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Proceedings Paper

Open-source software platform for medical image segmentation applications
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Paper Abstract

Segmenting 2D and 3D images is a crucial and challenging problem in medical image analysis. Although several image segmentation algorithms have been proposed for different applications, no universal method currently exists. Moreover, their use is usually limited when detection of complex and multiple adjacent objects of interest is needed. In addition, the continually increasing volumes of medical imaging scans require more efficient segmentation software design and highly usable applications. In this context, we present an extension of our previous segmentation framework which allows the combination of existing explicit deformable models in an efficient and transparent way, handling simultaneously different segmentation strategies and interacting with a graphic user interface (GUI). We present the object-oriented design and the general architecture which consist of two layers: the GUI at the top layer, and the processing core filters at the bottom layer. We apply the framework for segmenting different real-case medical image scenarios on public available datasets including bladder and prostate segmentation from 2D MRI, and heart segmentation in 3D CT. Our experiments on these concrete problems show that this framework facilitates complex and multi-object segmentation goals while providing a fast prototyping open-source segmentation tool.

Paper Details

Date Published: 17 November 2017
PDF: 16 pages
Proc. SPIE 10572, 13th International Conference on Medical Information Processing and Analysis, 105721J (17 November 2017); doi: 10.1117/12.2283487
Show Author Affiliations
R. Namías, CIFASIS, UNR-CONICET/UAM (France) (Argentina)
Consejo Nacional de Investigaciones Científicas y Técnicas (Argentina)
J. P. D'Amato, Instituto Pladema, Univ. Nacional del Centro (Argentina)
Consejo Nacional de Investigaciones Científicas y Técnicas (Argentina)
M. del Fresno, Instituto Pladema, Univ. Nacional del Centro (Argentina)
Comisión de Investigaciones Científicas de la Provincia de Buenos Aires (Argentina)


Published in SPIE Proceedings Vol. 10572:
13th International Conference on Medical Information Processing and Analysis
Eduardo Romero; Natasha Lepore; Jorge Brieva; Juan David García, Editor(s)

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