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Proceedings Paper

Evaluating the registration of multiparamater images
Author(s): Ronald M. Pickett; Haim Levkowitz; David L. Gonthier
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Paper Abstract

The great challenge in analyzing multiparameter images is to detect and analyze the patterns formed by the parameters in combination, and this requires that the images be in close registration. If they are misaligned non-linearly, as is often the case, particularly in medical diagnostic imaging, registration is a very difficult problem. In this paper we discuss various approaches to the assessment and correction of misregistrations among multiparameter images. We propose a technique that assess misregistrations using correlation computation and visualizes them using color and arrow displays. We demonstrate the technique with a medical case of CT and MR images; our technique shows misregistrations between images that were previously assumed to be in registration. The proposed technique provides a great potential for driving improved registration procedures, particularly in finding and correcting nonlinear effects.

Paper Details

Date Published: 8 September 1993
PDF: 8 pages
Proc. SPIE 1913, Human Vision, Visual Processing, and Digital Display IV, (8 September 1993); doi: 10.1117/12.152731
Show Author Affiliations
Ronald M. Pickett, Univ. of Massachusetts/Lowell (United States)
Haim Levkowitz, Univ. of Massachusetts/Lowell (United States)
David L. Gonthier, Univ. of Massachusetts/Lowell (United States)

Published in SPIE Proceedings Vol. 1913:
Human Vision, Visual Processing, and Digital Display IV
Jan P. Allebach; Bernice E. Rogowitz, Editor(s)

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