizing Federated Learning for Medical Image Classification on Distributed Non-iid Datasets with Partial Labels	Mar 10, 2023	Federated Learningimage-classification	—Unverified
Transfer Learning and Class Decomposition for Detecting the Cognitive Decline of Alzheimer Disease	Jan 31, 2023	Alzheimer's Detectionimage-classification	—Unverified
A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges	Nov 12, 2020	Decision MakingEnsemble Learning	—Unverified
ParseCaps: An Interpretable Parsing Capsule Network for Medical Image Diagnosis	Nov 3, 2024	image-classificationImage Classification	—Unverified
A review of deep learning-based information fusion techniques for multimodal medical image classification	Apr 23, 2024	image-classificationImage Classification	—Unverified

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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