Standardized evaluation methodology and reference database for evaluating IVUS image segmentation

Balocco, Simone and Gatta, Carlo and Ciompi, Francesco and Wahle, Andreas and Radeva, Petia and Carlier, Stephane and Ünal, Gözde and Sanidas, Elias and Mauri, Josepa and Carillo, Xavier and Kovarnik, Tomas and Wang, Ching-Wei and Chen, Hsiang-Chou and Exarchos, Themis P. and Fotiadis, Dimitrios I. and Destrempes, François and Cloutier, Guy and Pujol, Oriol and Alberti, Marina and Mendizabal-Ruiz, E. Gerardo and Rivera, Mariano and Aksoy, Timur and Downe, Richard W. and Kakadiaris, Ioannis A. (2014) Standardized evaluation methodology and reference database for evaluating IVUS image segmentation. Computerized Medical Imaging and Graphics, 38 (2). pp. 70-90. ISSN 0895-6111 (Print) 1879-0771 (Online)

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Abstract

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.
Item Type: Article
Uncontrolled Keywords: IVUS (intravascular ultrasound), Evaluation framework, Algorithm comparison, Image segmentation
Subjects: R Medicine > R Medicine (General) > R858-859.7 Computer applications to medicine. Medical informatics
Divisions: Faculty of Engineering and Natural Sciences > Academic programs > Electronics
Faculty of Engineering and Natural Sciences
Depositing User: Gözde Ünal
Date Deposited: 21 Jan 2014 20:57
Last Modified: 01 Aug 2019 14:41
URI: https://research.sabanciuniv.edu/id/eprint/22844

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