Abstract
Segmentation of coronary arteries in X-ray angiography is a fundamental tool to evaluate arterial diseases and choose proper coronary treatment. The accurate segmentation of coronary arteries has become an important topic for the registration of different modalities, which allows physicians rapid access to different medical imaging information from computed tomography (CT) scans or magnetic resonance imaging (MRI). In this paper, we propose an accurate fully automatic algorithm based on Graph-cuts for vessel centerline extraction, caliber estimation, and catheter detection. Vesselness, geodesic paths, and a new multiscale edgeness map are combined to customize the Graph-cuts approach to the segmentation of tubular structures, by means of a global optimization of the Graph-cuts energy function. Moreover, a novel supervised learning methodology that integrates local and contextual information is proposed for automatic catheter detection. We evaluate the method performance on three datasets coming from different imaging systems. The method performs as good as the expert observer with respect to centerline detection and caliber estimation. Moreover, the method discriminates between arteries and catheter with an accuracy of 96.5, sensitivity of 72, and precision of 97.4.
Original language | English |
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Article number | 6316192 |
Journal | IEEE Transactions on Information Technology in Biomedicine |
Volume | 16 |
Issue number | 6 |
Pages (from-to) | 1332-1340 |
Number of pages | 9 |
ISSN | 1089-7771 |
DOIs | |
Publication status | Published - 2012 |
Externally published | Yes |
Bibliographical note
Funding Information:Manuscript received January 12, 2012; revised May 26, 2012, August 2, 2012, and September 14, 2012; accepted September 16, 2012. Date of current version November 16, 2012. This work was supported in part by the Project La Marató de TV3 082131, Project TIN2009-14404-C02, and Project CONSOLIDER-INGENIO CSD 2007-00018. The work of C. Gatta was supported by a “Beatriude Pinos” grant and by a “Ramon y Cajal” contract. The work of A. Hernandez-Vela was supported by an Formación de Personal Uni-versitario fellowship from the Spanish government.
Keywords
- Angiography
- caliber
- catheter
- centerline (CL)
- Graph-cuts (GC)
- quantitative coronary angiography (QCA)
- segmentation
- X-Ray