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A fast double template convolution isocenter evaluation algorithm with subpixel accuracy
Author(s) -
Winey Brian,
Sharp Greg,
Bussière Marc
Publication year - 2011
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.3524227
Subject(s) - isocenter , subpixel rendering , algorithm , convolution (computer science) , computer science , pixel , mathematics , artificial intelligence , optics , physics , imaging phantom , artificial neural network
Purpose: To design a fast Winston Lutz ( fWL ) algorithm for accurate analysis of radiation isocenter from images without edge detection or center of mass calculations. Methods: An algorithm has been developed to implement the Winston Lutz test for mechanical/radiation isocenter agreement using an electronic portal imaging device (EPID). The algorithm detects the position of the radiation shadow of a tungsten ball within a stereotactic cone. The fWL algorithm employs a double convolution to independently find the position of the sphere and cone centers. Subpixel estimation is used to achieve high accuracy. Results of the algorithm were compared to (1) a human observer with template guidance and (2) an edge detection/center of mass (edCOM) algorithm. Testing was performed with high resolution (0.05mm/px, film) and low resolution (0.78mm/px, EPID) image sets. Results: Sphere and cone center relative positions were calculated with the fWL algorithm for high resolution test images with an accuracy of 0.002 ± 0.061 mm compared to 0.042 ± 0.294 mm for the human observer, and 0.003 ± 0.038 mm for the edCOM algorithm. The fWL algorithm required 0.01 s per image compared to 5 s for the edCOM algorithm and 20 s for the human observer. For lower resolution images the fWL algorithm localized the centers with an accuracy of 0.083 ± 0.12 mm compared to 0.03 ± 0.5514 mm for the edCOM algorithm. Conclusions: A fast (subsecond) subpixel algorithm has been developed that can accurately determine the center locations of the ball and cone in Winston Lutz test images without edge detection or COM calculations.