Conference proceeding
Development of a novel constellation based landmark detection algorithm
Progress in Biomedical Optics and Imaging - Proceedings of SPIE, Vol.8669, pp.86693F-86693F-6
03/13/2013
DOI: 10.1117/12.2006471
Abstract
Anatomical landmarks such as the anterior commissure (AC) and posterior commissure (PC) are commonly used by
researchers for co-registration of images. In this paper, we present a novel, automated approach for landmark detection
that combines morphometric constraining and statistical shape models to provide accurate estimation of landmark points.
This method is made robust to large rotations in initial head orientation by extracting extra information of the eye centers
using a radial Hough transform and exploiting the centroid of head mass (CM) using a novel estimation approach. To
evaluate the effectiveness of this method, the algorithm is trained on a set of 20 images with manually selected
landmarks, and a test dataset is used to compare the automatically detected against the manually detected landmark
locations of the AC, PC, midbrain-pons junction (MPJ), and fourth ventricle notch (VN4). The results show that the
proposed method is accurate as the average error between the automatically and manually labeled landmark points is less
than 1 mm. Also, the algorithm is highly robust as it was successfully run on a large dataset that included different kinds
of images with various orientation, spacing, and origin.
Details
- Title: Subtitle
- Development of a novel constellation based landmark detection algorithm
- Creators
- Ali Ghayoor - The Univ. of Iowa (United States)Jatin G Vaidya - The Univ. of Iowa (United States)Hans J Johnson - The Univ. of Iowa (United States)
- Contributors
- Sebastien Ourselin (Editor) - Univ. College London (United Kingdom)David R Haynor (Editor) - Univ. of Washington (United States)
- Resource Type
- Conference proceeding
- Publication Details
- Progress in Biomedical Optics and Imaging - Proceedings of SPIE, Vol.8669, pp.86693F-86693F-6
- Publisher
- SPIE
- DOI
- 10.1117/12.2006471
- ISSN
- 1605-7422
- Language
- English
- Date published
- 03/13/2013
- Academic Unit
- Psychiatry; Iowa Neuroscience Institute; University College Courses; Electrical and Computer Engineering; Roy J. Carver Department of Biomedical Engineering; The Iowa Institute for Biomedical Imaging; The Iowa Initiative for Artificial Intelligence; Iowa Informatics Initiative
- Record Identifier
- 9984070708302771
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