International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


Downloads: 109

Research Paper | Electronics & Communication Engineering | India | Volume 3 Issue 9, September 2014


Segmentation and Catheter Detection in Angiographic Images

R. Anu Prabha | M. Savitha [2] | M. Dinesh [3]


Abstract: Segmentation of coronary arteries in angiography images 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). An accurate fully automatic algorithm based on Graph-cuts for vessel centerline extraction, caliber estimation, and catheter detection is proposed. 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. A novel supervised learning methodology that integrates local and contextual information is proposed for automatic catheter detection.


Keywords: Coronary artery, Computed Tomography, Graph cut algorithm, Adaboost classifier, Catheter detection


Edition: Volume 3 Issue 9, September 2014,


Pages: 2050 - 2055


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How to Cite this Article?

R. Anu Prabha, M. Savitha, M. Dinesh, "Segmentation and Catheter Detection in Angiographic Images", International Journal of Science and Research (IJSR), Volume 3 Issue 9, September 2014, pp. 2050-2055, https://www.ijsr.net/get_abstract.php?paper_id=SEP14559

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