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 1–50 of 424 papers

TitleStatusHype
FedGSCA: Medical Federated Learning with Global Sample Selector and Client Adaptive Adjuster under Label Noise—0
Robust Training with Data Augmentation for Medical Imaging Classification—0
Finding Optimal Kernel Size and Dimension in Convolutional Neural Networks An Architecture Optimization Approach—0
Detecção da Psoríase Utilizando Visão Computacional: Uma Abordagem Comparativa Entre CNNs e Vision Transformers—0
Recent Advances in Medical Image Classification—0
Deep Modeling and Optimization of Medical Image ClassificationCode0
Advancements in Medical Image Classification through Fine-Tuning Natural Domain Foundation ModelsCode0
Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior—0
EVM-Fusion: An Explainable Vision Mamba Architecture with Neural Algorithmic Fusion—0
Learning Concept-Driven Logical Rules for Interpretable and Generalizable Medical Image ClassificationCode1
Expert-Like Reparameterization of Heterogeneous Pyramid Receptive Fields in Efficient CNNs for Fair Medical Image Classification—0
Improving Generalizability of Kolmogorov-Arnold Networks via Error-Correcting Output CodesCode0
Adapting a Segmentation Foundation Model for Medical Image Classification—0
V-EfficientNets: Vector-Valued Efficiently Scaled Convolutional Neural Network ModelsCode0
CLOG-CD: Curriculum Learning based on Oscillating Granularity of Class Decomposed Medical Image Classification—0
A Deep Bayesian Convolutional Spiking Neural Network-based CAD system with Uncertainty Quantification for Medical Images Classification—0
CheXWorld: Exploring Image World Modeling for Radiograph Representation LearningCode1
Embedding Radiomics into Vision Transformers for Multimodal Medical Image Classification—0
A Hybrid Fully Convolutional CNN-Transformer Model for Inherently Interpretable Medical Image Classification—0
Secure Diagnostics: Adversarial Robustness Meets Clinical Interpretability—0
Federated Learning for Medical Image Classification: A Comprehensive Benchmark—0
Diffusion models applied to skin and oral cancer classification—0
Fair Federated Medical Image Classification Against Quality Shift via Inter-Client Progressive State MatchingCode1
Keeping Representation Similarity in Finetuning for Medical Image Analysis—0
XFMamba: Cross-Fusion Mamba for Multi-View Medical Image ClassificationCode1
AI-Augmented Thyroid Scintigraphy for Robust Classification—0
MedKAN: An Advanced Kolmogorov-Arnold Network for Medical Image Classification—0
Can Score-Based Generative Modeling Effectively Handle Medical Image Classification?Code0
Medical Image Classification with KAN-Integrated Transformers and Dilated Neighborhood AttentionCode2
Benchmarking MedMNIST dataset on real quantum hardware—0
Hierarchical Vision Transformer with Prototypes for Interpretable Medical Image Classification—0
Hybrid Deep Learning Framework for Classification of Kidney CT Images: Diagnosis of Stones, Cysts, and Tumors—0
Long-tailed Medical Diagnosis with Relation-aware Representation Learning and Iterative Classifier CalibrationCode0
CoRPA: Adversarial Image Generation for Chest X-rays Using Concept Vector Perturbations and Generative Models—0
ViT-2SPN: Vision Transformer-based Dual-Stream Self-Supervised Pretraining Networks for Retinal OCT ClassificationCode0
Generating customized prompts for Zero-Shot Rare Event Medical Image Classification using LLMCode0
Rethinking Foundation Models for Medical Image Classification through a Benchmark Study on MedMNIST—0
Estimating the Conformal Prediction Threshold from Noisy LabelsCode0
CBVLM: Training-free Explainable Concept-based Large Vision Language Models for Medical Image Classification—0
KPL: Training-Free Medical Knowledge Mining of Vision-Language ModelsCode0
Efficient Few-Shot Medical Image Analysis via Hierarchical Contrastive Vision-Language Learning—0
MIAFEx: An Attention-based Feature Extraction Method for Medical Image ClassificationCode0
MedFocusCLIP : Improving few shot classification in medical datasets using pixel wise attention—0
Leveraging AI for Automatic Classification of PCOS Using Ultrasound ImagingCode0
Deep Learning in Image Classification: Evaluating VGG19's Performance on Complex Visual Data—0
On dataset transferability in medical image classificationCode0
Enhancing Transfer Learning for Medical Image Classification with SMOTE: A Comparative Study—0
Asymmetrical Reciprocity-based Federated Learning for Resolving Disparities in Medical DiagnosisCode0
FairREAD: Re-fusing Demographic Attributes after Disentanglement for Fair Medical Image Classification—0
Towards Interpretable Radiology Report Generation via Concept Bottlenecks using a Multi-Agentic RAGCode1
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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