BIRAM: A content-based image retrieval framework for medical images

Autor(es)

Moreno, Ramon A. ; Furuie, Sergio S. ; Horil, SC ; Ratib, OM

• Tipo de documento: Artigo Científico
• Fonte: MEDICAL IMAGING 2007: PACS AND IMAGING INFORMATICS; v. 6145, p. 8-pg., 2006-01-01.

Resumo

In the medical field, digital images are becoming more and more important for diagnostics and therapy of the patients. At the same time, the development of new technologies has increased the amount of image data produced in a hospital. This creates a demand for access methods that offer more than text-based queries for retrieval of the information. In this paper is proposed a framework for the retrieval of medical images that allows the use of different algorithms for the search of medical images by similarity. The framework also enables the search for textual information from an associated medical report and DICOM header information. The proposed system can be used for support of clinical decision making and is intended to be integrated with an open source picture, archiving and communication systems (PACS). The BIRAM has the following advantages: (i) Can receive several types of algorithms for image similarity search; (ii) Allows the codification of the report according to a medical dictionary, improving the indexing of the information and retrieval; (iii) The algorithms can be selectively applied to images with the appropriated characteristics, for instance, only in magnetic resonance images. The framework was implemented in Java language using a MS Access 97 database. The proposed framework can still be improved, by the use of regions of interest (ROI), indexing with slim-trees and integration with a PACS Server. (AU)

• Processo FAPESP: 01/05987-0 - Visualizador contextual de imagens médicas distribuídas aplicado a medicina nuclear
• Beneficiário: Ramon Alfredo Moreno
• Modalidade de apoio: Bolsas no Brasil - Doutorado Direto
• Processo FAPESP: 97/14206-5 - Ambiente distribuído para a transmissão, arquivamento, processamento e visualização de imagens médicas
• Beneficiário: Sergio Shiguemi Furuie
• Modalidade de apoio: Auxílio à Pesquisa - Temático