A knowledge-guided active model method of skull segmentation on T1-weighted MR images

Zuyao Y. Shan, Chia Ho Hua, Qing Ji, Carlos Parra, Xiaofei Ying, Matthew J. Krasin, Thomas E. Merchant, Larry E. Kun, Wilburn E. Reddick

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Skull is the anatomic landmark for patient set up of head radiation therapy. Skull is generally segmented from CT images because CT provides better definition of skull than MR imaging. In the mean time, radiation therapy is planned on MR images for soft tissue information. This study utilized a knowledge-guided active model (KAM) method to segmented skull on MR images in order to enable radiation therapy planning with MR images as the primary planning dataset. KAM utilized age-specific skull mesh models that segmented from CT images using a conditional region growing algorithm. Skull models were transformed to given MR images using an affine registration algorithm based on normalized mutual information. The transformed mesh models actively located skull boundaries by minimizing their total energy. The preliminary validation was performed on MR and CT images from five patients. The KAM segmented skulls were compared with those segmented from CT images. The average image similarity (kappa index) was 0.57. The initial validation showed that it was promising to segment skulls directly on MR images using KAM.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2007
Subtitle of host publicationImage Processing
EditionPART 2
DOIs
StatePublished - Nov 23 2007
EventMedical Imaging 2007: Image Processing - San Diego, CA, United States
Duration: Feb 18 2007Feb 20 2007

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
NumberPART 2
Volume6512
ISSN (Print)1605-7422

Other

OtherMedical Imaging 2007: Image Processing
CountryUnited States
CitySan Diego, CA
Period2/18/072/20/07

Keywords

  • Mathematical morphology
  • Registration
  • Segmentation

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics
  • Biomaterials
  • Radiology Nuclear Medicine and imaging

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    Shan, Z. Y., Hua, C. H., Ji, Q., Parra, C., Ying, X., Krasin, M. J., Merchant, T. E., Kun, L. E., & Reddick, W. E. (2007). A knowledge-guided active model method of skull segmentation on T1-weighted MR images. In Medical Imaging 2007: Image Processing (PART 2 ed.). [65122R] (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 6512, No. PART 2). https://doi.org/10.1117/12.709801