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 251275 of 424 papers

TitleStatusHype
Med-IC: Fusing a Single Layer Involution with Convolutions for Enhanced Medical Image Classification and Segmentation0
MedKAN: An Advanced Kolmogorov-Arnold Network for Medical Image Classification0
MED-TEX: Transferring and Explaining Knowledge with Less Data from Pretrained Medical Imaging Models0
Meta Ordinal Regression Forest for Medical Image Classification with Ordinal Labels0
Meta-Transfer Derm-Diagnosis: Exploring Few-Shot Learning and Transfer Learning for Skin Disease Classification in Long-Tail Distribution0
MIC: Medical Image Classification Using Chest X-ray (COVID-19 and Pneumonia) Dataset with the Help of CNN and Customized CNN0
MixModule: Mixed CNN Kernel Module for Medical Image Segmentation0
Mix-up Self-Supervised Learning for Contrast-agnostic Applications0
Modality-bridge Transfer Learning for Medical Image Classification0
More for Less: Compact Convolutional Transformers Enable Robust Medical Image Classification with Limited Data0
MoVL:Exploring Fusion Strategies for the Domain-Adaptive Application of Pretrained Models in Medical Imaging Tasks0
Multi-branch CNN and grouping cascade attention for medical image classification0
Multiclass Alignment of Confidence and Certainty for Network Calibration0
Multi-Instance Learning by Utilizing Structural Relationship among Instances0
Multi-Instance Multi-Scale CNN for Medical Image Classification0
Multi-Sample ζ-mixup: Richer, More Realistic Synthetic Samples from a p-Series Interpolant0
Mutual Attention-based Hybrid Dimensional Network for Multimodal Imaging Computer-aided Diagnosis0
Non-negative Subspace Feature Representation for Few-shot Learning in Medical Imaging0
On evaluating CNN representations for low resource medical image classification0
Only My Model On My Data: A Privacy Preserving Approach Protecting one Model and Deceiving Unauthorized Black-Box Models0
OpenMedIA: Open-Source Medical Image Analysis Toolbox and Benchmark under Heterogeneous AI Computing Platforms0
Optimizing Federated Learning for Medical Image Classification on Distributed Non-iid Datasets with Partial Labels0
ParseCaps: An Interpretable Parsing Capsule Network for Medical Image Diagnosis0
PCCT: Progressive Class-Center Triplet Loss for Imbalanced Medical Image Classification0
Plug-and-Play Feature Generation for Few-Shot Medical Image Classification0
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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