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Proceedings Paper

Detection and correction of geometric distortion in 3D MR images
Author(s): Marcel M. Breeuwer; Mark Holden; Waldemar Zylka
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Paper Abstract

Three-dimensional magnetic resonance medical images may contain scanner- and patient-induced geometric distortion. For qualitative diagnosis, geometric errors of a few millimeters are often tolerated. However, quantitative applications such as image-guided neurosurgery and radiotherapy can require an accuracy of a millimeter or better. We have developed a method to accurately measure scanner-induced geometric distortion and to correct the MR images for this type of distortion. The method involves a number of steps. First, a specially designed phantom is scanned that contains a large number of reference structures on positions with a manufacturing error of less than 0.05 mm. Next, the positions of the reference structures are automatically detected in the scanned images and a higher-order polynomial distortion-correction transformation is estimated. Then the patient is scanned and the transformation is applied to correct the patient images for the detected distortion. The distortion-correction method is explained in detail in this paper. The accuracy of the method has been measured with synthetically generated phantom scans that contain an exactly-known amount and type of distortion. The reproducibility of the method has been measured by applying it to a series of consecutive phantom scans. Validation results are briefly described in this paper, a more-detailed description is given in another submission to SPIE Medical Imaging 2001.

Paper Details

Date Published: 3 July 2001
PDF: 11 pages
Proc. SPIE 4322, Medical Imaging 2001: Image Processing, (3 July 2001); doi: 10.1117/12.430986
Show Author Affiliations
Marcel M. Breeuwer, Philips Medical Systems (Netherlands)
Mark Holden, The Guy's, King's and St. Thomas' School of Medicine (United Kingdom)
Waldemar Zylka, Univ. of Applied Sciences (Germany)


Published in SPIE Proceedings Vol. 4322:
Medical Imaging 2001: Image Processing
Milan Sonka; Kenneth M. Hanson, Editor(s)

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