Literature DB >> 17664578

Evaluating an optical-flow-based registration algorithm for contrast-enhanced magnetic resonance imaging of the breast.

A L Martel1, M S Froh, K K Brock, D B Plewes, D C Barber.   

Abstract

Dynamic contrast-enhanced magnetic resonance imaging studies of the breast are frequently degraded by patient motion. In order to correct for this, any registration algorithm must overcome two major challenges: the highly deformable nature of the breast itself and the need to remove changes in signal intensity due to patient motion whilst leaving potentially significant changes in signal intensity due to changes in contrast agent concentration unchanged. In this paper, we evaluate the use of a non-rigid registration method that uses optical flow equations to drive the displacement of a grid of control points. With conventional optical flow techniques it is assumed that changes in image intensity are solely due to motion, making it unsuitable for use with contrast-enhanced studies. The registration algorithm evaluated in this paper overcomes this problem by including an additional term to account for changes in image intensity. Studies simulating physiologically plausible deformations of the breast together with realistic changes in contrast-enhancement derived from patient studies demonstrate that the algorithm is capable of registering images to sub-voxel accuracy within minutes. This technique has now been successfully incorporated into a breast cancer screening protocol allowing registered images to be provided routinely to the radiologist immediately after the scanning session.

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Year:  2007        PMID: 17664578     DOI: 10.1088/0031-9155/52/13/010

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  12 in total

1.  A vector machine formulation with application to the computer-aided diagnosis of breast cancer from DCE-MRI screening examinations.

Authors:  Jacob E D Levman; Ellen Warner; Petrina Causer; Anne L Martel
Journal:  J Digit Imaging       Date:  2014-02       Impact factor: 4.056

2.  Feature selection in computer-aided breast cancer diagnosis via dynamic contrast-enhanced magnetic resonance images.

Authors:  Megan Rakoczy; Donald McGaughey; Michael J Korenberg; Jacob Levman; Anne L Martel
Journal:  J Digit Imaging       Date:  2013-04       Impact factor: 4.056

3.  A Metric for Reducing False Positives in the Computer-Aided Detection of Breast Cancer from Dynamic Contrast-Enhanced Magnetic Resonance Imaging Based Screening Examinations of High-Risk Women.

Authors:  Jacob E D Levman; Cristina Gallego-Ortiz; Ellen Warner; Petrina Causer; Anne L Martel
Journal:  J Digit Imaging       Date:  2016-02       Impact factor: 4.056

4.  Semi-automatic region-of-interest segmentation based computer-aided diagnosis of mass lesions from dynamic contrast-enhanced magnetic resonance imaging based breast cancer screening.

Authors:  Jacob Levman; Ellen Warner; Petrina Causer; Anne Martel
Journal:  J Digit Imaging       Date:  2014-10       Impact factor: 4.056

5.  Impact of nonrigid motion correction technique on pixel-wise pharmacokinetic analysis of free-breathing pulmonary dynamic contrast-enhanced MR imaging.

Authors:  Junichi Tokuda; Hatsuho Mamata; Ritu R Gill; Nobuhiko Hata; Ron Kikinis; Robert F Padera; Robert E Lenkinski; David J Sugarbaker; Hiroto Hatabu
Journal:  J Magn Reson Imaging       Date:  2011-04       Impact factor: 4.813

6.  Deformable registration for quantifying longitudinal tumor changes during neoadjuvant chemotherapy.

Authors:  Yangming Ou; Susan P Weinstein; Emily F Conant; Sarah Englander; Xiao Da; Bilwaj Gaonkar; Meng-Kang Hsieh; Mark Rosen; Angela DeMichele; Christos Davatzikos; Despina Kontos
Journal:  Magn Reson Med       Date:  2014-07-15       Impact factor: 4.668

7.  Clinical application of pharmacokinetic analysis as a biomarker of solitary pulmonary nodules: dynamic contrast-enhanced MR imaging.

Authors:  Hatsuho Mamata; Junichi Tokuda; Ritu R Gill; Robert F Padera; Robert E Lenkinski; David J Sugarbaker; James P Butler; Hiroto Hatabu
Journal:  Magn Reson Med       Date:  2012-01-09       Impact factor: 4.668

8.  Image registration for quantitative parametric response mapping of cancer treatment response.

Authors:  Jennifer L Boes; Benjamin A Hoff; Nola Hylton; Martin D Pickles; Lindsay W Turnbull; Anne F Schott; Alnawaz Rehemtulla; Ryan Chamberlain; Benjamin Lemasson; Thomas L Chenevert; Craig J Galbán; Charles R Meyer; Brian D Ross
Journal:  Transl Oncol       Date:  2014-02-01       Impact factor: 4.243

9.  Effect of the enhancement threshold on the computer-aided detection of breast cancer using MRI.

Authors:  Jacob E D Levman; Petrina Causer; Ellen Warner; Anne L Martel
Journal:  Acad Radiol       Date:  2009-06-09       Impact factor: 3.173

10.  The Effect of Registration on Voxel-Wise Tofts Model Parameters and Uncertainties from DCE-MRI of Early-Stage Breast Cancer Patients Using 3DSlicer.

Authors:  Matthew Mouawad; Heather Biernaski; Muriel Brackstone; Michael Lock; Anat Kornecki; Olga Shmuilovich; Ilanit Ben-Nachum; Frank S Prato; R Terry Thompson; Stewart Gaede; Neil Gelman
Journal:  J Digit Imaging       Date:  2020-08-03       Impact factor: 4.056

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