Segmentation of Hyperacute Cerebral Infarcts Based on Sparse Representation of Diffusion Weighted Imaging
Joint Authors
Hu, Qingmao
Zhang, Xiaodong
Jing, Shasha
Gao, Peiyi
Xue, Jing
Su, Lu
Li, Weiping
Ren, Lijie
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-09-22
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
Segmentation of infarcts at hyperacute stage is challenging as they exhibit substantial variability which may even be hard for experts to delineate manually.
In this paper, a sparse representation based classification method is explored.
For each patient, four volumetric data items including three volumes of diffusion weighted imaging and a computed asymmetry map are employed to extract patch features which are then fed to dictionary learning and classification based on sparse representation.
Elastic net is adopted to replace the traditional L0-norm/L1-norm constraints on sparse representation to stabilize sparse code.
To decrease computation cost and to reduce false positives, regions-of-interest are determined to confine candidate infarct voxels.
The proposed method has been validated on 98 consecutive patients recruited within 6 hours from onset.
It is shown that the proposed method could handle well infarcts with intensity variability and ill-defined edges to yield significantly higher Dice coefficient (0.755 ± 0.118) than the other two methods and their enhanced versions by confining their segmentations within the regions-of-interest (average Dice coefficient less than 0.610).
The proposed method could provide a potential tool to quantify infarcts from diffusion weighted imaging at hyperacute stage with accuracy and speed to assist the decision making especially for thrombolytic therapy.
American Psychological Association (APA)
Zhang, Xiaodong& Jing, Shasha& Gao, Peiyi& Xue, Jing& Su, Lu& Li, Weiping…[et al.]. 2016. Segmentation of Hyperacute Cerebral Infarcts Based on Sparse Representation of Diffusion Weighted Imaging. Computational and Mathematical Methods in Medicine،Vol. 2016, no. 2016, pp.1-14.
https://search.emarefa.net/detail/BIM-1100084
Modern Language Association (MLA)
Zhang, Xiaodong…[et al.]. Segmentation of Hyperacute Cerebral Infarcts Based on Sparse Representation of Diffusion Weighted Imaging. Computational and Mathematical Methods in Medicine No. 2016 (2016), pp.1-14.
https://search.emarefa.net/detail/BIM-1100084
American Medical Association (AMA)
Zhang, Xiaodong& Jing, Shasha& Gao, Peiyi& Xue, Jing& Su, Lu& Li, Weiping…[et al.]. Segmentation of Hyperacute Cerebral Infarcts Based on Sparse Representation of Diffusion Weighted Imaging. Computational and Mathematical Methods in Medicine. 2016. Vol. 2016, no. 2016, pp.1-14.
https://search.emarefa.net/detail/BIM-1100084
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1100084