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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/25087

Title: Automated Winston-Lutz Test for Efficient Quality Control in Stereotactic Radiosurgery
Authors: Darcis, Michiel
Leurs, Gert
Geens, Kenny
Jankelevitch, Alexandra
Swinkels, Wout
Claesen, Luc
Issue Date: 2017
Publisher: IEEE Institute of Electrical and Electronics Engineers
Citation: Li, Qingli; Wang, Lipo; Zhou, Mei; Sun, Li; Qiu, Song; Liu, Hongying (Ed.). Proceedings 2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics CISP-BMEI 2017, IEEE Institute of Electrical and Electronics Engineers,p. 3B-13-3B-18
Status: In Press
Abstract: Modern oncology and neurosurgery treatments often use stereotactic radiosurgery. Using linear accelerators and appropriate collimators, treatments of predefined high localized radiation doses can be concentrated in small volumes inside the patient. This can be used to treat tumors in otherwise difficult reachable zones of the patient, such as inside the head. In order to avoid unnecessary damage to surrounding healthy tissue, the treatment volume must be positioned as accurate as possible. The Winston-Lutz test is a standard test that is used in quality control procedures to verify the correct alignment of CT scan images with respect to the isocenter of the radiation equipment. The Winston-Lutz test uses a metal Tungsten ball positioned at the isocenter of the linear accelerator to calibrate the system under various positions of the gantry and various angles of the collimator in the gantry head and patient table. In current procedures, the calibration images that are captured during the test are manually interpreted, measured on workstation screens by the medical personnel. This paper presents new automatic methods to accurately determine the center of the metal ball, based on the image center of gravity as well as the automatic detection of the center of a square radiation field around the ball. The calibration results obtained from the automatic image processing based calculations are consistent and precise with a mean difference of 0.17 mm and a standard deviation of 0.15 mm.
URI: http://hdl.handle.net/1942/25087
ISBN: 9781538619360
Category: C1
Type: Proceedings Paper
Appears in Collections: Research publications

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