Robust seed detection for coronary arteries segmentation using thresholded   Frangi response

Sammer ZAI; Muhammad Ahsan ANSARI; Soon-young SONG; Young Shik MOON

Makale detayları

Robust seed detection for coronary arteries segmentation using thresholded Frangi response

Yazarlar:

Sammer ZAI | Muhammad Ahsan ANSARI | Soon-young SONG | Young Shik MOON

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Electrical Engineering and Computer Science 2017 Vol.25 Issue 4, pp.2749-2760

Belge Tipi:

Makale

Yayın Tarihi:

7/2017

Belge Dili:

Türkçe

Document ID (Org No.):

2000736075

Sıklık:

İki Aylık

eISSN:

1303-6203

pISSN:

1300-0632

Özet:

 

Automatic detection of initial seed points has become an   essential step towards delineating coronary arteries in coronary computed   tomography angiography (CCTA) images due to image inhomogeneity and other   factors. Most coronary segmentation algorithms require user interaction for   seed point selection, which may lead to erroneous segmentation. In this   study, we present an improved technique of seed detection for coronary   segmentation using a thresholded Frangi response. Before computing region of   interest (ROI), the proposed method first computes the Frangi response of   the complete CCTA volume, followed by thresholding with respect to quantile   and median values, and then the ROI selection procedure is applied. Further,   this procedure is joined with a feature that is built according to the   resemblance among consecutive orthogonal cross-sections. The proposed method   was evaluated on nine clinical datasets, and the proposed framework   automatically detected coronary seeds accurately and can be used for an   accurate delineation of coronary arteries. The obtained results were   compared qualitatively and quantitatively by a radiologist, and the proposed   method outperformed the previous method with an improvement of 45.9%.

Makale detayları

Robust seed detection for coronary arteries segmentation using thresholded Frangi response

Yazarlar: Sammer ZAI | Muhammad Ahsan ANSARI | Soon-young SONG | Young Shik MOON

Yayıncı: TUBITAK

Dergi: Turkish Journal of Electrical Engineering and Computer Science 2017 Vol.25 Issue 4, pp.2749-2760

Belge Tipi: Makale

Yayın Tarihi: 7/2017

Belge Dili: Türkçe

Document ID (Org No.): 2000736075

Sıklık: İki Aylık

eISSN: 1303-6203

pISSN: 1300-0632

Sayı

Yazarlar:

Sammer ZAI | Muhammad Ahsan ANSARI | Soon-young SONG | Young Shik MOON

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Electrical Engineering and Computer Science 2017 Vol.25 Issue 4, pp.2749-2760

Belge Tipi:

Makale

Yayın Tarihi:

7/2017

Belge Dili:

Türkçe

Document ID (Org No.):

2000736075

Sıklık:

İki Aylık

eISSN:

1303-6203

pISSN:

1300-0632