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

L. Wang, Ken Chung Chen, Feng Shi, Shu Liao, Gang Li, Yaozong Gao, Steve G F Shen, Jin Yan, Philip K M Lee, Ben Chow, Nancy X. Liu, James J. Xia, Dinggang Shen

Research output: Chapter in Book/Report/Conference proceedingChapter

18 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationMedical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Pages251-258
Number of pages8
Volume16
EditionPt 3
Publication statusPublished - 2013 Dec 1
Externally publishedYes

Fingerprint

Cone-Beam Computed Tomography
Atlases
Spiral Computed Tomography
Maxilla
Mandible
Artifacts
Noise
Radiation
Costs and Cost Analysis
Therapeutics

ASJC Scopus subject areas

  • Medicine(all)

Cite this

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. In Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention (Pt 3 ed., Vol. 16, pp. 251-258)

Automated segmentation of CBCT image using spiral CT atlases and convex optimization. / Wang, L.; Chen, Ken Chung; Shi, Feng; Liao, Shu; Li, Gang; Gao, Yaozong; Shen, Steve G F; Yan, Jin; Lee, Philip K M; Chow, Ben; Liu, Nancy X.; Xia, James J.; Shen, Dinggang.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Vol. 16 Pt 3. ed. 2013. p. 251-258.

Research output: Chapter in Book/Report/Conference proceedingChapter

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 2013, Automated segmentation of CBCT image using spiral CT atlases and convex optimization. in Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Pt 3 edn, vol. 16, pp. 251-258.
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. In Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Pt 3 ed. Vol. 16. 2013. p. 251-258
Wang, L. ; Chen, Ken Chung ; Shi, Feng ; Liao, Shu ; Li, Gang ; Gao, Yaozong ; Shen, Steve G F ; Yan, Jin ; Lee, Philip K M ; Chow, Ben ; Liu, Nancy X. ; Xia, James J. ; Shen, Dinggang. / Automated segmentation of CBCT image using spiral CT atlases and convex optimization. Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Vol. 16 Pt 3. ed. 2013. pp. 251-258
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