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	Hype
A Two-Stage Federated Transfer Learning Framework in Medical Images Classification on Limited Data: A COVID-19 Case Study	Mar 24, 2022	COVID-19 DiagnosisFederated Learning	—Unverified	0
Computer vision and machine learning for medical image analysis: recent advances, challenges, and way forward	Mar 21, 2022	image-classificationImage Classification	—Unverified	0
Meta Ordinal Regression Forest for Medical Image Classification with Ordinal Labels	Mar 15, 2022	Classificationfeature selection	—Unverified	0
Self Pre-training with Masked Autoencoders for Medical Image Classification and Segmentation	Mar 10, 2022	Brain Tumor Segmentationimage-classification	CodeCode Available	1
Deep Multimodal Guidance for Medical Image Classification	Mar 10, 2022	Brain Tumor ClassificationClassification	CodeCode Available	1
FairPrune: Achieving Fairness Through Pruning for Dermatological Disease Diagnosis	Mar 4, 2022	Fairnessimage-classification	—Unverified	0
Improving the repeatability of deep learning models with Monte Carlo dropout	Feb 15, 2022	AttributeBinary Classification	CodeCode Available	0
An Analysis on Ensemble Learning optimized Medical Image Classification with Deep Convolutional Neural Networks	Jan 27, 2022	ClassificationEnsemble Learning	CodeCode Available	1
Detection of Dementia Through 3D Convolutional Neural Networks Based on Amyloid PET	Jan 24, 2022	Medical Image Classification	CodeCode Available	0
Mutual Attention-based Hybrid Dimensional Network for Multimodal Imaging Computer-aided Diagnosis	Jan 24, 2022	Diagnosticimage-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