Journal
MEDICAL IMAGE ANALYSIS
Volume 17, Issue 8, Pages 929-945Publisher
ELSEVIER
DOI: 10.1016/j.media.2013.05.004
Keywords
Simultaneous segmentation; PET segmentation; Random Walk; MRI-PET Co-segmentation; PET-CT Co-segmentation
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Funding
- Center for Infectious Disease Imaging (CIDI)
- National Institutes of Allergy and Infectious Diseases (NIAID)
- National Institutes of Bio-imaging and Bioengineering (NIBIB) at the National Institutes of Health (NIH)
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We present a novel method for the joint segmentation of anatomical and functional images. Our proposed methodology unifies the domains of anatomical and functional images, represents them in a product lattice, and performs simultaneous delineation of regions based on random walk image segmentation. Furthermore, we also propose a simple yet effective object/background seed localization method to make the proposed segmentation process fully automatic. Our study uses PET, PET-CT, MRI-PET, and fused MRI-PET-CT scans (77 studies in all) from 56 patients who had various lesions in different body regions. We validated the effectiveness of the proposed method on different PET phantoms as well as on clinical images with respect to the ground truth segmentation provided by clinicians. Experimental results indicate that the presented method is superior to threshold and Bayesian methods commonly used in PET image segmentation, is more accurate and robust compared to the other PET-CT segmentation methods recently published in the literature, and also it is general in the sense of simultaneously segmenting multiple scans in real-time with high accuracy needed in routine clinical use. Published by Elsevier B.V.
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