A Binary Entropy Measure to Assess Nonrigid Registration Algorithms

Topics:
Healthcare Services
Tags:
Algorithm,
Engineering,
Harvard College,
President
Source:
President and Fellows of Harvard College

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Overview: Assessment of normal and abnormal anatomical variability requires a coordinate system enabling inter-subject comparison. This paper presents a binary minimum entropy criterion to assess affine and nonrigid transformations bringing a group of subject scans into alignment. This measure is a data-driven measure allowing the identification of an intrinsic coordinate system of a particular group of subjects. The paper also informs about two statistical atlases derived from magnetic resonance imaging of newborn infants with gestational age ranging from 24 to 40 weeks.

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Format: PDF | Size: 126KB | Date: Dec 2001 | Pages: 9

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