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 51–75 of 424 papers

TitleStatusHype
Addressing Small and Imbalanced Medical Image Datasets Using Generative Models: A Comparative Study of DDPM and PGGANs with Random and Greedy K SamplingCode0
Embeddings are all you need! Achieving High Performance Medical Image Classification through Training-Free Embedding Analysis—0
Higher Order Transformers: Efficient Attention Mechanism for Tensor Structured Data—0
Towards Privacy-Preserving Medical Imaging: Federated Learning with Differential Privacy and Secure Aggregation Using a Modified ResNet Architecture—0
Curriculum Fine-tuning of Vision Foundation Model for Medical Image Classification Under Label Noise—0
Embedding Byzantine Fault Tolerance into Federated Learning via Virtual Data-Driven Consistency Scoring PluginCode0
Judge Like a Real Doctor: Dual Teacher Sample Consistency Framework for Semi-supervised Medical Image Classification—0
ParseCaps: An Interpretable Parsing Capsule Network for Medical Image Diagnosis—0
MIC: Medical Image Classification Using Chest X-ray (COVID-19 and Pneumonia) Dataset with the Help of CNN and Customized CNN—0
Interpretable Bilingual Multimodal Large Language Model for Diverse Biomedical Tasks—0
Enhancing Multimodal Medical Image Classification using Cross-Graph Modal Contrastive LearningCode0
Development of CNN Architectures using Transfer Learning Methods for Medical Image Classification—0
Domain-Adaptive Pre-training of Self-Supervised Foundation Models for Medical Image Classification in Gastrointestinal EndoscopyCode0
Osteoporosis screening: Leveraging EfficientNet with complete and cropped facial panoramic radiography imagingCode0
EG-SpikeFormer: Eye-Gaze Guided Transformer on Spiking Neural Networks for Medical Image Analysis—0
Explainability of Deep Neural Networks for Brain Tumor DetectionCode0
FACMIC: Federated Adaptative CLIP Model for Medical Image ClassificationCode1
MONICA: Benchmarking on Long-tailed Medical Image ClassificationCode1
LoRKD: Low-Rank Knowledge Decomposition for Medical Foundation ModelsCode1
Med-IC: Fusing a Single Layer Involution with Convolutions for Enhanced Medical Image Classification and Segmentation—0
An ensemble framework approach of hybrid Quantum convolutional neural networks for classification of breast cancer images—0
Enhancing Image Classification in Small and Unbalanced Datasets through Synthetic Data Augmentation—0
Can language-guided unsupervised adaptation improve medical image classification using unpaired images and texts?Code0
A high-order focus interaction model and oral ulcer dataset for oral ulcer segmentationCode1
Visual Prompt Engineering for Medical Vision Language Models in Radiology—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