Literature DB >> 26539630

Evaluation and optimization of the parameters used in multiple-atlas-based segmentation of prostate cancers in radiation therapy.

Wicger K H Wong1, Lucullus H T Leung1, Dora L W Kwong2.   

Abstract

OBJECTIVE: To evaluate and optimize the parameters used in multiple-atlas-based segmentation of prostate cancers in radiation therapy.
METHODS: A retrospective study was conducted, and the accuracy of the multiple-atlas-based segmentation was tested on 30 patients. The effect of library size (LS), number of atlases used for contour averaging and the contour averaging strategy were also studied. The autogenerated contours were compared with the manually drawn contours. Dice similarity coefficient (DSC) and Hausdorff distance were used to evaluate the segmentation agreement.
RESULTS: Mixed results were found between simultaneous truth and performance level estimation (STAPLE) and majority vote (MV) strategies. Multiple-atlas approaches were relatively insensitive to LS. A LS of ten was adequate, and further increase in the LS only showed insignificant gain. Multiple atlas performed better than single atlas for most of the time. Using more atlases did not guarantee better performance, with five atlases performing better than ten atlases. With our recommended setting, the median DSC for the bladder, rectum, prostate, seminal vesicle and femurs was 0.90, 0.77, 0.84, 0.56 and 0.95, respectively.
CONCLUSION: Our study shows that multiple-atlas-based strategies have better accuracy than single-atlas approach. STAPLE is preferred, and a LS of ten is adequate for prostate cases. Using five atlases for contour averaging is recommended. The contouring accuracy of seminal vesicle still needs improvement, and manual editing is still required for the other structures. ADVANCES IN KNOWLEDGE: This article provides a better understanding of the influence of the parameters used in multiple-atlas-based segmentation of prostate cancers.

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Year:  2015        PMID: 26539630      PMCID: PMC4985939          DOI: 10.1259/bjr.20140732

Source DB:  PubMed          Journal:  Br J Radiol        ISSN: 0007-1285            Impact factor:   3.039


  13 in total

1.  Multi-atlas based segmentation of brain images: atlas selection and its effect on accuracy.

Authors:  P Aljabar; R A Heckemann; A Hammers; J V Hajnal; D Rueckert
Journal:  Neuroimage       Date:  2009-02-23       Impact factor: 6.556

2.  Automatic segmentation of the prostate in 3D MR images by atlas matching using localized mutual information.

Authors:  Stefan Klein; Uulke A van der Heide; Irene M Lips; Marco van Vulpen; Marius Staring; Josien P W Pluim
Journal:  Med Phys       Date:  2008-04       Impact factor: 4.071

3.  Computer-assisted, atlas-based segmentation for target volume delineation in whole pelvic IMRT for prostate cancer.

Authors:  Sunanda Pejavar; Sue S Yom; Andrew Hwang; Joycelyn Speight; Alexander Gottschalk; I-Chow Hsu; Mack Roach; Ping Xia
Journal:  Technol Cancer Res Treat       Date:  2012-12-26

4.  The utility of atlas-assisted segmentation in the male pelvis is dependent on the interobserver agreement of the structures segmented.

Authors:  K A Langmack; C Perry; C Sinstead; J Mills; D Saunders
Journal:  Br J Radiol       Date:  2014-08-29       Impact factor: 3.039

Review 5.  Vision 20/20: perspectives on automated image segmentation for radiotherapy.

Authors:  Gregory Sharp; Karl D Fritscher; Vladimir Pekar; Marta Peroni; Nadya Shusharina; Harini Veeraraghavan; Jinzhong Yang
Journal:  Med Phys       Date:  2014-05       Impact factor: 4.071

6.  Biomechanical-based image registration for head and neck radiation treatment.

Authors:  Adil Al-Mayah; Joanne Moseley; Shannon Hunter; Mike Velec; Lily Chau; Stephen Breen; Kristy Brock
Journal:  Phys Med Biol       Date:  2010-10-19       Impact factor: 3.609

7.  Clinical validation of atlas-based auto-segmentation of pelvic volumes and normal tissue in rectal tumors using auto-segmentation computed system.

Authors:  Maria Antonietta Gambacorta; Chiara Valentini; Nicola Dinapoli; Luca Boldrini; Nicola Caria; Maria Cristina Barba; Gian Carlo Mattiucci; Danilo Pasini; Bruce Minsky; Vincenzo Valentini
Journal:  Acta Oncol       Date:  2013-01-22       Impact factor: 4.089

8.  Development of RTOG consensus guidelines for the definition of the clinical target volume for postoperative conformal radiation therapy for prostate cancer.

Authors:  Jeff M Michalski; Colleen Lawton; Issam El Naqa; Mark Ritter; Elizabeth O'Meara; Michael J Seider; W Robert Lee; Seth A Rosenthal; Thomas Pisansky; Charles Catton; Richard K Valicenti; Anthony L Zietman; Walter R Bosch; Howard Sandler; Mark K Buyyounouski; Cynthia Ménard
Journal:  Int J Radiat Oncol Biol Phys       Date:  2009-04-23       Impact factor: 7.038

9.  Technology assessment of automated atlas based segmentation in prostate bed contouring.

Authors:  Jeremiah Hwee; Alexander V Louie; Stewart Gaede; Glenn Bauman; David D'Souza; Tracy Sexton; Michael Lock; Belal Ahmad; George Rodrigues
Journal:  Radiat Oncol       Date:  2011-09-09       Impact factor: 3.481

10.  Systematic evaluation of three different commercial software solutions for automatic segmentation for adaptive therapy in head-and-neck, prostate and pleural cancer.

Authors:  Mariangela La Macchia; Francesco Fellin; Maurizio Amichetti; Marco Cianchetti; Stefano Gianolini; Vitali Paola; Antony J Lomax; Lamberto Widesott
Journal:  Radiat Oncol       Date:  2012-09-18       Impact factor: 3.481

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  9 in total

Review 1.  Automation in intensity modulated radiotherapy treatment planning-a review of recent innovations.

Authors:  Mohammad Hussein; Ben J M Heijmen; Dirk Verellen; Andrew Nisbet
Journal:  Br J Radiol       Date:  2018-09-04       Impact factor: 3.039

2.  Automatic Segmentation of Clinical Target Volume and Organs-at-Risk for Breast Conservative Radiotherapy Using a Convolutional Neural Network.

Authors:  Fangjie Liu; Wanqi Chen; Zhikai Liu; Yinjie Tao; Xia Liu; Fuquan Zhang; Jing Shen; Hui Guan; Hongnan Zhen; Shaobin Wang; Qi Chen; Yu Chen; Xiaorong Hou
Journal:  Cancer Manag Res       Date:  2021-11-02       Impact factor: 3.989

3.  Auto-segmentations by convolutional neural network in cervical and anorectal cancer with clinical structure sets as the ground truth.

Authors:  Hanna Sartor; David Minarik; Olof Enqvist; Johannes Ulén; Anders Wittrup; Maria Bjurberg; Elin Trägårdh
Journal:  Clin Transl Radiat Oncol       Date:  2020-09-14

4.  Iterative framework for the joint segmentation and CT synthesis of MR images: application to MRI-only radiotherapy treatment planning.

Authors:  Ninon Burgos; Filipa Guerreiro; Jamie McClelland; Benoît Presles; Marc Modat; Simeon Nill; David Dearnaley; Nandita deSouza; Uwe Oelfke; Antje-Christin Knopf; Sébastien Ourselin; M Jorge Cardoso
Journal:  Phys Med Biol       Date:  2017-03-14       Impact factor: 3.609

5.  Atlas-based auto-segmentation for postoperative radiotherapy planning in endometrial and cervical cancers.

Authors:  Nalee Kim; Jee Suk Chang; Yong Bae Kim; Jin Sung Kim
Journal:  Radiat Oncol       Date:  2020-05-13       Impact factor: 3.481

6.  Methodological approach to create an atlas using a commercial auto-contouring software.

Authors:  Marta Casati; Stefano Piffer; Silvia Calusi; Livia Marrazzo; Gabriele Simontacchi; Vanessa Di Cataldo; Daniela Greto; Isacco Desideri; Marco Vernaleone; Giulio Francolini; Lorenzo Livi; Stefania Pallotta
Journal:  J Appl Clin Med Phys       Date:  2020-11-25       Impact factor: 2.102

7.  The clinical evaluation of atlas-based auto-segmentation for automatic contouring during cervical cancer radiotherapy.

Authors:  Yi Li; Wenjing Wu; Yuchen Sun; Dequan Yu; Yuemei Zhang; Long Wang; Yao Wang; Xiaozhi Zhang; Yongkai Lu
Journal:  Front Oncol       Date:  2022-08-02       Impact factor: 5.738

8.  Analysis of Geometric Performance and Dosimetric Impact of Using Automatic Contour Segmentation for Radiotherapy Planning.

Authors:  Minsong Cao; Bradley Stiehl; Victoria Y Yu; Ke Sheng; Amar U Kishan; Robert K Chin; Yingli Yang; Dan Ruan
Journal:  Front Oncol       Date:  2020-09-23       Impact factor: 6.244

9.  Clinical validation of an automatic atlas-based segmentation tool for male pelvis CT images.

Authors:  Marta Casati; Stefano Piffer; Silvia Calusi; Livia Marrazzo; Gabriele Simontacchi; Vanessa Di Cataldo; Daniela Greto; Isacco Desideri; Marco Vernaleone; Giulio Francolini; Lorenzo Livi; Stefania Pallotta
Journal:  J Appl Clin Med Phys       Date:  2022-01-22       Impact factor: 2.102

  9 in total

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