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Automated segmentation of CBCT image using spiral CT atlases and convex optimization.

Publication ,  Journal Article
Wang, L; Chen, KC; Shi, F; Liao, S; Li, G; Gao, Y; Shen, SGF; Yan, J; Lee, PKM; Chow, B; Liu, NX; Xia, JJ; Shen, D
Published in: Med Image Comput Comput Assist Interv
2013

Cone-beam computed tomography (CBCT) is an increasingly utilized imaging modality for the diagnosis and treatment planning of the patients with craniomaxillofacial (CMF) deformities. CBCT scans have relatively low cost and low radiation dose in comparison to conventional spiral CT scans. However, a major limitation of CBCT scans is the widespread image artifacts such as noise, beam hardening and inhomogeneity, causing great difficulties for accurate segmentation of bony structures from soft tissues, as well as separating mandible from maxilla. In this paper, we presented a novel fully automated method for CBCT image segmentation. In this method, we first estimated a patient-specific atlas using a sparse label fusion strategy from predefined spiral CT atlases. This patient-specific atlas was then integrated into a convex segmentation framework based on maximum a posteriori probability for accurate segmentation. Finally, the performance of our method was validated via comparisons with manual ground-truth segmentations.

Duke Scholars

Published In

Med Image Comput Comput Assist Interv

DOI

Publication Date

2013

Volume

16

Issue

Pt 3

Start / End Page

251 / 258

Location

Germany

Related Subject Headings

  • Young Adult
  • Spiral Cone-Beam Computed Tomography
  • Sensitivity and Specificity
  • Reproducibility of Results
  • Radiographic Image Interpretation, Computer-Assisted
  • Radiographic Image Enhancement
  • Pattern Recognition, Automated
  • Middle Aged
  • Maxillofacial Abnormalities
  • Male
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Wang, L., Chen, K. C., Shi, F., Liao, S., Li, G., Gao, Y., … Shen, D. (2013). Automated segmentation of CBCT image using spiral CT atlases and convex optimization. Med Image Comput Comput Assist Interv, 16(Pt 3), 251–258. https://doi.org/10.1007/978-3-642-40760-4_32
Wang, Li, Ken Chung Chen, Feng Shi, Shu Liao, Gang Li, Yaozong Gao, Steve G. F. Shen, et al. “Automated segmentation of CBCT image using spiral CT atlases and convex optimization.Med Image Comput Comput Assist Interv 16, no. Pt 3 (2013): 251–58. https://doi.org/10.1007/978-3-642-40760-4_32.
Wang L, Chen KC, Shi F, Liao S, Li G, Gao Y, et al. Automated segmentation of CBCT image using spiral CT atlases and convex optimization. Med Image Comput Comput Assist Interv. 2013;16(Pt 3):251–8.
Wang, Li, et al. “Automated segmentation of CBCT image using spiral CT atlases and convex optimization.Med Image Comput Comput Assist Interv, vol. 16, no. Pt 3, 2013, pp. 251–58. Pubmed, doi:10.1007/978-3-642-40760-4_32.
Wang L, Chen KC, Shi F, Liao S, Li G, Gao Y, Shen SGF, Yan J, Lee PKM, Chow B, Liu NX, Xia JJ, Shen D. Automated segmentation of CBCT image using spiral CT atlases and convex optimization. Med Image Comput Comput Assist Interv. 2013;16(Pt 3):251–258.

Published In

Med Image Comput Comput Assist Interv

DOI

Publication Date

2013

Volume

16

Issue

Pt 3

Start / End Page

251 / 258

Location

Germany

Related Subject Headings

  • Young Adult
  • Spiral Cone-Beam Computed Tomography
  • Sensitivity and Specificity
  • Reproducibility of Results
  • Radiographic Image Interpretation, Computer-Assisted
  • Radiographic Image Enhancement
  • Pattern Recognition, Automated
  • Middle Aged
  • Maxillofacial Abnormalities
  • Male