Maximum a posteriori estimation method for aorta localization and coronary seed identification

Byunghwan Jeon; Yoonmi Hong; Dongjin Han; Yeonggul Jang; Sunghee Jung; Youngtaek Hong; Seongmin Ha; Hackjoon Shim; Hyuk Jae Chang

doi:10.1016/j.patcog.2017.03.005

Maximum a posteriori estimation method for aorta localization and coronary seed identification

Byunghwan Jeon
, Yoonmi Hong
, Dongjin Han
, Yeonggul Jang
, Sunghee Jung
, Youngtaek Hong
, Seongmin Ha
, Hackjoon Shim
, Hyuk Jae Chang

Department of Biomedical Engineering

Research output: Contribution to journal › Article › peer-review

9 Scopus citations

Abstract

We propose a robust method for the automatic identification of seed points for the segmentation of coronary arteries from coronary computed tomography angiography (CCTA). The detection of the aorta and the two ostia for use as seed points is required for the automatic segmentation of coronary arteries. Our method is based on a Bayesian framework combining anatomical and geometrical features. We demonstrate the robustness and accuracy of our method by comparison with two conventional methods on 130 CT cases.

Original language	English
Pages (from-to)	222-232
Number of pages	11
Journal	Pattern Recognition
Volume	68
DOIs	https://doi.org/10.1016/j.patcog.2017.03.005
State	Published - 1 Aug 2017

Keywords

Aorta localization
Bayesian
Cardiac CT
Coronary seed
MAP
Pairwise

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10.1016/j.patcog.2017.03.005

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title = "Maximum a posteriori estimation method for aorta localization and coronary seed identification",

abstract = "We propose a robust method for the automatic identification of seed points for the segmentation of coronary arteries from coronary computed tomography angiography (CCTA). The detection of the aorta and the two ostia for use as seed points is required for the automatic segmentation of coronary arteries. Our method is based on a Bayesian framework combining anatomical and geometrical features. We demonstrate the robustness and accuracy of our method by comparison with two conventional methods on 130 CT cases.",

keywords = "Aorta localization, Bayesian, Cardiac CT, Coronary seed, MAP, Pairwise",

author = "Byunghwan Jeon and Yoonmi Hong and Dongjin Han and Yeonggul Jang and Sunghee Jung and Youngtaek Hong and Seongmin Ha and Hackjoon Shim and Chang, \{Hyuk Jae\}",

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doi = "10.1016/j.patcog.2017.03.005",

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TY - JOUR

T1 - Maximum a posteriori estimation method for aorta localization and coronary seed identification

AU - Jeon, Byunghwan

AU - Hong, Yoonmi

AU - Han, Dongjin

AU - Jang, Yeonggul

AU - Jung, Sunghee

AU - Hong, Youngtaek

AU - Ha, Seongmin

AU - Shim, Hackjoon

AU - Chang, Hyuk Jae

PY - 2017/8/1

Y1 - 2017/8/1

N2 - We propose a robust method for the automatic identification of seed points for the segmentation of coronary arteries from coronary computed tomography angiography (CCTA). The detection of the aorta and the two ostia for use as seed points is required for the automatic segmentation of coronary arteries. Our method is based on a Bayesian framework combining anatomical and geometrical features. We demonstrate the robustness and accuracy of our method by comparison with two conventional methods on 130 CT cases.

AB - We propose a robust method for the automatic identification of seed points for the segmentation of coronary arteries from coronary computed tomography angiography (CCTA). The detection of the aorta and the two ostia for use as seed points is required for the automatic segmentation of coronary arteries. Our method is based on a Bayesian framework combining anatomical and geometrical features. We demonstrate the robustness and accuracy of our method by comparison with two conventional methods on 130 CT cases.

KW - Aorta localization

KW - Bayesian

KW - Cardiac CT

KW - Coronary seed

KW - MAP

KW - Pairwise

UR - https://www.scopus.com/pages/publications/85017664010

U2 - 10.1016/j.patcog.2017.03.005

DO - 10.1016/j.patcog.2017.03.005

M3 - Article

AN - SCOPUS:85017664010

SN - 0031-3203

VL - 68

SP - 222

EP - 232

JO - Pattern Recognition

JF - Pattern Recognition

ER -

Maximum a posteriori estimation method for aorta localization and coronary seed identification

Abstract

Keywords

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