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	Hype
Brain Storm Optimization Based Swarm Learning for Diabetic Retinopathy Image Classification	Apr 24, 2024	Federated Learningimage-classification	—Unverified	0
A review of deep learning-based information fusion techniques for multimodal medical image classification	Apr 23, 2024	image-classificationImage Classification	—Unverified	0
Distributed Federated Learning-Based Deep Learning Model for Privacy MRI Brain Tumor Detection	Apr 15, 2024	DiagnosticFederated Learning	—Unverified	0
PM2: A New Prompting Multi-modal Model Paradigm for Few-shot Medical Image Classification	Apr 13, 2024	ClassificationFew-Shot Learning	—Unverified	0
CopilotCAD: Empowering Radiologists with Report Completion Models and Quantitative Evidence from Medical Image Foundation Models	Apr 11, 2024	Diagnosticimage-classification	—Unverified	0
Contrastive-Based Deep Embeddings for Label Noise-Resilient Histopathology Image Classification	Apr 11, 2024	Contrastive LearningDeep Learning	CodeCode Available	0
PairAug: What Can Augmented Image-Text Pairs Do for Radiology?	Apr 7, 2024	Data Augmentationimage-classification	CodeCode Available	1
Non-negative Subspace Feature Representation for Few-shot Learning in Medical Imaging	Apr 3, 2024	AttributeDimensionality Reduction	—Unverified	0
Boosting Few-Shot Learning with Disentangled Self-Supervised Learning and Meta-Learning for Medical Image Classification	Mar 26, 2024	Few-Shot Learningimage-classification	—Unverified	0
Improved EATFormer: A Vision Transformer for Medical Image Classification	Mar 19, 2024	Classificationimage-classification	—Unverified	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