Literature DB >> 4048266

Prism representation: a 3D ray-tracing algorithm for radiotherapy applications.

R L Siddon.   

Abstract

Computing the intersection of a line with a volume, or 'ray tracing' as it is commonly known, is an integral component of three-dimensional radiotherapy dose calculation algorithms. Examples of ray tracing include the intersection of a ray from the radiation source with the patient, with heterogeneous volumes within the patient and with beam-modifying devices, such as a wedge or compensator. Ray tracing is also of primary importance in the field of three-dimensional computer graphics. Through the process of ray tracing, various display features, such as hidden surfaces, shadows, reflection and refraction, can be rendered simply and with startling realism. Advances have recently been made in three-dimensional ray-tracing methods in computer graphics. Due to the similarity of ray tracing in three-dimensional computer graphics and radiotherapy, these new techniques have an immediate application to the ray-tracing problems in three-dimensional radiotherapy dose calculations. The purpose of this paper is to present these advances and illustrate their use in radiation therapy.

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Year:  1985        PMID: 4048266     DOI: 10.1088/0031-9155/30/8/005

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  13 in total

1.  Monte Carlo evaluation of scatter mitigation strategies in cone-beam CT.

Authors:  Dimitrios Lazos; Jeffrey F Williamson
Journal:  Med Phys       Date:  2010-10       Impact factor: 4.071

2.  Accelerated statistical reconstruction for C-arm cone-beam CT using Nesterov's method.

Authors:  Adam S Wang; J Webster Stayman; Yoshito Otake; Sebastian Vogt; Gerhard Kleinszig; Jeffrey H Siewerdsen
Journal:  Med Phys       Date:  2015-05       Impact factor: 4.071

3.  Variable temporal sampling and tube current modulation for myocardial blood flow estimation from dose-reduced dynamic computed tomography.

Authors:  Dimple Modgil; Michael D Bindschadler; Adam M Alessio; Patrick J La Rivière
Journal:  J Med Imaging (Bellingham)       Date:  2017-05-13

4.  Volume-of-change cone-beam CT for image-guided surgery.

Authors:  Junghoon Lee; J Webster Stayman; Yoshito Otake; Sebastian Schafer; Wojciech Zbijewski; A Jay Khanna; Jerry L Prince; Jeffrey H Siewerdsen
Journal:  Phys Med Biol       Date:  2012-07-17       Impact factor: 3.609

5.  Soft-tissue imaging with C-arm cone-beam CT using statistical reconstruction.

Authors:  Adam S Wang; J Webster Stayman; Yoshito Otake; Gerhard Kleinszig; Sebastian Vogt; Gary L Gallia; A Jay Khanna; Jeffrey H Siewerdsen
Journal:  Phys Med Biol       Date:  2014-02-07       Impact factor: 3.609

6.  Low-dose preview for patient-specific, task-specific technique selection in cone-beam CT.

Authors:  Adam S Wang; J Webster Stayman; Yoshito Otake; Sebastian Vogt; Gerhard Kleinszig; A Jay Khanna; Gary L Gallia; Jeffrey H Siewerdsen
Journal:  Med Phys       Date:  2014-07       Impact factor: 4.071

7.  Acuros CTS: A fast, linear Boltzmann transport equation solver for computed tomography scatter - Part I: Core algorithms and validation.

Authors:  Alexander Maslowski; Adam Wang; Mingshan Sun; Todd Wareing; Ian Davis; Josh Star-Lack
Journal:  Med Phys       Date:  2018-04-06       Impact factor: 4.071

8.  Review of fast monte carlo codes for dose calculation in radiation therapy treatment planning.

Authors:  Keyvan Jabbari
Journal:  J Med Signals Sens       Date:  2011-01

9.  An unsupervised 2D-3D deformable registration network (2D3D-RegNet) for cone-beam CT estimation.

Authors:  You Zhang
Journal:  Phys Med Biol       Date:  2021-03-24       Impact factor: 4.174

10.  Design and system evaluation of a dual-panel portable PET (DP-PET).

Authors:  Tianyi Zeng; Jiaxu Zheng; Xinyuan Xia; Xin Chen; Beien Wang; Shuangyue Zhang; Adam Chandler; Tuoyu Cao; Lingzhi Hu; Qun Chen; Xu Chu
Journal:  EJNMMI Phys       Date:  2021-06-12
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