Carregant...
Miniatura

Tipus de document

Article

Versió

Versió acceptada

Data de publicació

Tots els drets reservats

Si us plau utilitzeu sempre aquest identificador per citar o enllaçar aquest document: https://hdl.handle.net/2445/53334

Standardized evaluation methodology and reference database for evaluating IVUS image segmentation

Títol de la revista

Director/Tutor

ISSN de la revista

Títol del volum

Resum

This paper describes an evaluation framework that allows a standardized and quantitative comparison of IVUS lumen and media segmentation algorithms. This framework has been introduced at the MICCAI 2011 Computing and Visualization for (Intra)Vascular Imaging (CVII) workshop, comparing the results of eight teams that participated. We describe the available data-base comprising of multi-center, multi-vendor and multi-frequency IVUS datasets, their acquisition, the creation of the reference standard and the evaluation measures. The approaches address segmentation of the lumen, the media, or both borders; semi- or fully-automatic operation; and 2-D vs. 3-D methodology. Three performance measures for quantitative analysis have been proposed. The results of the evaluation indicate that segmentation of the vessel lumen and media is possible with an accuracy that is comparable to manual annotation when semi-automatic methods are used, as well as encouraging results can be obtained also in case of fully-automatic segmentation. The analysis performed in this paper also highlights the challenges in IVUS segmentation that remains to be solved.

Citació

Citació

BALOCCO, Simone, GATTA, Carlo, CIOMPI, Francesco, WAHLE, Andreas, RADEVA, Petia, CARLIER, Stéphane, ÜNAL, Gözde b., SANIDAS, Elias, MAURI, Josepa, CARRILLO, Xavier, KOVARNIK, Tomas, WANG, Ching-wei, CHEN, Hsiang-chou, EXARCHOS, Themis p., FOTIADIS, Dimitrios i., DESTREMPES, François, CLOUTIER, Guy, PUJOL VILA, Oriol, ALBERTI, Marina, MENDIZABAL-RUIZ, E. gerardo. Standardized evaluation methodology and reference database for evaluating IVUS image segmentation. _Computerized Medical Imaging and Graphics_. 2014. Vol. 38, núm. 2, pàgs. 70-90. [consulta: 25 de febrer de 2026]. ISSN: 0895-6111. [Disponible a: https://hdl.handle.net/2445/53334]

Exportar metadades

JSON - METS

Compartir registre