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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 301–350 of 424 papers

TitleStatusHype
Imbalanced Classification in Medical Imaging via Regrouping—0
Image Projective Transformation Rectification with Synthetic Data for Smartphone-captured Chest X-ray Photos ClassificationCode0
CLINICAL: Targeted Active Learning for Imbalanced Medical Image Classification—0
Deeply Supervised Layer Selective Attention Network: Towards Label-Efficient Learning for Medical Image Classification—0
Data Augmentation using Feature Generation for Volumetric Medical Images—0
CEC-CNN: A Consecutive Expansion-Contraction Convolutional Network for Very Small Resolution Medical Image Classification—0
Moving from 2D to 3D: volumetric medical image classification for rectal cancer stagingCode0
Single-Stage Broad Multi-Instance Multi-Label Learning (BMIML) with Diverse Inter-Correlations and its application to medical image classification—0
Consistency-Based Semi-supervised Evidential Active Learning for Diagnostic Radiograph Classification—0
ProCo: Prototype-aware Contrastive Learning for Long-tailed Medical Image ClassificationCode0
OpenMedIA: Open-Source Medical Image Analysis Toolbox and Benchmark under Heterogeneous AI Computing Platforms—0
RadTex: Learning Efficient Radiograph Representations from Text Reports—0
A Novel Automated Classification and Segmentation for COVID-19 using 3D CT Scans—0
Automatic Acne Object Detection and Acne Severity Grading Using Smartphone Images and Artificial IntelligenceCode0
Texture features in medical image analysis: a survey—0
Information Gain Sampling for Active Learning in Medical Image Classification—0
Learning Discriminative Representation via Metric Learning for Imbalanced Medical Image Classification—0
PCCT: Progressive Class-Center Triplet Loss for Imbalanced Medical Image Classification—0
Unsupervised Domain Adaptation Using Feature Disentanglement And GCNs For Medical Image Classification—0
A novel adversarial learning strategy for medical image classification—0
Deep reinforced active learning for multi-class image classification—0
The Importance of Background Information for Out of Distribution Generalization—0
Video Capsule Endoscopy Classification using Focal Modulation Guided Convolutional Neural NetworkCode0
Deep learning pipeline for image classification on mobile phones—0
Contrastive Centroid Supervision Alleviates Domain Shift in Medical Image Classification—0
Robust Medical Image Classification from Noisy Labeled Data with Global and Local Representation Guided Co-training—0
Preservation of High Frequency Content for Deep Learning-Based Medical Image ClassificationCode0
Making the Most of Text Semantics to Improve Biomedical Vision--Language ProcessingCode0
Multi-Sample ζ-mixup: Richer, More Realistic Synthetic Samples from a p-Series Interpolant—0
CAIPI in Practice: Towards Explainable Interactive Medical Image Classification—0
Interpretable Saliency Maps And Self-Supervised Learning For Generalized Zero Shot Medical Image Classification—0
Mix-up Self-Supervised Learning for Contrast-agnostic Applications—0
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
FairPrune: Achieving Fairness Through Pruning for Dermatological Disease Diagnosis—0
Improving the repeatability of deep learning models with Monte Carlo dropoutCode0
Mutual Attention-based Hybrid Dimensional Network for Multimodal Imaging Computer-aided Diagnosis—0
Detection of Dementia Through 3D Convolutional Neural Networks Based on Amyloid PETCode0
Weakly-supervised Generative Adversarial Networks for medical image classification—0
Medical Knowledge-Guided Deep Learning for Imbalanced Medical Image Classification—0
Deep AUC Maximization for Medical Image Classification: Challenges and Opportunities—0
FedSLD: Federated Learning with Shared Label Distribution for Medical Image Classification—0
Homogeneous Learning: Self-Attention Decentralized Deep LearningCode0
Does deep learning model calibration improve performance in class-imbalanced medical image classification?—0
Compositional Training for End-to-End Deep AUC Maximization—0
Classification of COVID-19 from CXR Images in a 15-class Scenario: an Attempt to Avoid Bias in the System—0
Splitfed learning without client-side synchronization: Analyzing client-side split network portion size to overall performance—0
Privacy-preserving Machine Learning for Medical Image Classification—0
How Transferable Are Self-supervised Features in Medical Image Classification Tasks?—0
Show:102550
← PrevPage 7 of 9Next →
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