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Proceedings Paper

An intensity-based approach to x-ray mammography: MRI registration
Author(s): Thomy Mertzanidou; John H. Hipwell; Christine Tanner; David J. Hawkes
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Paper Abstract

This paper presents a novel approach to X-ray mammography - MRI registration. The proposed method uses an intensity-based technique and an affine transformation matrix to approximate the 3D deformation of the breast resulting from the compression applied during mammogram acquisition. The registration is driven by a similarity measure that is calculated at each iteration of the algorithm between the target X-ray mammogram and a simulated X-ray image, created from the MR volume. Although the similarity measure is calculated in 2D, we compute a 3D transformation that is updated at each iteration. We have performed two types of experiments. In the first set, we used simulated X-ray target data, for which the ground truth deformation of the volume was known and thus the results could be validated. For this case, we examined the performance of 4 different similarity measures and we show that Normalized Cross Correlation and Gradient Difference perform best. The calculated mean reprojection error was for both similarity measures 4mm, for an initial misregistration of 14mm. In the second set of experiments, we present the initial results of registering real X-ray mammograms with MR volumes. The results indicate that the breast boundaries were registered well and the volume was deformed in 3D in a similar way to the deformation of the breast during X-ray mammogram acquisition. The experiments were carried out on five patients.

Paper Details

Date Published: 12 March 2010
PDF: 8 pages
Proc. SPIE 7623, Medical Imaging 2010: Image Processing, 76232Z (12 March 2010); doi: 10.1117/12.843988
Show Author Affiliations
Thomy Mertzanidou, Univ. College London (United Kingdom)
John H. Hipwell, Univ. College London (United Kingdom)
Christine Tanner, ETH Zürich (Switzerland)
David J. Hawkes, Univ. College London (United Kingdom)


Published in SPIE Proceedings Vol. 7623:
Medical Imaging 2010: Image Processing
Benoit M. Dawant; David R. Haynor, Editor(s)

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