Medical Image Classification
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Benchmarks
NCT-CRC-HE-100K
IDRiD
ImageNet
PCOS Classification
COVIDGR
CheXphoto
Galaxy10 DECals
ISIC 2017
Malaria Dataset
OASIS 3
Most implemented
Deep Residual Learning for Image Recognition
Densely Connected Convolutional Networks
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
Res2Net: A New Multi-scale Backbone Architecture
ResNet strikes back: An improved training procedure in timm
RegNet: Self-Regulated Network for Image Classification
Papers
MVC-Bench: Benchmarking Calibration of Medical Vision-Language Models
Reliable evaluation of vision-language models (VLMs) and medical vision-language models (Medical-VLMs) requires calibrated confidence, particularly under realistic clinical conditions. However, existing efforts mainly fo…
Medical Image ClassificationLabel-Free Foundational Model Selection for Medical Image Classification under Distribution Shift via Pseudo Label Discrepancy
Foundation models are increasingly deployed for medical image analysis. However, under the inter-institutional distribution shift typical of deployment, their performance varies widely and cannot be known without target-…
Medical Image ClassificationHow Many Labels Are Enough? ALDA: Active Learning Deployment Advisor for Medical Image Classification
Active learning (AL) promises to reduce the cost of medical imaging projects by lowering the number of clinical labels required. However, practical deployment requires committing to a sampling strategy before the full an…
Medical Image ClassificationActive LearningRecurrent Contrastive Learning for Imbalanced Medical Image Classification
Medical image classification often suffers from class imbalance due to the inherent disparities in disease incidence. Existing approaches, such as class resampling and loss reweighting, mainly improve learning within the…
Medical Image ClassificationContrastive LearningWhat Makes Deep Learning Work for Traditional Chinese Medicine Tongue Diagnosis? A Comprehensive Ablation Study
Deep learning has shown promise for automated tongue diagnosis in traditional Chinese medicine (TCM), yet the design space remains underexplored. We conducted a systematic ablation study spanning 20+ model versions under…
Medical Image ClassificationScaFE: Data-Efficient Scar Classification with LLM-Generated Clinical Feature Programs
Classifying pathological scars from clinical photographs requires distinguishing keloids from hypertrophic scars despite limited expert-labeled data and substantial acquisition variation across hospitals. End-to-end imag…
Medical Image ClassificationFeature EngineeringClinical Knowledge