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Proceedings Paper

Posture-dependent spatial correlation: similarity of multiple CT-derived pulmonary structural and functional parameters
Author(s): Jehangir K. Tajik; Collin L. Olson; Gopal Sundaramoorthy; Eric A. Hoffman
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Paper Abstract

To help characterize the determinants of the spatial distribution of regional pulmonary structure and function and to characterize a spatial autocorrelation (SAC) approach, we have applied SAC statistics to our pulmonary cine x-ray CT data of regional pulmonary blood flow and to various computer derived models (cubes and pyramids, 3-D wedges, and lung shapes in which pure `flow' gradients in either the x, y, or z directions were applied). To generate graphs of correlation vs. distance, we bin the data according to distance into a user specified number of groupings and then autocorrelate the data within each bin. Only regions of pulmonary parenchyma within the same lobe were used. We present the results of our analysis which show that several regional parameters exhibit a similar negative sloping correlation vs. distance relationship. SAC statistics provide a unique tool for demonstrating the existence of underlying patterns to distribution of pulmonary function.

Paper Details

Date Published: 1 May 1994
PDF: 13 pages
Proc. SPIE 2168, Medical Imaging 1994: Physiology and Function from Multidimensional Images, (1 May 1994); doi: 10.1117/12.174412
Show Author Affiliations
Jehangir K. Tajik, Univ. of Iowa College of Medicine (United States)
Collin L. Olson, Univ. of Iowa College of Medicine (United States)
Gopal Sundaramoorthy, Univ. of Iowa College of Medicine (United States)
Eric A. Hoffman, Univ. of Iowa College of Medicine (United States)


Published in SPIE Proceedings Vol. 2168:
Medical Imaging 1994: Physiology and Function from Multidimensional Images
Eric A. Hoffman; Raj S. Acharya, Editor(s)

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