Literature DB >> 18649478

Focused beam-stop array for the measurement of scatter in megavoltage portal and cone beam CT imaging.

Jonathan S Maltz1, Bijumon Gangadharan, Marie Vidal, Ajay Paidi, Supratik Bose, Bruce A Faddegon, Michele Aubin, Olivier Morin, Jean Pouliot, Zirao Zheng, Michelle M Svatos, Ali R Bani-Hashemi.   

Abstract

We describe a focused beam-stop array (BSA) for the measurement of object scatter in imaging systems that utilize x-ray beams in the megavoltage (MV) energy range. The BSA consists of 64 doubly truncated tungsten cone elements of 0.5 cm maximum diameter that are arranged in a regular array on an acrylic slab. The BSA is placed in the accessory tray of a medical linear accelerator at a distance of approximately 50 cm from the focal spot. We derive an expression that allows us to estimate the scatter in an image taken without the array present, given image values in a second image with the array in place. The presence of the array reduces fluence incident on the imaged object. This leads to an object-dependent underestimation bias in the scatter measurements. We apply corrections in order to address this issue. We compare estimates of the flat panel detector response to scatter obtained using the BSA to those derived from Monte Carlo simulations. We find that the two estimates agree to within 10% in terms of RMS error for 30 cm x 30 cm water slabs in the thickness range of 10-30 cm. Larger errors in the scatter estimates are encountered for thinner objects, probably owing to extrafocal radiation sources. However, RMS errors in the estimates of primary images are no more than 5% for water slab thicknesses in the range of 1-30 cm. The BSA scatter estimates are also used to correct cone beam tomographic projections. Maximum deviations of central profiles of uniform water phantoms are reduced from 193 to 19 HU after application of corrections for scatter, beam hardening, and lateral truncation that are based on the BSA-derived scatter estimate. The same corrections remove the typical cupping artifact from both phantom and patient images. The BSA proves to be a useful tool for quantifying and removing image scatter, as well as for validating models of MV imaging systems.

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Year:  2008        PMID: 18649478     DOI: 10.1118/1.2924220

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  9 in total

1.  Scatter correction for full-fan volumetric CT using a stationary beam blocker in a single full scan.

Authors:  Tianye Niu; Lei Zhu
Journal:  Med Phys       Date:  2011-11       Impact factor: 4.071

2.  Estimating scatter from sparsely measured primary signal.

Authors:  Gongting Wu; Christina R Inscoe; Jabari Calliste; Jing Shan; Yueh Z Lee; Otto Zhou; Jianping Lu
Journal:  J Med Imaging (Bellingham)       Date:  2017-03-29

3.  Impact of flat panel-imager veiling glare on scatter-estimation accuracy and image quality of a commercial on-board cone-beam CT imaging system.

Authors:  Dimitrios Lazos; Jeffrey F Williamson
Journal:  Med Phys       Date:  2012-09       Impact factor: 4.071

4.  Learning-based CBCT correction using alternating random forest based on auto-context model.

Authors:  Yang Lei; Xiangyang Tang; Kristin Higgins; Jolinta Lin; Jiwoong Jeong; Tian Liu; Anees Dhabaan; Tonghe Wang; Xue Dong; Robert Press; Walter J Curran; Xiaofeng Yang
Journal:  Med Phys       Date:  2018-12-11       Impact factor: 4.071

5.  Image-domain shading correction for cone-beam CT without prior patient information.

Authors:  Qiyong Fan; Bo Lu; Justin C Park; Tianye Niu; Jonathan G Li; Chihray Liu; Lei Zhu
Journal:  J Appl Clin Med Phys       Date:  2015-11-08       Impact factor: 2.102

6.  A Simple Scatter Reduction Method in Cone-Beam Computed Tomography for Dental and Maxillofacial Applications Based on Monte Carlo Simulation.

Authors:  Chalinee Thanasupsombat; Saowapak S Thongvigitmanee; Sorapong Aootaphao; Pairash Thajchayapong
Journal:  Biomed Res Int       Date:  2018-01-03       Impact factor: 3.411

7.  Shading artifact correction in breast CT using an interleaved deep learning segmentation and maximum-likelihood polynomial fitting approach.

Authors:  Peymon Ghazi; Andrew M Hernandez; Craig Abbey; Kai Yang; John M Boone
Journal:  Med Phys       Date:  2019-06-23       Impact factor: 4.071

8.  Low-dose and scatter-free cone-beam CT imaging using a stationary beam blocker in a single scan: phantom studies.

Authors:  Xue Dong; Michael Petrongolo; Tianye Niu; Lei Zhu
Journal:  Comput Math Methods Med       Date:  2013-11-20       Impact factor: 2.238

9.  X-Ray Scatter Correction on Soft Tissue Images for Portable Cone Beam CT.

Authors:  Sorapong Aootaphao; Saowapak S Thongvigitmanee; Jartuwat Rajruangrabin; Chalinee Thanasupsombat; Tanapon Srivongsa; Pairash Thajchayapong
Journal:  Biomed Res Int       Date:  2016-02-16       Impact factor: 3.411

  9 in total

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