Literature DB >> 22149818

Robust automatic segmentation of multiple implanted cylindrical gold fiducial markers in cone-beam CT projections.

Walther Fledelius1, Esben Worm, Ulrik V Elstrøm, Jørgen B Petersen, Cai Grau, Morten Høyer, Per R Poulsen.   

Abstract

PURPOSE: Implanted fiducial markers, which are used to correct for day-to-day variations, may potentially also be used to correct for intrafraction motion measurements. However, before any treatment can make use of, and react to, the position of the inserted markers they have to be segmented, either manually through expert user intervention or automatically from an imaging system. In the current study, we aimed to establish a robust and autonomous segmentation method for implanted cylindrical gold markers in a single set of projections from a cone-beam computed tomography (CBCT).
METHODS: Multiple cylindrical gold markers were segmented in the projection images of CBCT scans by five sequential steps. Initially, marker candidates were identified in all projections with a blob detection routine, and then traced in subsequent projections. Traces inconsistent with a 3D marker position were rejected, and the best remaining traces were identified and used for the construction of a 3D marker constellation model, consisting of the size, position and orientation of the markers. Finally, projections of the model were used to generate templates for the final template-based marker segmentation. Hereby, challenging situations such as overlap of markers and low contrast regions were taken into account. The segmentation method was tested in 63 CBCT scans from 11 patients with 2-4 cylindrical gold markers implanted in the prostate and for 62 CBCT scans from six patients each with 2-3 cylindrical gold markers implanted in the liver and up to two cylindrical markers placed externally on the abdomen. After segmentation all projections of the 125 scans were manually inspected, and a successful segmentation was registered if the segmented position was within the projection of the marker.
RESULTS: For prostate markers, the segmentation was successful in 99.8% of the projections. For the liver patients, liver markers and external markers were segmented successfully in 99.9 and 99.8% of the projections, respectively. All markers were identified in the 3D marker constellation model. The most common source of segmentation error was low contrast and motion of markers relative to each other, which resulted in a discrepancy between the template and actual projection appearance during marker overlap. Markers were overlapping in 20, 2.7, and 0.1% of the projections for prostate, liver, and external, respectively.
CONCLUSIONS: We have successfully implemented a new method that, without prior knowledge on marker size, position, orientation, and number, autonomously segments cylindrical gold markers from CBCT projections with a high success rate, despite overlap, motion, and low contrast.

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Year:  2011        PMID: 22149818     DOI: 10.1118/1.3658566

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


  7 in total

1.  A framework for automatic creation of gold-standard rigid 3D-2D registration datasets.

Authors:  Hennadii Madan; Franjo Pernuš; Boštjan Likar; Žiga Špiclin
Journal:  Int J Comput Assist Radiol Surg       Date:  2016-09-21       Impact factor: 2.924

2.  Kilovoltage intrafraction monitoring for prostate intensity modulated arc therapy: first clinical results.

Authors:  Jin Aun Ng; Jeremy T Booth; Per R Poulsen; Walther Fledelius; Esben Schjødt Worm; Thomas Eade; Fiona Hegi; Andrew Kneebone; Zdenka Kuncic; Paul J Keall
Journal:  Int J Radiat Oncol Biol Phys       Date:  2012-09-11       Impact factor: 7.038

3.  Automated target tracking in kilovoltage images using dynamic templates of fiducial marker clusters.

Authors:  Warren G Campbell; Moyed Miften; Bernard L Jones
Journal:  Med Phys       Date:  2017-02       Impact factor: 4.071

4.  Development and clinical evaluation of automatic fiducial detection for tumor tracking in cine megavoltage images during volumetric modulated arc therapy.

Authors:  Juan Diego Azcona; Ruijiang Li; Edward Mok; Steven Hancock; Lei Xing
Journal:  Med Phys       Date:  2013-03       Impact factor: 4.071

5.  Robust methods for automatic image-to-world registration in cone-beam CT interventional guidance.

Authors:  H Dang; Y Otake; S Schafer; J W Stayman; G Kleinszig; J H Siewerdsen
Journal:  Med Phys       Date:  2012-10       Impact factor: 4.506

6.  Automatic Detection and Tracking of Marker Seeds Implanted in Prostate Cancer Patients using a Deep Learning Algorithm.

Authors:  Keya Amarsee; Prabhakar Ramachandran; Andrew Fielding; Margot Lehman; Christopher Noble; Ben Perrett; Daryl Ning
Journal:  J Med Phys       Date:  2021-08-07

7.  First clinical implementation of audiovisual biofeedback in liver cancer stereotactic body radiation therapy.

Authors:  Sean Pollock; Regina Tse; Darren Martin; Lisa McLean; Gwi Cho; Robin Hill; Sheila Pickard; Paul Aston; Chen-Yu Huang; Kuldeep Makhija; Ricky O'Brien; Paul Keall
Journal:  J Med Imaging Radiat Oncol       Date:  2015-08-06       Impact factor: 1.735

  7 in total

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