SOTAVerified

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

Showing 401424 of 424 papers

TitleStatusHype
Improving Sample Complexity with Observational Supervision0
Unsupervised Deep Transfer Feature Learning for Medical Image Classification0
Evolutionary Neural AutoML for Deep LearningCode1
Robust Learning at Noisy Labeled Medical Images: Applied to Skin Lesion Classification0
Semi-Supervised Deep Learning for Abnormality Classification in Retinal ImagesCode1
TOP-GAN: Label-Free Cancer Cell Classification Using Deep Learning with a Small Training Set0
Effective, Fast, and Memory-Efficient Compressed Multi-function Convolutional Neural Networks for More Accurate Medical Image Classification0
Attention Gated Networks: Learning to Leverage Salient Regions in Medical ImagesCode0
Robust training of recurrent neural networks to handle missing data for disease progression modeling0
Chest X-rays Classification: A Multi-Label and Fine-Grained Problem0
Capsule Networks against Medical Imaging Data ChallengesCode0
Deep Residual Network based Automatic Image Grading for Diabetic Macular EdemaCode0
Efficient Active Learning for Image Classification and Segmentation using a Sample Selection and Conditional Generative Adversarial Network0
Learning multiple non-mutually-exclusive tasks for improved classification of inherently ordered labels0
GAN-based Synthetic Medical Image Augmentation for increased CNN Performance in Liver Lesion Classification0
Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) for Medical Image SegmentationCode0
Synthetic Medical Images from Dual Generative Adversarial NetworksCode0
Modality-bridge Transfer Learning for Medical Image Classification0
Classification of Medical Images and Illustrations in the Biomedical Literature Using Synergic Deep Learning0
Densely Connected Convolutional NetworksCode1
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning0
Deep Residual Learning for Image RecognitionCode4
How much data is needed to train a medical image deep learning system to achieve necessary high accuracy?0
Medical Image Classification via SVM using LBP Features from Saliency-Based Folded Data0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Efficientnet-b0Accuracy (%)95.59Unverified
2ResNeXt-50-32x4dAccuracy (%)95.46Unverified
3RegNetY-3.2GFAccuracy (%)95.42Unverified
4ResNet-50Accuracy (%)94.72Unverified
5DenseNet-169Accuracy (%)94.41Unverified
6Res2Net-50Accuracy (%)93.37Unverified
7ResNet-18Accuracy (%)92.66Unverified
#ModelMetricClaimedVerifiedStatus
1ResNet-152Accuracy (% )86.56Unverified
2Beta-RankAccuracy81.88Unverified
#ModelMetricClaimedVerifiedStatus
1DaViT-SGFLOPs8.8Unverified
2DaViT-TGFLOPs4.5Unverified
#ModelMetricClaimedVerifiedStatus
1InceptionV31:1 Accuracy90.2Unverified
2EfficientNet B71:1 Accuracy88.9Unverified
#ModelMetricClaimedVerifiedStatus
1PTRNMean AUC0.85Unverified
#ModelMetricClaimedVerifiedStatus
1AstroformerTop-1 Accuracy (%)94.87Unverified
#ModelMetricClaimedVerifiedStatus
1Beta-RankAccuracy72.44Unverified
#ModelMetricClaimedVerifiedStatus
1EfficientNet EnsembleAUC0.95Unverified
#ModelMetricClaimedVerifiedStatus
1SNAPSHOT ENSEMBLEF1 score99.37Unverified
#ModelMetricClaimedVerifiedStatus
13D CNNAUC87Unverified