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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


Chenxi Huang

Xiaoying Shan

Yisha Lan

Lu Liu

Haidong Cai

Wenliang Che

Yongtao Hao

Yongqiang Cheng

Yonghong Peng


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.


Huang, C., Shan, X., Lan, Y., Liu, L., Cai, H., Che, W., …Peng, Y. (2018). A hybrid active contour segmentation method for myocardial D-SPECT images. IEEE Access, 6, 39334-39343.

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
Keywords General Engineering; General Materials Science; General Computer Science
Public URL
Publisher URL


Article (682 Kb)

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