An approach of exposure dose reduction of cone-beam computed tomography in an image guided patient positioning system by using various noise suppression filters

Hidemi Kamezawa, Katsutoshi Shirieda, Hidetaka Arimura, Noboru Kameda, Masafumi Ohki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

We have investigated an approach of exposure dose reduction in image guided patient positioning (IGPP) system based on noise suppression filters for cone-beam computed tomography (CBCT) images. Three axis translations (left-right, anterior-posterior, superior-inferior) were performed on the IGPP system as patient setup errors between a planning CT image and the low-dose (LD)-CBCT images, which were processed by 6 noise suppression filters, i.e., averaging filter (AF), median filter (MF), Gaussian filter (GF), bilateral filter (BF), edge preserving smoothing filter (EPF), and adaptive partial median filter (AMF). A reference dose (RD) and low-dose (LD)-CBCT images were acquired with a reference exposure dose of 86.2 mGy and various low exposure doses of 1.4 to 43.1 mGy, respectively. The exposure doses were estimated by use of weighted CT dose index (CTDIW). Residual errors representing the patient positioning accuracy were calculated as an Euclidean distance between setup error vectors estimated using the LD-CBCT image and RD-CBCT image. The residual errors as a function of the exposure dose (CTDIW) were obtained for LD-CBCT images processed by the 6 noise suppression filters, and then the exposure doses for the 6 filtered LD-CBCT images were estimated at a residual error, which was a baseline obtained with the RD-CBCT. This approach was applied to an anthropomorphic pelvic phantom. Our phantom study showed that the exposure doses could be reduced from 67% (EPF) to 77% (AMF) while keeping the same residual error as the RD-CBCT by applying the noise suppression filters to the LD-CBCT images. The preliminary results suggested that applying noise suppression filters, particularly an adaptive partial median filter, could be feasible to decrease the additional exposure dose to patients in IGPP systems

Original languageEnglish
Title of host publication2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1475-1480
Number of pages6
ISBN (Electronic)9781479959556
DOIs
Publication statusPublished - Feb 18 2014
Event2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014 - Kitakyushu, Japan
Duration: Dec 3 2014Dec 6 2014

Publication series

Name2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014

Other

Other2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014
Country/TerritoryJapan
CityKitakyushu
Period12/3/1412/6/14

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence

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