Literature DB >> 32702685

Cost-function testing methodology for image-based registration of endoscopy to CT images in the head and neck.

Runjie B Shi1, Souzan Mirza2, Diego Martinez1, Catriona Douglas3, John Cho1,4, Jonathon C Irish3,5, David A Jaffray1,2,4,5,6, Robert A Weersink1,2,4,5,6.   

Abstract

One of the largest geometric uncertainties in designing radiotherapy treatment plans for squamous cell cancers of the head and neck is contouring the gross tumor volume. We have previously described a method of projecting mucosal disease contours, visible on endoscopy, to volumetrically reconstructed planning computed tomography (CT) datasets, using electromagnetic (EM) tracking of a flexible endoscope, enabling rigid registration between endoscopic and CT images.However, to achieve better accuracy for radiotherapy planning, we propose refining this initial registration with image-based registration methods. In this paper, several types of cost functions are evaluated based on accuracy and robustness. Three phantoms and eight clinical cases are used to test each cost function, with initial registration of endoscopy to CT provided by the pose of the flexible endoscope recovered from EM tracking. Cost function classes include: cross correlation, mutual information and gradient methods. For each test case, a ground truth virtual camera pose was first defined by manual registration of anatomical features visible in both real and virtual endoscope images. A new set of evenly spaced fiducial points and a sample contour were created and projected onto the CT image to be used in assessing image registration quality. A new set of 5000 displaced poses was generated by random sampling displacements along each translational and rotational dimension. At each pose, fiducial and contour points in the real image were again projected on the CT image. The cost function, fiducial registration error and contouring error values were then calculated.While all cost functions performed well in select cases, only the normalized gradient field function consistently had registration errors less than 2 mm, which is the accuracy needed if this application of registering mucosal disease identified on optical image to CT images is to be used in the clinical practice of radiation treatment planning.(Registration: ClinicalTrials.gov NCT02704169).
© 2020 Institute of Physics and Engineering in Medicine.

Entities:  

Keywords:  endoscopy; image registration; radiation therapy

Mesh:

Year:  2020        PMID: 32702685     DOI: 10.1088/1361-6560/aba8b3

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


  2 in total

1.  Feature matching for texture-less endoscopy images via superpixel vector field consistency.

Authors:  Shiyuan Liu; Jingfan Fan; Danni Ai; Hong Song; Tianyu Fu; Yongtian Wang; Jian Yang
Journal:  Biomed Opt Express       Date:  2022-03-18       Impact factor: 3.562

2.  The Feasibility of Haar Feature-Based Endoscopic Ultrasound Probe Tracking for Implanting Hydrogel Spacer in Radiation Therapy for Pancreatic Cancer.

Authors:  Ziwei Feng; Hamed Hooshangnejad; Eun Ji Shin; Amol Narang; Muyinatu A Lediju Bell; Kai Ding
Journal:  Front Oncol       Date:  2021-11-04       Impact factor: 6.244

  2 in total

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