caa a22 4500 463178653 CHVBK 20180406164832.0 cr unu---uuuuu 170326e20071101xx s 000 0 eng 10.1007/s10278-007-9059-y doi (NATIONALLICENCE)springer-10.1007/s10278-007-9059-y BRISC—An Open Source Pulmonary Nodule Image Retrieval Framework [Elektronische Daten] [Michael Lam, Tim Disney, Daniela Raicu, Jacob Furst, David Channin] We have created a content-based image retrieval framework for computed tomography images of pulmonary nodules. When presented with a nodule image, the system retrieves images of similar nodules from a collection prepared by the Lung Image Database Consortium (LIDC). The system (1) extracts images of individual nodules from the LIDC collection based on LIDC expert annotations, (2) stores the extracted data in a flat XML database, (3) calculates a set of quantitative descriptors for each nodule that provide a high-level characterization of its texture, and (4) uses various measures to determine the similarity of two nodules and perform queries on a selected query nodule. Using our framework, we compared three feature extraction methods: Haralick co-occurrence, Gabor filters, and Markov random fields. Gabor and Markov descriptors perform better at retrieving similar nodules than do Haralick co-occurrence techniques, with best retrieval precisions in excess of 88%. Because the software we have developed and the reference images are both open source and publicly available they may be incorporated into both commercial and academic imaging workstations and extended by others in their research. Society for Imaging Informatics in Medicine, 2007 Content-based image retrieval nationallicence open source nationallicence lung nationallicence computer-aided diagnosis (CAD) nationallicence extensible markup language (XML) nationallicence image database nationallicence software design nationallicence computed tomography nationallicence texture feature nationallicence nodule nationallicence Lam Michael James Madison University, 20002 Wooded View Lane, 22827, Elkton, VA, USA aut Disney Tim Seattle Pacific University, Seattle, WA, USA aut Raicu Daniela CTI, Loop Campus, DePaul University, Office 471, 243 S. Wabash Ave, 60604, Chicago, IL, USA aut Furst Jacob CTI, Loop Campus, DePaul University, Office 471, 243 S. Wabash Ave, 60604, Chicago, IL, USA aut Channin David Department of Radiology, Northwestern University Medical School, 448 East Ontario Street Ste 300, 60611, Chicago, IL, USA aut Journal of Digital Imaging Springer-Verlag 20(2007-11-01), 63-71 0897-1889 20<63 2007 20 10278 https://doi.org/10.1007/s10278-007-9059-y text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s10278-007-9059-y text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Lam Michael James Madison University, 20002 Wooded View Lane, 22827, Elkton, VA, USA aut NATIONALLICENCE 700 1- Disney Tim Seattle Pacific University, Seattle, WA, USA aut NATIONALLICENCE 700 1- Raicu Daniela CTI, Loop Campus, DePaul University, Office 471, 243 S. Wabash Ave, 60604, Chicago, IL, USA aut NATIONALLICENCE 700 1- Furst Jacob CTI, Loop Campus, DePaul University, Office 471, 243 S. Wabash Ave, 60604, Chicago, IL, USA aut NATIONALLICENCE 700 1- Channin David Department of Radiology, Northwestern University Medical School, 448 East Ontario Street Ste 300, 60611, Chicago, IL, USA aut NATIONALLICENCE 773 0- Journal of Digital Imaging Springer-Verlag 20(2007-11-01), 63-71 0897-1889 20<63 2007 20 10278 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer