期刊
IEEE ACCESS
卷 6, 期 -, 页码 39334-39343出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2018.2855060
关键词
Myocardium D-SPECT; image segmentation; active contour; level set
资金
- National Science and Technology [2015BAF10B01]
- Natural Science Foundation of China [81670403, 81500381, 81201069]
The 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 the myocardial function in patients suffering from various heart diseases. Accurate automatic localization and segmentation of myocardial regions is helpful in creating a 3-D 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 artifacts 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 the 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 neighborhood center. The proposed approach guarantees precision and computational efficiency by combining the region-scalable fitting energy model and local image fitting energy model, and it can solve the issue of high sensitivity to initialization for myocardial D-SPECT segmentation.
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