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 31–40 of 424 papers

Title	Date	Tasks	Status	Hype	Score
Evolutionary Neural AutoML for Deep Learning	Feb 18, 2019	AutoMLDeep Learning	CodeCode Available	1	5
Explainable Deep Learning Methods in Medical Image Classification: A Survey	May 10, 2022	Deep LearningExplainable artificial intelligence	CodeCode Available	1	5
Densely Connected Convolutional Networks	Aug 25, 2016	Breast Tumour ClassificationClassification	CodeCode Available	1	5
Balanced-MixUp for Highly Imbalanced Medical Image Classification	Sep 20, 2021	Classificationimage-classification	CodeCode Available	1	5
Systematic comparison of semi-supervised and self-supervised learning for medical image classification	Jul 18, 2023	GPUimage-classification	CodeCode Available	1	5
DiffMIC: Dual-Guidance Diffusion Network for Medical Image Classification	Mar 19, 2023	ClassificationDiabetic Retinopathy Grading	CodeCode Available	1	5
Deep Multimodal Guidance for Medical Image Classification	Mar 10, 2022	Brain Tumor ClassificationClassification	CodeCode Available	1	5
Astroformer: More Data Might not be all you need for Classification	Apr 3, 2023	AllAstronomy	CodeCode Available	1	5
Embedded Prompt Tuning: Towards Enhanced Calibration of Pretrained Models for Medical Images	Jul 1, 2024	Cross-Domain Few-Shotimage-classification	CodeCode Available	1	5
A Single Graph Convolution Is All You Need: Efficient Grayscale Image Classification	Feb 1, 2024	AllClassification	CodeCode Available	1	5

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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