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Proceedings Paper

Detection of pulmonary perfusion patterns in patients with pulmonary embolism by ultrafast CT
Author(s): Christopher J. Wolfkiel
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Paper Abstract

This report outlines a method of automatically segmenting pulmonary perfusion regions from ultrafast CT data. Segmenting was performed by a k-means clustering of unenhanced, maximal enhancement and both parameters. Time density curves from distinct regions were generated and perfusion determined. In two example subjects with pulmonary embolism hypoperfused regions were identified. In a normal subject slight gravity related gradient hypoperfusion was also detected. These preliminary results suggest that automated segmentation of UFCT pulmonary perfusion scans is possible and could greatly improve the clinical utility of the scanning technology.

Paper Details

Date Published: 24 May 1995
PDF: 9 pages
Proc. SPIE 2433, Medical Imaging 1995: Physiology and Function from Multidimensional Images, (24 May 1995); doi: 10.1117/12.209710
Show Author Affiliations
Christopher J. Wolfkiel, Univ. of Illinois/Chicago (United States)


Published in SPIE Proceedings Vol. 2433:
Medical Imaging 1995: Physiology and Function from Multidimensional Images
Eric A. Hoffman, Editor(s)

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