Medical Image Retrieval
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Benchmarks
BreakHis
Most implemented
BreastScreening: On the Use of Multi-Modality in Medical Imaging Diagnosis
EndoMapper dataset of complete calibrated endoscopy procedures
Evaluating Pre-trained Convolutional Neural Networks and Foundation Models as Feature Extractors for Content-based Medical Image Retrieval
RadiomicsRetrieval: A Customizable Framework for Medical Image Retrieval Using Radiomics Features
Vision Foundation Models for Computed Tomography
Papers
Predicting the risk of colorectal anastomotic leak based on preoperative mapping of the blood supply of the bowel
Anastomotic leak remains one of the most serious complications following colorectal cancer surgery, substantially affecting patient outcomes, recovery trajectories, and healthcare costs. Despite advances in imaging techn…
Medical Image RetrievalDecision MakingMIRAGE: Retrieval and Generation of Multimodal Images and Texts for Medical Education
Access to diverse, well-annotated medical images with interactive learning tools is fundamental for training practitioners in medicine and related fields to improve their diagnostic skills and understanding of anatomical…
Medical Image RetrievalHMAR: Hierarchical Modality-Aware Expert and Dynamic Routing Medical Image Retrieval Architecture
Medical image retrieval (MIR) is a critical component of computer-aided diagnosis, yet existing systems suffer from three persistent limitations: uniform feature encoding that fails to account for the varying clinical im…
Medical Image RetrievalContrastive LearningComposed Vision-Language Retrieval for Skin Cancer Case Search via Joint Alignment of Global and Local Representations
Medical image retrieval aims to identify clinically relevant lesion cases to support diagnostic decision making, education, and quality control. In practice, retrieval queries often combine a reference lesion image with …
Medical Image RetrievalDecision MakingWristMIR: Coarse-to-Fine Region-Aware Retrieval of Pediatric Wrist Radiographs with Radiology Report-Driven Learning
Retrieving wrist radiographs with analogous fracture patterns is challenging because clinically important cues are subtle, highly localized and often obscured by overlapping anatomy or variable imaging views. Progress is…
Medical Image RetrievalComparative Analysis of Binarization Methods For Medical Image Hashing On Odir Dataset
In this study, we evaluated four binarization methods. Locality-Sensitive Hashing (LSH), Iterative Quantization (ITQ), Kernel-based Supervised Hashing (KSH), and Supervised Discrete Hashing (SDH) on the ODIR dataset usin…
Medical Image Retrieval