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Proceedings Paper

Towards the automatic detection of large misregistrations
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Paper Abstract

In many cases three-dimensional anatomical and functional images (SPECT, PET, MRI, CT) ought to be combined to determine the precise nature and extent of lesions in many parts of the body. The images must be adequately aligned prior to any addition, substraction, or any other combination; registration can be done by experienced radiologists via visual inspection, mental reorientation and overlap of slices, or by an automated registration algorithm. To be useful clinically, the latter case requires validation. The human capacity to evaluate registration results visually is limited and the process is time consuming. This paper describes an algorithmic procedure that distinguishes between badly misregistered pairs and those likely to be clinically useful. Our algorithm used brain and/or skin/air contours and a function based on the principal axes of the contour volumes. The results of the present study indicate that the measure based on the combination of brain and skin contours and a principal-axis function is a good first step to reduce the number of badly registered images reaching the clinician.

Paper Details

Date Published: 15 May 2003
PDF: 12 pages
Proc. SPIE 5032, Medical Imaging 2003: Image Processing, (15 May 2003); doi: 10.1117/12.481383
Show Author Affiliations
Claudia E. Rodriguez-Carranza, George Washington Univ. (United States)
Murray H. Loew, George Washington Univ. (United States)

Published in SPIE Proceedings Vol. 5032:
Medical Imaging 2003: Image Processing
Milan Sonka; J. Michael Fitzpatrick, Editor(s)

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