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Proceedings Paper

Likelihood estimation in image warping
Author(s): Alexei Manso Correa Machado; Mario F.M. Campos; James C. Gee
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Paper Abstract

The problem of matching two images can be posed as the search for a displacement field which assigns each point of one image to a point in the second image in such a way that a likelihood function is maximized ruled by topological constraints. Since the images may be acquired by different scanners, the intensity relationship between intensity levels is generally unknown. The matching problem is usually solved iteratively by optimization methods. The evaluation of each candidate solution is based on an objective function which favors smooth displacements that yield likely intensity matches. This paper is concerned with the construction of a likelihood function that is derived from the information contained in the data and is thus applicable to data acquired from an arbitrary scanner. The basic assumption of the method is that the pair of images to be matched is assumed to contain roughly the same proportion of tissues, which will be reflected in their gray-level histograms. Experiments with MRI images corrupted with strong non-linear intensity shading show the method's effectiveness for modeling intensity artifacts. Image matching can thus be made robust to a wide range of intensity degradations.

Paper Details

Date Published: 21 May 1999
PDF: 11 pages
Proc. SPIE 3661, Medical Imaging 1999: Image Processing, (21 May 1999); doi: 10.1117/12.348615
Show Author Affiliations
Alexei Manso Correa Machado, Federal Univ of Minas Gerais and Pontifical Catholic Univ. of Minas Gerais (Brazil)
Mario F.M. Campos, Federal Univ. of Minas Gerais (Brazil)
James C. Gee, Univ. of Pennsylvania (United States)


Published in SPIE Proceedings Vol. 3661:
Medical Imaging 1999: Image Processing
Kenneth M. Hanson, Editor(s)

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