Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/3474
Title: Automatic cardiac ventricular boundary detection
Authors: Cheng, Jierong
Keywords: DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Medical electronics
Issue Date: 2007
Source: Cheng, J. (2012). Automatic cardiac ventricular boundary detection. Doctoral thesis, Nanyang Technological University, Singapore.
Abstract: 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.
URI: https://hdl.handle.net/10356/3474
DOI: 10.32657/10356/3474
Rights: Nanyang Technological University
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

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