An Evaluation of Atlas Selection Methods for Atlas-Based Automatic Segmentation in Radiotherapy Treatment Planning

Bas Schipaanboord, Djamal Boukerroui*, Devis Peressutti, Johan van Soest, Tim Lustberg, Andre Dekker, Wouter van Elmpt, Mark J. Gooding

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

10 Citations (Web of Science)

Abstract

Atlas-based automatic segmentation is used in radiotherapy planning to accelerate the delineation of organs at risk (OARs). Atlas selection has been proposed as a way to improve the accuracy and execution time of segmentation, assuming that, the more similar the atlas is to the patient, the better the results will be. This paper presents an analysis of atlas selection methods in the context of radiotherapy treatment planning. For a range of commonly contoured OARs, a thorough comparison of a large class of typical atlas selection methods has been performed. For this evaluation, clinically contoured CT images of the head and neck ( ${N}={316}$ ) and thorax ( ${N}={280}$ ) were used. The state-of-the-art intensity and deformation similarity-based atlas selection methods were found to compare poorly to perfect atlas selection. Counter-intuitively, atlas selection methods based on a fixed set of representative atlases outperformed atlas selection methods based on the patient image. This study suggests that atlas-based segmentation with currently available selection methods compares poorly to the potential best performance, hampering the clinical utility of atlas-based segmentation. Effective atlas selection remains an open challenge in atlas-based segmentation for radiotherapy planning.

Original languageEnglish
Pages (from-to)2654-2664
Number of pages11
JournalIeee Transactions on Medical Imaging
Volume38
Issue number11
DOIs
Publication statusPublished - Nov 2019

Keywords

  • Image segmentation
  • Computed tomography
  • Planning
  • Databases
  • Neck
  • Strain
  • Measurement
  • Multi-atlas segmentation
  • atlas selection
  • radiotherapy
  • IMAGE SEGMENTATION
  • AUTO-SEGMENTATION
  • LABEL FUSION
  • REGISTRATION
  • PROSTATE
  • CT
  • COMBINATION
  • VALIDATION
  • STRATEGIES
  • VOLUMES

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