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Discriminative Random Field Segmentation of Lung Nodules in CT Studies
Joint Authors
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-07-02
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
The ability to conduct high-quality semiautomatic 3D segmentation of lung nodules in CT scans is of high value to busy radiologists.
Discriminative random fields (DRFs) were used to segment 3D volumes of lung nodules in CT scan data using only one seed point per nodule.
Optimal parameters for the DRF inference were first found using simulated annealing.
These parameters were then used to solve the inference problem using the graph cuts algorithm.
Results of the segmentation exhibited high precision and recall.
The system can be adapted to facilitate the process of longitudinal studies but will still require human checking for failed cases.
American Psychological Association (APA)
Liu, Brian& Raj, Ashish. 2013. Discriminative Random Field Segmentation of Lung Nodules in CT Studies. Computational and Mathematical Methods in Medicine،Vol. 2013, no. 2013, pp.1-9.
https://search.emarefa.net/detail/BIM-490238
Modern Language Association (MLA)
Liu, Brian& Raj, Ashish. Discriminative Random Field Segmentation of Lung Nodules in CT Studies. Computational and Mathematical Methods in Medicine No. 2013 (2013), pp.1-9.
https://search.emarefa.net/detail/BIM-490238
American Medical Association (AMA)
Liu, Brian& Raj, Ashish. Discriminative Random Field Segmentation of Lung Nodules in CT Studies. Computational and Mathematical Methods in Medicine. 2013. Vol. 2013, no. 2013, pp.1-9.
https://search.emarefa.net/detail/BIM-490238
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-490238