Alignment of contrast enhanced medical images

The re-alignment of series of medical images in which there are multiple contrast variations is difficult. The reason for this is that the popularmeasures of image similarity used to drive the alignment procedure do not separate the influence of intensity variation due to image feature motion and in...

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Main Author: Melbourne, A.
Published: University College London (University of London) 2009
Subjects:
610
Online Access:http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.564601
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spelling ndltd-bl.uk-oai-ethos.bl.uk-5646012015-12-03T03:27:57ZAlignment of contrast enhanced medical imagesMelbourne, A.2009The re-alignment of series of medical images in which there are multiple contrast variations is difficult. The reason for this is that the popularmeasures of image similarity used to drive the alignment procedure do not separate the influence of intensity variation due to image feature motion and intensity variation due to feature enhancement. In particular, the appearance of new structure poses problems when it has no representation in the original image. The acquisition of many images over time, such as in dynamic contrast enhanced MRI, requires that many images with different contrast be registered to the same coordinate system, compounding the problem. This thesis addresses these issues, beginning by presenting conditions under which conventional registration fails and proposing a solution in the form of a ’progressive principal component registration’. The algorithm uses a statistical analysis of a series of contrast varying images in order to reduce the influence of contrast-enhancement that would otherwise distort the calculation of the image similarity measures used in image registration. The algorithm is shown to be versatile in that it may be applied to series of images in which contrast variation is due to either temporal contrast enhancement changes, as in dynamic contrast-enhanced MRI or intrinsically in the image selection procedure as in diffusion weighted MRI.610University College London (University of London)http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.564601http://discovery.ucl.ac.uk/15846/Electronic Thesis or Dissertation
collection NDLTD
sources NDLTD
topic 610
spellingShingle 610
Melbourne, A.
Alignment of contrast enhanced medical images
description The re-alignment of series of medical images in which there are multiple contrast variations is difficult. The reason for this is that the popularmeasures of image similarity used to drive the alignment procedure do not separate the influence of intensity variation due to image feature motion and intensity variation due to feature enhancement. In particular, the appearance of new structure poses problems when it has no representation in the original image. The acquisition of many images over time, such as in dynamic contrast enhanced MRI, requires that many images with different contrast be registered to the same coordinate system, compounding the problem. This thesis addresses these issues, beginning by presenting conditions under which conventional registration fails and proposing a solution in the form of a ’progressive principal component registration’. The algorithm uses a statistical analysis of a series of contrast varying images in order to reduce the influence of contrast-enhancement that would otherwise distort the calculation of the image similarity measures used in image registration. The algorithm is shown to be versatile in that it may be applied to series of images in which contrast variation is due to either temporal contrast enhancement changes, as in dynamic contrast-enhanced MRI or intrinsically in the image selection procedure as in diffusion weighted MRI.
author Melbourne, A.
author_facet Melbourne, A.
author_sort Melbourne, A.
title Alignment of contrast enhanced medical images
title_short Alignment of contrast enhanced medical images
title_full Alignment of contrast enhanced medical images
title_fullStr Alignment of contrast enhanced medical images
title_full_unstemmed Alignment of contrast enhanced medical images
title_sort alignment of contrast enhanced medical images
publisher University College London (University of London)
publishDate 2009
url http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.564601
work_keys_str_mv AT melbournea alignmentofcontrastenhancedmedicalimages
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