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 71–80 of 424 papers

Title	Date	Tasks	Status	Hype
HarmoFL: Harmonizing Local and Global Drifts in Federated Learning on Heterogeneous Medical Images	Dec 20, 2021	Federated Learningimage-classification	CodeCode Available	1
UniMiSS: Universal Medical Self-Supervised Learning via Breaking Dimensionality Barrier	Dec 17, 2021	Image ClassificationMedical Image Analysis	CodeCode Available	1
Joint Learning of Localized Representations from Medical Images and Reports	Dec 6, 2021	Contrastive Learningimage-classification	CodeCode Available	1
ACPL: Anti-curriculum Pseudo-labelling for Semi-supervised Medical Image Classification	Nov 25, 2021	image-classificationImage Classification	CodeCode Available	1
Malaria Parasite Detection using Efficient Neural Ensembles	Oct 15, 2021	DiagnosticMedical Image Classification	CodeCode Available	1
ResNet strikes back: An improved training procedure in timm	Oct 1, 2021	ClassificationData Augmentation	CodeCode Available	1
Balanced-MixUp for Highly Imbalanced Medical Image Classification	Sep 20, 2021	Classificationimage-classification	CodeCode Available	1
Co-Correcting: Noise-tolerant Medical Image Classification via mutual Label Correction	Sep 11, 2021	ClassificationDeep Learning	CodeCode Available	1
Categorical Relation-Preserving Contrastive Knowledge Distillation for Medical Image Classification	Jul 7, 2021	Classificationimage-classification	CodeCode Available	1
Federated Semi-supervised Medical Image Classification via Inter-client Relation Matching	Jun 16, 2021	Federated Learningimage-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