Atlas Diffeomorphisms Via Object Models Public Deposited

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Last Modified
  • March 19, 2019
Creator
  • Saboo, Rohit R.
    • Affiliation: College of Arts and Sciences, Department of Computer Science
Abstract
  • To tackle the problem of segmenting several closely-spaced objects from 3D medical images, I propose a hybrid of two segmentation approaches: one image-based and one model-based. A major contribution takes the image-based approach by diffeomorphically mapping a fully segmented atlas image to a partially segmented target patient image preserving any `correspondence' inferred from the partial segmentation of the target. The mapping is produced by solving the steady-state heat flow equation where the temperature is a coordinate vector and corresponding points have the same temperature. Objects carried over from the atlas into the target serve as reasonable initial segmentations and can be further refined by a model-based segmentation method. Good quality segmentations are added to the list of the initial partial segmentations, and the process is repeated. Another contribution takes the model-based approach in developing shape models of quasi-tubular objects and statistics on those models. Whereas medial models were previously only developed for slab-shaped objects, this contribution provides an approximately medial method to stably represent nearly tubular objects. I test my method on segmenting objects from 3D Computed Tomography (CT) scans of the head and neck obtained for radiotherapy treatment planning.
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  • In Copyright
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  • "... in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Computer Science."
Advisor
  • Pizer, Stephen M.
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Place of publication
  • Chapel Hill, NC
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  • Open access
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