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

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Showing 326–350 of 424 papers

TitleStatusHype
Robust Medical Image Classification from Noisy Labeled Data with Global and Local Representation Guided Co-training—0
Preservation of High Frequency Content for Deep Learning-Based Medical Image ClassificationCode0
Making the Most of Text Semantics to Improve Biomedical Vision--Language ProcessingCode0
Multi-Sample ζ-mixup: Richer, More Realistic Synthetic Samples from a p-Series Interpolant—0
CAIPI in Practice: Towards Explainable Interactive Medical Image Classification—0
Interpretable Saliency Maps And Self-Supervised Learning For Generalized Zero Shot Medical Image Classification—0
Mix-up Self-Supervised Learning for Contrast-agnostic Applications—0
A Two-Stage Federated Transfer Learning Framework in Medical Images Classification on Limited Data: A COVID-19 Case Study—0
Computer vision and machine learning for medical image analysis: recent advances, challenges, and way forward—0
Meta Ordinal Regression Forest for Medical Image Classification with Ordinal Labels—0
FairPrune: Achieving Fairness Through Pruning for Dermatological Disease Diagnosis—0
Improving the repeatability of deep learning models with Monte Carlo dropoutCode0
Mutual Attention-based Hybrid Dimensional Network for Multimodal Imaging Computer-aided Diagnosis—0
Detection of Dementia Through 3D Convolutional Neural Networks Based on Amyloid PETCode0
Weakly-supervised Generative Adversarial Networks for medical image classification—0
Medical Knowledge-Guided Deep Learning for Imbalanced Medical Image Classification—0
Deep AUC Maximization for Medical Image Classification: Challenges and Opportunities—0
FedSLD: Federated Learning with Shared Label Distribution for Medical Image Classification—0
Homogeneous Learning: Self-Attention Decentralized Deep LearningCode0
Does deep learning model calibration improve performance in class-imbalanced medical image classification?—0
Compositional Training for End-to-End Deep AUC Maximization—0
Classification of COVID-19 from CXR Images in a 15-class Scenario: an Attempt to Avoid Bias in the System—0
Splitfed learning without client-side synchronization: Analyzing client-side split network portion size to overall performance—0
Privacy-preserving Machine Learning for Medical Image Classification—0
How Transferable Are Self-supervised Features in Medical Image Classification Tasks?—0
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All datasetsNCT-CRC-HE-100KIDRiDImageNetPCOS ClassificationCheXphotoGalaxy10 DECalsISIC 2017ISIC 2020 Challenge DatasetMalaria DatasetOASIS 3

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Efficientnet-b0Accuracy (%)95.59—Unverified
2ResNeXt-50-32x4dAccuracy (%)95.46—Unverified
3RegNetY-3.2GFAccuracy (%)95.42—Unverified
4ResNet-50Accuracy (%)94.72—Unverified
5DenseNet-169Accuracy (%)94.41—Unverified
6Res2Net-50Accuracy (%)93.37—Unverified
7ResNet-18Accuracy (%)92.66—Unverified
#ModelMetricClaimedVerifiedStatus
1ResNet-152Accuracy (% )86.56—Unverified
2Beta-RankAccuracy81.88—Unverified
#ModelMetricClaimedVerifiedStatus
1DaViT-SGFLOPs8.8—Unverified
2DaViT-TGFLOPs4.5—Unverified
#ModelMetricClaimedVerifiedStatus
1InceptionV31:1 Accuracy90.2—Unverified
2EfficientNet B71:1 Accuracy88.9—Unverified
#ModelMetricClaimedVerifiedStatus
1PTRNMean AUC0.85—Unverified
#ModelMetricClaimedVerifiedStatus
1AstroformerTop-1 Accuracy (%)94.87—Unverified
#ModelMetricClaimedVerifiedStatus
1Beta-RankAccuracy72.44—Unverified
#ModelMetricClaimedVerifiedStatus
1EfficientNet EnsembleAUC0.95—Unverified
#ModelMetricClaimedVerifiedStatus
1SNAPSHOT ENSEMBLEF1 score99.37—Unverified
#ModelMetricClaimedVerifiedStatus
13D CNNAUC87—Unverified