Chenxi Huang
A hybrid active contour segmentation method for myocardial D-SPECT images
Huang, Chenxi; Shan, Xiaoying; Lan, Yisha; Liu, Lu; Cai, Haidong; Che, Wenliang; Hao, Yongtao; Cheng, Yongqiang; Peng, Yonghong
Authors
Xiaoying Shan
Yisha Lan
Lu Liu
Haidong Cai
Wenliang Che
Yongtao Hao
Yongqiang Cheng
Yonghong Peng
Abstract
Ischaemic heart disease has become one of the leading causes of mortality worldwide. Dynamic single-photon emission computed tomography (D-SPECT) is an advanced routine diagnostic tool commonly used to validate myocardial function in patients suffering from various heart diseases. Accurate automatic localization and segmentation of myocardial regions is helpful in creating a three-dimensional myocardial model and assisting clinicians to perform assessments of myocardial function. Thus, image segmentation is a key technology in preclinical cardiac studies. Intensity inhomogeneity is one of the common challenges in image segmentation and is caused by image artefacts and instrument inaccuracy. In this paper, a novel region-based active contour model that can segment the myocardial D-SPECT image accurately is presented. First, a local region-based fitting image is defined based on information related to the intensity. Second, a likelihood fitting image energy function is built in a local region around each point in a given vector-valued image. Next, the level set method is used to present a global energy function with respect to the neighbourhood centre. The proposed approach guarantees precision and computational efficiency by combining the region-scalable fitting energy (RSF) model and local image fitting energy (LIF) model, and it can solve the issue of high sensitivity to initialization for myocardial D-SPECT segmentation.
Citation
Huang, C., Shan, X., Lan, Y., Liu, L., Cai, H., Che, W., Hao, Y., Cheng, Y., & Peng, Y. (2018). A hybrid active contour segmentation method for myocardial D-SPECT images. IEEE Access, 6, 39334-39343. https://doi.org/10.1109/ACCESS.2018.2855060
Journal Article Type | Article |
---|---|
Acceptance Date | Jul 8, 2018 |
Online Publication Date | Jul 11, 2018 |
Publication Date | Jul 10, 2018 |
Deposit Date | Jul 20, 2018 |
Publicly Available Date | Jul 20, 2018 |
Journal | IEEE Access |
Electronic ISSN | 2169-3536 |
Publisher | Institute of Electrical and Electronics Engineers |
Peer Reviewed | Peer Reviewed |
Volume | 6 |
Pages | 39334-39343 |
DOI | https://doi.org/10.1109/ACCESS.2018.2855060 |
Keywords | General Engineering; General Materials Science; General Computer Science |
Public URL | https://hull-repository.worktribe.com/output/937873 |
Publisher URL | https://ieeexplore.ieee.org/document/8409947/ |
Contract Date | Jul 20, 2018 |
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