Supervised method to build an atlas database for multi-atlas segmentation-propagation

Shen, Kaikai, Bourgeat, Pierrick, Fripp, Jurgen, Meriaudeau, Fabrice, Ames, David, Ellis, Kathryn A., Masters, Colin L., Villemagne, Victor L, Rowe, Christopher C, and Salvado, Olivier (2010). Supervised method to build an atlas database for multi-atlas segmentation-propagation. In: Progress in Biomedical Optics and Imaging: Proceedings of SPIE, Volume 7624. Conference on Medical Imaging 2010 - Computer-Aided Diagnosis, San Diego, CA, United States, (76241N -1-76241N -8). 14-16 February 2010. doi:10.1117/12.844048

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Author Shen, Kaikai
Bourgeat, Pierrick
Fripp, Jurgen
Meriaudeau, Fabrice
Ames, David
Ellis, Kathryn A.
Masters, Colin L.
Villemagne, Victor L
Rowe, Christopher C,
Salvado, Olivier
Title of paper Supervised method to build an atlas database for multi-atlas segmentation-propagation
Conference name Conference on Medical Imaging 2010 - Computer-Aided Diagnosis
Conference location San Diego, CA, United States
Conference dates 14-16 February 2010
Proceedings title Progress in Biomedical Optics and Imaging: Proceedings of SPIE, Volume 7624   Check publisher's open access policy
Journal name Medical Imaging 2010: Computer - Aided Diagnosis   Check publisher's open access policy
Place of Publication Bellingham, WA, United States
Publisher S P I E - International Society for Optical Engineering
Publication Year 2010
Sub-type Fully published paper
DOI 10.1117/12.844048
Open Access Status File (Publisher version)
ISBN 9780819480279
ISSN 0277-786X
Volume 7624
Issue Part 1
Start page 76241N -1
End page 76241N -8
Total pages 8
Language eng
Abstract/Summary Multi-atlas based segmentation-propagation approaches have been shown to obtain accurate parcelation of brain structures. However, this approach requires a large number of manually delineated atlases, which are often not available. We propose a supervised method to build a population specific atlas database, using the publicly available Internet Brain Segmentation Repository (IBSR). The set of atlases grows iteratively as new atlases are added, so that its segmentation capability may be enhanced in the multi-atlas based approach. Using a dataset of 210 MR images of elderly subjects (170 elderly controls, 40 Alzheimer's disease) from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study, 40 MR images were segmented to build a population specific atlas database for the purpose of multi-atlas segmentation-propagation. The population specific atlases were used to segment the elderly population of 210 MR images, and were evaluated in terms of the agreement among the propagated labels. The agreement was measured by using the entropy H of the probability image produced when fused by voting rule and the partial moment mu(2) of the histogram. Compared with using IBSR atlases, the population specific atlases obtained a higher agreement when dealing with images of elderly subjects.
Keyword Image segmentation
Multi-atlas segmentation-propagation
Mri
Q-Index Code E1
Q-Index Status Provisional Code
Institutional Status Non-UQ
Additional Notes Article number 76241N. Progress in Biomedical Optics and Imaging (1605-7422) Vol. 11, No. 34

 
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