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Abstract: . In this paper we describe a statistical model for the observation of labeled points in gated cardiac single photon emission computed tomography (SPECT) images. The model has two major parts: one based on shape correspondence between the image for evaluation and a reference image, and a second based on the match in image features. While the statistical deformation model is applicable to a broad range of image objects, the addition of a contraction mechanism to the baseline model... (Update)
Context of citations to this paper: More
.... having been applied to voxel flow descriptions of shape by Christensen [1997] and Grenander [1994] as well as by McCulloch et al. [Laading 1998] in author Valen Johnson s laboratory. However, our application of hierarchical modeling to the richer medial and boundary...
...among neighbouring probe cells. To motivate the alignment algorithm, which is similar to the facet model described in Laading et al.[4], we refer to Figure 2 where probe cells boundaries are evident by abrupt changes in pixel to pixel intensities near neighbouring probe...
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BibTeX entry: (Update)
Laading, J, C McCulloch, V Johnson, D Gilland and R Jasczak (1998). A hierarchical feature based deformation model applied to 4d cardiac SPECT data. Discussion paper, Duke U. Inst for Statistics & Decisions Scis., www.isds.duke.edu, 98-33. http://citeseer.ist.psu.edu/laading98hierarchical.html More
@article{ laading99hierarchical,
author = "Jacob K. Laading and Colin McCulloch and Valen E. Johnson and David R. Gilland and Ronald J. Jaszczak",
title = "A Hierarchical Feature Based Deformation Model Applied to {$4$D} Cardiac {SPECT} Data",
journal = "Lecture Notes in Computer Science",
volume = "1613",
pages = "266--??",
year = "1999",
url = "citeseer.ist.psu.edu/laading98hierarchical.html" }
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Documents on the same site (http://www.stat.duke.edu/~colin/):
High-Level Image Understanding Via Bayesian Hierarchical Models - McCulloch (1998) (Correct)
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