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 201–250 of 424 papers

TitleStatusHype
Concept Bottleneck with Visual Concept Filtering for Explainable Medical Image Classification—0
CONFINE: Conformal Prediction for Interpretable Neural Networks—0
Consistency-Based Semi-supervised Evidential Active Learning for Diagnostic Radiograph Classification—0
Contrastive Centroid Supervision Alleviates Domain Shift in Medical Image Classification—0
Convolutional XGBoost (C-XGBOOST) Model for Brain Tumor Detection—0
CopilotCAD: Empowering Radiologists with Report Completion Models and Quantitative Evidence from Medical Image Foundation Models—0
CoRPA: Adversarial Image Generation for Chest X-rays Using Concept Vector Perturbations and Generative Models—0
Covid-19: Automatic detection from X-Ray images utilizing Transfer Learning with Convolutional Neural Networks—0
Cross-Modal Information Maximization for Medical Imaging: CMIM—0
Curriculum Fine-tuning of Vision Foundation Model for Medical Image Classification Under Label Noise—0
Data Augmentation using Feature Generation for Volumetric Medical Images—0
Deep AUC Maximization for Medical Image Classification: Challenges and Opportunities—0
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning—0
Deep Learning in Image Classification: Evaluating VGG19's Performance on Complex Visual Data—0
Deep Learning in Medical Image Classification from MRI-based Brain Tumor Images—0
Deep learning pipeline for image classification on mobile phones—0
Deeply Supervised Layer Selective Attention Network: Towards Label-Efficient Learning for Medical Image Classification—0
Deep reinforced active learning for multi-class image classification—0
Detecção da Psoríase Utilizando Visão Computacional: Uma Abordagem Comparativa Entre CNNs e Vision Transformers—0
Development of CNN Architectures using Transfer Learning Methods for Medical Image Classification—0
Diagnosis and Analysis of Celiac Disease and Environmental Enteropathy on Biopsy Images using Deep Learning Approaches—0
Diff3Dformer: Leveraging Slice Sequence Diffusion for Enhanced 3D CT Classification with Transformer Networks—0
Diffusion models applied to skin and oral cancer classification—0
DINO-CXR: A self supervised method based on vision transformer for chest X-ray classification—0
Distant Domain Transfer Learning for Medical Imaging—0
Distributed Federated Learning-Based Deep Learning Model for Privacy MRI Brain Tumor Detection—0
Distributionally Robust Optimization and Invariant Representation Learning for Addressing Subgroup Underrepresentation: Mechanisms and Limitations—0
Does deep learning model calibration improve performance in class-imbalanced medical image classification?—0
Dynamic Perturbation-Adaptive Adversarial Training on Medical Image Classification—0
Effective, Fast, and Memory-Efficient Compressed Multi-function Convolutional Neural Networks for More Accurate Medical Image Classification—0
Efficient Active Learning for Image Classification and Segmentation using a Sample Selection and Conditional Generative Adversarial Network—0
Efficient feature embedding of 3D brain MRI images for content-based image retrieval with deep metric learning—0
Efficient Few-Shot Medical Image Analysis via Hierarchical Contrastive Vision-Language Learning—0
EG-SpikeFormer: Eye-Gaze Guided Transformer on Spiking Neural Networks for Medical Image Analysis—0
Embedding Radiomics into Vision Transformers for Multimodal Medical Image Classification—0
Embeddings are all you need! Achieving High Performance Medical Image Classification through Training-Free Embedding Analysis—0
Embedding Task Knowledge into 3D Neural Networks via Self-supervised Learning—0
Enhancing Image Classification in Small and Unbalanced Datasets through Synthetic Data Augmentation—0
Enhancing Transfer Learning for Medical Image Classification with SMOTE: A Comparative Study—0
Keeping Representation Similarity in Finetuning for Medical Image Analysis—0
Label-noise-tolerant medical image classification via self-attention and self-supervised learning—0
Learning and Exploiting Interclass Visual Correlations for Medical Image Classification—0
Learning Discriminative Representation via Metric Learning for Imbalanced Medical Image Classification—0
Learning from Exemplary Explanations—0
Learning multiple non-mutually-exclusive tasks for improved classification of inherently ordered labels—0
MedFocusCLIP : Improving few shot classification in medical datasets using pixel wise attention—0
Medical Image Classification Using Transfer Learning and Chaos Game Optimization on the Internet of Medical Things—0
Medical Image Classification via SVM using LBP Features from Saliency-Based Folded Data—0
Medical Knowledge-Guided Deep Learning for Imbalanced Medical Image Classification—0
Medi-CAT: Contrastive Adversarial Training for 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