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Measuring brain atrophy with a generalized formulation of the boundary shift integral.

Prados F, Cardoso MJ, Leung KK, Cash DM, Modat M, Fox NC, Wheeler-Kingshott CA, Ourselin S, Alzheimer's Disease Neuroimaging Initiati - Neurobiol. Aging (2014)

Bottom Line: Brain atrophy measured using structural magnetic resonance imaging (MRI) has been widely used as an imaging biomarker for disease diagnosis and tracking of pathologic progression in neurodegenerative diseases.In this work, we present a generalized and extended formulation of the boundary shift integral (gBSI) using probabilistic segmentations to estimate anatomic changes between 2 time points.This method adaptively estimates a non-binary exclusive OR region of interest from probabilistic brain segmentations of the baseline and repeat scans to better localize and capture the brain atrophy.

View Article: PubMed Central - PubMed

Affiliation: Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK; NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, London, UK. Electronic address: f.carrasco@ucl.ac.uk.

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Extra N3 correction. (A) Initial scan with the template-12-dof mask overlaid. (B) Corrected scan. (C) Subtraction between initial scan and corrected scan.
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fig2: Extra N3 correction. (A) Initial scan with the template-12-dof mask overlaid. (B) Corrected scan. (C) Subtraction between initial scan and corrected scan.

Mentions: An overview of the whole pipeline is shown in Fig. 1. An extra preprocessing step for intensity inhomogeneity correction was applied to the ADNI scans using a robust version of the N3 algorithm, as proposed in Boyes et al. (2008), see Fig. 2. The preprocessed scans were independently segmented using a segmentation propagation and fusion method, which provided probabilistic masks for each image. The next step was a symmetric and inverse-consistent registration to the middle space of the 2 time-point images using 12 degrees of freedom (DOF) registration (Modat et al., 2014). A symmetric differential bias correction (DBC) was then applied to both registered images to reduce the residual bias field between them. Finally, the atrophy was calculated using the proposed generalized BSI method, denoted as gBSI.


Measuring brain atrophy with a generalized formulation of the boundary shift integral.

Prados F, Cardoso MJ, Leung KK, Cash DM, Modat M, Fox NC, Wheeler-Kingshott CA, Ourselin S, Alzheimer's Disease Neuroimaging Initiati - Neurobiol. Aging (2014)

Extra N3 correction. (A) Initial scan with the template-12-dof mask overlaid. (B) Corrected scan. (C) Subtraction between initial scan and corrected scan.
© Copyright Policy - CC BY
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4288791&req=5

fig2: Extra N3 correction. (A) Initial scan with the template-12-dof mask overlaid. (B) Corrected scan. (C) Subtraction between initial scan and corrected scan.
Mentions: An overview of the whole pipeline is shown in Fig. 1. An extra preprocessing step for intensity inhomogeneity correction was applied to the ADNI scans using a robust version of the N3 algorithm, as proposed in Boyes et al. (2008), see Fig. 2. The preprocessed scans were independently segmented using a segmentation propagation and fusion method, which provided probabilistic masks for each image. The next step was a symmetric and inverse-consistent registration to the middle space of the 2 time-point images using 12 degrees of freedom (DOF) registration (Modat et al., 2014). A symmetric differential bias correction (DBC) was then applied to both registered images to reduce the residual bias field between them. Finally, the atrophy was calculated using the proposed generalized BSI method, denoted as gBSI.

Bottom Line: Brain atrophy measured using structural magnetic resonance imaging (MRI) has been widely used as an imaging biomarker for disease diagnosis and tracking of pathologic progression in neurodegenerative diseases.In this work, we present a generalized and extended formulation of the boundary shift integral (gBSI) using probabilistic segmentations to estimate anatomic changes between 2 time points.This method adaptively estimates a non-binary exclusive OR region of interest from probabilistic brain segmentations of the baseline and repeat scans to better localize and capture the brain atrophy.

View Article: PubMed Central - PubMed

Affiliation: Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK; NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, London, UK. Electronic address: f.carrasco@ucl.ac.uk.

Show MeSH
Related in: MedlinePlus