Medical Image Retrieval Using Multimodal Semantic Indexing

Large collections of medical images have become a valuable source of knowledge, taking an important role in education, medical research and clinical decision making. An important unsolved issue that is actively investigated is the efficient and effective access to these repositories. This work addresses the problem of information retrieval in large collections of biomedical images, allowing to use sample images as alternative queries to the classic keywords. The proposed approach takes advantage of both modalities: text and visual information. The main drawback of the multimodal strategies is that the associated algorithms are memory and computation intensive. So, an important challenge addressed in this work is the design of scalable strategies, that can be applied efficiently and effectively in large medical image collections. The experimental evaluation shows that the proposed multimodal strategies are useful to improve the image retrieval performance, and are fully applicable to large image repositories.

• Autores: Vanegas Ramírez, Jorge Andrés
• Fecha de publicación: 2013
• Institución: Universidad Nacional de Colombia
• Repositorio: Universidad Nacional de Colombia
• Idioma: spa
• OAI Identifier: oai:repositorio.unal.edu.co:unal/20025
• Acceso en línea: https://repositorio.unal.edu.co/handle/unal/20025; http://bdigital.unal.edu.co/10274/
• Palabra clave: 0 Generalidades / Computer science, information and general works; 61 Ciencias médicas; Medicina / Medicine and health; 62 Ingeniería y operaciones afines / Engineering; Computer vision; Information retrieval; Machine learning; Multimodal semantic indexing; Medical images
• Rights: openAccess
• License: Atribución-NoComercial 4.0 Internacional