23 January 2017 Hybrid positron emission tomography segmentation of heterogeneous lung tumors using 3D Slicer: improved GrowCut algorithm with threshold initialization
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Abstract
This paper presents an improved GrowCut (IGC), a positron emission tomography-based segmentation algorithm, and tests its clinical applicability. Contrary to the traditional method that requires the user to provide the initial seeds, the IGC algorithm starts with a threshold-based estimate of the tumor and a three-dimensional morphologically grown shell around the tumor as the foreground and background seeds, respectively. The repeatability of IGC from the same observer at multiple time points was compared with the traditional GrowCut algorithm. The algorithm was tested in 11 nonsmall cell lung cancer lesions and validated against the clinician-defined manual contour and compared against the clinically used 25% of the maximum standardized uptake value [SUV-(max)], 40% SUV max , and adaptive threshold methods. The time to edit IGC-defined functional volume to arrive at the gross tumor volume (GTV) was compared with that of manual contouring. The repeatability of the IGC algorithm was very high compared with the traditional GrowCut ( p = 0.003 ) and demonstrated higher agreement with the manual contour with respect to threshold-based methods. Compared with manual contouring, editing the IGC achieved the GTV in significantly less time ( p = 0.11 ). The IGC algorithm offers a highly repeatable functional volume and serves as an effective initial guess that can well minimize the time spent on labor-intensive manual contouring.
© 2017 Society of Photo-Optical Instrumentation Engineers (SPIE)
Devadhas Devakumar, Hannah Mary T. Thomas, Balukrishna Sasidharan, Danie Kingslin Heck, Stephen R. Bowen, E. James Jebaseelan Samuel, "Hybrid positron emission tomography segmentation of heterogeneous lung tumors using 3D Slicer: improved GrowCut algorithm with threshold initialization," Journal of Medical Imaging 4(1), 011009 (23 January 2017). https://doi.org/10.1117/1.JMI.4.1.011009 . Submission: Received: 10 June 2016; Accepted: 20 December 2016
Received: 10 June 2016; Accepted: 20 December 2016; Published: 23 January 2017
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