A Low-Interaction Automatic 3D Liver Segmentation Method Using Computed Tomography for Selective Internal Radiation Therapy
Joint Authors
McGoron, Anthony J.
Goryawala, Mohammed
Bhatt, Ruchir
Adjouadi, Malek
Gulec, Seza
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-07-03
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
This study introduces a novel liver segmentation approach for estimating anatomic liver volumes towards selective internal radiation treatment (SIRT).
The algorithm requires minimal human interaction since the initialization process to segment the entire liver in 3D relied on a single computed tomography (CT) slice.
The algorithm integrates a localized contouring algorithm with a modified k-means method.
The modified k-means segments each slice into five distinct regions belonging to different structures.
The liver region is further segmented using localized contouring.
The novelty of the algorithm is in the design of the initialization masks for region contouring to minimize human intervention.
Intensity based region growing together with novel volume of interest (VOI) based corrections is used to accomplish the single slice initialization.
The performance of the algorithm is evaluated using 34 liver CT scans.
Statistical experiments were performed to determine consistency of segmentation and to assess user dependency on the initialization process.
Volume estimations are compared to the manual gold standard.
Results show an average accuracy of 97.22% for volumetric calculation with an average Dice coefficient of 0.92.
Statistical tests show that the algorithm is highly consistent (P=0.55) and independent of user initialization (P=0.20 and Fleiss’ Kappa=0.77±0.06).
American Psychological Association (APA)
Goryawala, Mohammed& Gulec, Seza& Bhatt, Ruchir& McGoron, Anthony J.& Adjouadi, Malek. 2014. A Low-Interaction Automatic 3D Liver Segmentation Method Using Computed Tomography for Selective Internal Radiation Therapy. BioMed Research International،Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-453842
Modern Language Association (MLA)
Goryawala, Mohammed…[et al.]. A Low-Interaction Automatic 3D Liver Segmentation Method Using Computed Tomography for Selective Internal Radiation Therapy. BioMed Research International No. 2014 (2014), pp.1-12.
https://search.emarefa.net/detail/BIM-453842
American Medical Association (AMA)
Goryawala, Mohammed& Gulec, Seza& Bhatt, Ruchir& McGoron, Anthony J.& Adjouadi, Malek. A Low-Interaction Automatic 3D Liver Segmentation Method Using Computed Tomography for Selective Internal Radiation Therapy. BioMed Research International. 2014. Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-453842
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-453842