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 126150 of 424 papers

TitleStatusHype
Contrastive-Based Deep Embeddings for Label Noise-Resilient Histopathology Image ClassificationCode0
PairAug: What Can Augmented Image-Text Pairs Do for Radiology?Code1
Non-negative Subspace Feature Representation for Few-shot Learning in Medical Imaging0
Boosting Few-Shot Learning with Disentangled Self-Supervised Learning and Meta-Learning for Medical Image Classification0
Improved EATFormer: A Vision Transformer for Medical Image Classification0
A Systematic Review of Generalization Research in Medical Image Classification0
Multiple Teachers-Meticulous Student: A Domain Adaptive Meta-Knowledge Distillation Model for Medical Image ClassificationCode0
ConDiSR: Contrastive Disentanglement and Style Regularization for Single Domain GeneralizationCode0
Iterative Online Image Synthesis via Diffusion Model for Imbalanced Classification0
In-context learning enables multimodal large language models to classify cancer pathology images0
Fine-grained Prompt Tuning: A Parameter and Memory Efficient Transfer Learning Method for High-resolution Medical Image ClassificationCode1
Dynamic Perturbation-Adaptive Adversarial Training on Medical Image Classification0
BSDA: Bayesian Random Semantic Data Augmentation for Medical Image ClassificationCode0
Debiased Noise Editing on Foundation Models for Fair Medical Image ClassificationCode0
MedMamba: Vision Mamba for Medical Image ClassificationCode4
Investigating the Robustness of Vision Transformers against Label Noise in Medical Image Classification0
Integrating kNN with Foundation Models for Adaptable and Privacy-Aware Image ClassificationCode0
Only My Model On My Data: A Privacy Preserving Approach Protecting one Model and Deceiving Unauthorized Black-Box Models0
Comparative Analysis of ImageNet Pre-Trained Deep Learning Models and DINOv2 in Medical Imaging ClassificationCode0
Exploring Low-Resource Medical Image Classification with Weakly Supervised Prompt Learning0
SynthVision - Harnessing Minimal Input for Maximal Output in Computer Vision Models using Synthetic Image data0
InceptionCapsule: Inception-Resnet and CapsuleNet with self-attention for medical image Classification0
A Single Graph Convolution Is All You Need: Efficient Grayscale Image ClassificationCode1
Exploring the Transferability of a Foundation Model for Fundus Images: Application to Hypertensive Retinopathy0
Medical Image Debiasing by Learning Adaptive Agreement from a Biased CouncilCode0
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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