A Radiology Image Retrieval System based on User Preferences

摘要

This article introduces a computer-aided solution for radiology education integrated with the clinic practice, inherited from modern technologies that facilitate the processing of large amounts of stored information. Radiology training may have several challenges such as image retrieval, extraction of knowledge, education towards solving problems and the interaction with huge repositories known as Picture Archiving and Communication Systems (PACS). This project proposes a user-based system that learns from user interaction, retrieving not just the requested information but recommending related cases and interesting images. The recommended images are retrieved using a Click-through rate (CTR) strategy for defining the most similar cases in the database. This is a fully web-based proposal, potentially useful at classroom or home, that allows students to develop the clinical skills needed in a more realistic scenario.