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 281–290 of 424 papers

Title	Date	Tasks	Status
The Whole Pathological Slide Classification via Weakly Supervised Learning	Jul 12, 2023	ClassificationContrastive Learning	—Unverified
MixModule: Mixed CNN Kernel Module for Medical Image Segmentation	Oct 19, 2019	image-classificationImage Classification	—Unverified
Mix-up Self-Supervised Learning for Contrast-agnostic Applications	Apr 2, 2022	image-classificationImage Classification	—Unverified
Modality-bridge Transfer Learning for Medical Image Classification	Aug 10, 2017	ClassificationGeneral Classification	—Unverified
Beyond Fine-tuning: Classifying High Resolution Mammograms using Function-Preserving Transformations	Jan 20, 2021	Cancer-no cancer per image classificationGPU	—Unverified
Benchmarking MedMNIST dataset on real quantum hardware	Feb 18, 2025	Benchmarkingimage-classification	—Unverified
More for Less: Compact Convolutional Transformers Enable Robust Medical Image Classification with Limited Data	Jul 1, 2023	Image Captioningimage-classification	—Unverified
TOP-GAN: Label-Free Cancer Cell Classification Using Deep Learning with a Small Training Set	Dec 17, 2018	General ClassificationGenerative Adversarial Network	—Unverified
MoVL:Exploring Fusion Strategies for the Domain-Adaptive Application of Pretrained Models in Medical Imaging Tasks	May 13, 2024	image-classificationImage Classification	—Unverified
Multi-branch CNN and grouping cascade attention for medical image classification	Jul 1, 2024	Classificationimage-classification	—Unverified

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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