Segmentation of Cerebrovascular Anatomy from TOF-MRA Using Length-Strained Enhancement and Random Walker.
Cerebrovascular rupture can cause a severe stroke. Three-dimensional time-of-flight (TOF) magnetic resonance angiography (MRA) is a common method of obtaining vascular information. This work proposes a fully automated segmentation method for extracting the vascular anatomy from TOF-MRA. The steps of...
| Published in: | BioMed Research International pp. 1 - 17 |
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| Main Authors: | , , , , , , |
| Format: | diagnostic images equations & formulas research tables/charts Journal Article |
| Published: |
Wiley-Blackwell
9/22/2020
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=146010999&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 146010999 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 9/22/2020 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 146010999 146010999 146010999 10.1155/2020/9347215 146010999 ppf: 1 ppct: 16 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Segmentation of Cerebrovascular Anatomy from TOF-MRA Using Length-Strained Enhancement and Random Walker. aug: au: Xiao, Ruoxiu Chen, Cheng Zou, Hanying Luo, Ying Wang, Jiayu Zha, Muxi Yu, Ming-An affil: School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China sug: subj: Cerebrovascular Disorders Diagnosis Cerebral Veins Anatomy and Histology Magnetic Resonance Angiography Methods Imaging, Three-Dimensional Methods Human Image Processing, Computer Assisted Methods Algorithms Evaluation Neural Networks (Computer) Sensitivity and Specificity ab: Cerebrovascular rupture can cause a severe stroke. Three-dimensional time-of-flight (TOF) magnetic resonance angiography (MRA) is a common method of obtaining vascular information. This work proposes a fully automated segmentation method for extracting the vascular anatomy from TOF-MRA. The steps of the method are as follows. First, the brain is extracted on the basis of regional growth and path planning. Next, the brain's highlighted connected area is explored to obtain seed point information, and the Hessian matrix is used to enhance the contrast of image. Finally, a random walker combined with seed points and enhanced images is used to complete vascular anatomy segmentation. The method is tested using 12 sets of data and compared with two traditional vascular segmentation methods. Results show that the described method obtains an average Dice coefficient of 90.68%, and better results were obtained in comparison with the traditional methods. pubtype: Academic Journal doctype: diagnostic images equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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