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 391–400 of 424 papers

Title	Date	Tasks	Status	Hype
Visualization approach to assess the robustness of neural networks for medical image classification	Nov 19, 2019	General Classificationimage-classification	—Unverified	0
MixModule: Mixed CNN Kernel Module for Medical Image Segmentation	Oct 19, 2019	image-classificationImage Classification	—Unverified	0
Joint Acne Image Grading and Counting via Label Distribution Learning	Oct 1, 2019	Acne Severity GradingMedical Image Classification	CodeCode Available	0
Multi-Instance Multi-Scale CNN for Medical Image Classification	Jul 4, 2019	ClassificationGeneral Classification	—Unverified	0
Unsupervised Feature Learning with K-means and An Ensemble of Deep Convolutional Neural Networks for Medical Image Classification	Jun 7, 2019	ClusteringDeep Learning	—Unverified	0
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks	May 28, 2019	Action RecognitionDomain Generalization	CodeCode Available	3
Transfer Learning based Detection of Diabetic Retinopathy from Small Dataset	May 17, 2019	ClassificationDeep Learning	CodeCode Available	0
TRk-CNN: Transferable Ranking-CNN for image classification of glaucoma, glaucoma suspect, and normal eyes	May 16, 2019	ClassificationGeneral Classification	—Unverified	0
Res2Net: A New Multi-scale Backbone Architecture	Apr 2, 2019	Image ClassificationInstance Segmentation	CodeCode Available	1
On evaluating CNN representations for low resource medical image classification	Mar 26, 2019	ClassificationGeneral 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