Level Set Based Hippocampus Segmentation in MR Images with Improved Initialization Using Region Growing
Joint Authors
Li, Bailin
Zhou, Zhaozhong
Ding, Xiaokang
Deng, Xiaolei
Zou, Ling
Jiang, Xiaoliang
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-01-15
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
The hippocampus has been known as one of the most important structures referred to as Alzheimer’s disease and other neurological disorders.
However, segmentation of the hippocampus from MR images is still a challenging task due to its small size, complex shape, low contrast, and discontinuous boundaries.
For the accurate and efficient detection of the hippocampus, a new image segmentation method based on adaptive region growing and level set algorithm is proposed.
Firstly, adaptive region growing and morphological operations are performed in the target regions and its output is used for the initial contour of level set evolution method.
Then, an improved edge-based level set method utilizing global Gaussian distributions with different means and variances is developed to implement the accurate segmentation.
Finally, gradient descent method is adopted to get the minimization of the energy equation.
As proved by experiment results, the proposed method can ideally extract the contours of the hippocampus that are very close to manual segmentation drawn by specialists.
American Psychological Association (APA)
Jiang, Xiaoliang& Zhou, Zhaozhong& Ding, Xiaokang& Deng, Xiaolei& Zou, Ling& Li, Bailin. 2017. Level Set Based Hippocampus Segmentation in MR Images with Improved Initialization Using Region Growing. Computational and Mathematical Methods in Medicine،Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1142173
Modern Language Association (MLA)
Jiang, Xiaoliang…[et al.]. Level Set Based Hippocampus Segmentation in MR Images with Improved Initialization Using Region Growing. Computational and Mathematical Methods in Medicine No. 2017 (2017), pp.1-11.
https://search.emarefa.net/detail/BIM-1142173
American Medical Association (AMA)
Jiang, Xiaoliang& Zhou, Zhaozhong& Ding, Xiaokang& Deng, Xiaolei& Zou, Ling& Li, Bailin. Level Set Based Hippocampus Segmentation in MR Images with Improved Initialization Using Region Growing. Computational and Mathematical Methods in Medicine. 2017. Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1142173
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1142173