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 151–160 of 424 papers

Title	Date	Tasks	Status
Enhancing Multimodal Medical Image Classification using Cross-Graph Modal Contrastive Learning	Oct 23, 2024	ClassificationContrastive Learning	CodeCode Available
Development of CNN Architectures using Transfer Learning Methods for Medical Image Classification	Oct 22, 2024	ClassificationDeep Learning	—Unverified
Domain-Adaptive Pre-training of Self-Supervised Foundation Models for Medical Image Classification in Gastrointestinal Endoscopy	Oct 21, 2024	Domain Adaptationimage-classification	CodeCode Available
Osteoporosis screening: Leveraging EfficientNet with complete and cropped facial panoramic radiography imaging	Oct 18, 2024	Medical Image Classification	CodeCode Available
EG-SpikeFormer: Eye-Gaze Guided Transformer on Spiking Neural Networks for Medical Image Analysis	Oct 12, 2024	Image ClassificationMedical Image Analysis	—Unverified
Explainability of Deep Neural Networks for Brain Tumor Detection	Oct 10, 2024	Data AugmentationDecision Making	CodeCode Available
Med-IC: Fusing a Single Layer Involution with Convolutions for Enhanced Medical Image Classification and Segmentation	Sep 27, 2024	image-classificationImage Classification	—Unverified
An ensemble framework approach of hybrid Quantum convolutional neural networks for classification of breast cancer images	Sep 24, 2024	image-classificationImage Classification	—Unverified
Enhancing Image Classification in Small and Unbalanced Datasets through Synthetic Data Augmentation	Sep 16, 2024	Data AugmentationDiagnostic	—Unverified
Can language-guided unsupervised adaptation improve medical image classification using unpaired images and texts?	Sep 3, 2024	image-classificationImage Classification	CodeCode Available

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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