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 301–350 of 424 papers

TitleStatusHype
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
Self Pre-training with Masked Autoencoders for Medical Image Classification and SegmentationCode1
Deep Multimodal Guidance for Medical Image ClassificationCode1
FairPrune: Achieving Fairness Through Pruning for Dermatological Disease Diagnosis—0
Improving the repeatability of deep learning models with Monte Carlo dropoutCode0
An Analysis on Ensemble Learning optimized Medical Image Classification with Deep Convolutional Neural NetworksCode1
Detection of Dementia Through 3D Convolutional Neural Networks Based on Amyloid PETCode0
Mutual Attention-based Hybrid Dimensional Network for Multimodal Imaging Computer-aided Diagnosis—0
HarmoFL: Harmonizing Local and Global Drifts in Federated Learning on Heterogeneous Medical ImagesCode1
UniMiSS: Universal Medical Self-Supervised Learning via Breaking Dimensionality BarrierCode1
Joint Learning of Localized Representations from Medical Images and ReportsCode1
Weakly-supervised Generative Adversarial Networks for medical image classification—0
ACPL: Anti-curriculum Pseudo-labelling for Semi-supervised Medical Image ClassificationCode1
Medical Knowledge-Guided Deep Learning for Imbalanced Medical Image Classification—0
Deep AUC Maximization for Medical Image Classification: Challenges and Opportunities—0
Malaria Parasite Detection using Efficient Neural EnsemblesCode1
FedSLD: Federated Learning with Shared Label Distribution for Medical Image Classification—0
Homogeneous Learning: Self-Attention Decentralized Deep LearningCode0
ResNet strikes back: An improved training procedure in timmCode1
Compositional Training for End-to-End Deep AUC Maximization—0
Does deep learning model calibration improve performance in class-imbalanced medical image classification?—0
Classification of COVID-19 from CXR Images in a 15-class Scenario: an Attempt to Avoid Bias in the System—0
Balanced-MixUp for Highly Imbalanced Medical Image ClassificationCode1
Splitfed learning without client-side synchronization: Analyzing client-side split network portion size to overall performance—0
Co-Correcting: Noise-tolerant Medical Image Classification via mutual Label CorrectionCode1
Privacy-preserving Machine Learning for Medical Image Classification—0
How Transferable Are Self-supervised Features in Medical Image Classification Tasks?—0
Semi-supervised learning for medical image classification using imbalanced training data—0
Simple black-box universal adversarial attacks on medical image classification based on deep neural networks—0
Statistical Dependency Guided Contrastive Learning for Multiple Labeling in Prenatal Ultrasound—0
Reconstructing Images of Two Adjacent Objects through Scattering Medium Using Generative Adversarial Network—0
CHEF: A Cheap and Fast Pipeline for Iteratively Cleaning Label Uncertainties (Technical Report)Code0
Cats, not CAT scans: a study of dataset similarity in transfer learning for 2D medical image classificationCode0
Categorical Relation-Preserving Contrastive Knowledge Distillation for Medical Image ClassificationCode1
Bayesian Statistics Guided Label Refurbishment Mechanism: Mitigating Label Noise in Medical Image ClassificationCode0
Federated Semi-supervised Medical Image Classification via Inter-client Relation MatchingCode1
Rethinking Transfer Learning for Medical Image ClassificationCode1
Mixture Outlier Exposure: Towards Out-of-Distribution Detection in Fine-grained EnvironmentsCode1
Meta-Learning with Fewer Tasks through Task InterpolationCode1
A systematic review of transfer learning based approaches for diabetic retinopathy detection—0
Privacy-Preserving Constrained Domain Generalization via Gradient Alignment—0
SKID: Self-Supervised Learning for Knee Injury Diagnosis from MRI DataCode0
MedSelect: Selective Labeling for Medical Image Classification Combining Meta-Learning with Deep Reinforcement LearningCode1
Transfer learning for automatic brain tumor classification Using MRI Images.—0
Variational Knowledge Distillation for Disease Classification in Chest X-Rays—0
TransMed: Transformers Advance Multi-modal Medical Image Classification—0
Improving Medical Image Classification with Label Noise Using Dual-uncertainty Estimation—0
Highly Efficient Representation and Active Learning Framework and Its Application to Imbalanced Medical Image Classification—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