Automatic cardiac ventricular boundary detection

Echocardiography is a common diagnostic imaging modality for patients with heart diseases. One essential goal in the analysis of echocardiographic images is to identify the locations of the endocardial boundary. This is necessary in order to visualize the structure of the patient's heart, and...

全面介紹

Saved in:
書目詳細資料
主要作者: Cheng, Jierong
其他作者: Foo, Say Wei
格式: Theses and Dissertations
出版: 2008
主題:
在線閱讀:https://hdl.handle.net/10356/3474
標簽: 添加標簽
沒有標簽, 成為第一個標記此記錄!
機構: Nanyang Technological University
id sg-ntu-dr.10356-3474
record_format dspace
spelling sg-ntu-dr.10356-34742023-07-04T16:40:45Z Automatic cardiac ventricular boundary detection Cheng, Jierong Foo, Say Wei School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Medical electronics Echocardiography is a common diagnostic imaging modality for patients with heart diseases. One essential goal in the analysis of echocardiographic images is to identify the locations of the endocardial boundary. This is necessary in order to visualize the structure of the patient's heart, and to derive quantitative parameters from the images. However, manual identification of endocardial boundary is time-consuming, inconvenient, and dependant on the competence of the clinician. In this thesis, three new algorithms are developed for boundary detection in two dimensional (2D) echocardiographic images. For long-axis echocardiographic images, a pre-segmentation algorithm is developed to locate the left ventricular (LV) region without user intervention. The final segmentation to find the actual LV boundary in long-axis echocardiographic images is carried out using a Markovian level set method. A new external force for snakes is proposed as dynamic directional gradient vector flow (DDGVF) for LV boundary detection in short-axis echocardiographic images. The techniques developed in this thesis have the potential to be integrated into an accurate and automatic system that could be used in routine clinical practice. DOCTOR OF PHILOSOPHY (EEE) 2008-09-17T09:30:44Z 2008-09-17T09:30:44Z 2007 2007 Thesis Cheng, J. (2012). Automatic cardiac ventricular boundary detection. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/3474 10.32657/10356/3474 Nanyang Technological University application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
topic DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Medical electronics
spellingShingle DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Medical electronics
Cheng, Jierong
Automatic cardiac ventricular boundary detection
description Echocardiography is a common diagnostic imaging modality for patients with heart diseases. One essential goal in the analysis of echocardiographic images is to identify the locations of the endocardial boundary. This is necessary in order to visualize the structure of the patient's heart, and to derive quantitative parameters from the images. However, manual identification of endocardial boundary is time-consuming, inconvenient, and dependant on the competence of the clinician. In this thesis, three new algorithms are developed for boundary detection in two dimensional (2D) echocardiographic images. For long-axis echocardiographic images, a pre-segmentation algorithm is developed to locate the left ventricular (LV) region without user intervention. The final segmentation to find the actual LV boundary in long-axis echocardiographic images is carried out using a Markovian level set method. A new external force for snakes is proposed as dynamic directional gradient vector flow (DDGVF) for LV boundary detection in short-axis echocardiographic images. The techniques developed in this thesis have the potential to be integrated into an accurate and automatic system that could be used in routine clinical practice.
author2 Foo, Say Wei
author_facet Foo, Say Wei
Cheng, Jierong
format Theses and Dissertations
author Cheng, Jierong
author_sort Cheng, Jierong
title Automatic cardiac ventricular boundary detection
title_short Automatic cardiac ventricular boundary detection
title_full Automatic cardiac ventricular boundary detection
title_fullStr Automatic cardiac ventricular boundary detection
title_full_unstemmed Automatic cardiac ventricular boundary detection
title_sort automatic cardiac ventricular boundary detection
publishDate 2008
url https://hdl.handle.net/10356/3474
_version_ 1772828988469673984