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Proceedings Paper

Fast pseudo-CT synthesis from MRI T1-weighted images using a patch-based approach
Author(s): A. Torrado-Carvajal; E. Alcain; A. S. Montemayor; J. L. Herraiz; Y. Rozenholc; J. A. Hernandez-Tamames; E. Adalsteinsson; L. L. Wald; N. Malpica
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Paper Abstract

MRI-based bone segmentation is a challenging task because bone tissue and air both present low signal intensity on MR images, making it difficult to accurately delimit the bone boundaries. However, estimating bone from MRI images may allow decreasing patient ionization by removing the need of patient-specific CT acquisition in several applications. In this work, we propose a fast GPU-based pseudo-CT generation from a patient-specific MRI T1-weighted image using a group-wise patch-based approach and a limited MRI and CT atlas dictionary. For every voxel in the input MR image, we compute the similarity of the patch containing that voxel with the patches of all MR images in the database, which lie in a certain anatomical neighborhood. The pseudo-CT is obtained as a local weighted linear combination of the CT values of the corresponding patches. The algorithm was implemented in a GPU. The use of patch-based techniques allows a fast and accurate estimation of the pseudo-CT from MR T1-weighted images, with a similar accuracy as the patient-specific CT. The experimental normalized cross correlation reaches 0.9324±0.0048 for an atlas with 10 datasets. The high NCC values indicate how our method can accurately approximate the patient-specific CT. The GPU implementation led to a substantial decrease in computational time making the approach suitable for real applications.

Paper Details

Date Published: 22 December 2015
PDF: 7 pages
Proc. SPIE 9681, 11th International Symposium on Medical Information Processing and Analysis, 968106 (22 December 2015); doi: 10.1117/12.2210963
Show Author Affiliations
A. Torrado-Carvajal, Univ. Rey Juan Carlos (Spain)
Madrid-MIT M+Vision Consortium (Spain)
E. Alcain, Univ. Rey Juan Carlos (Spain)
A. S. Montemayor, Univ. Rey Juan Carlos (Spain)
J. L. Herraiz, Madrid-MIT M+Vision Consortium (Spain)
Massachusetts Institute of Technology (United States)
Y. Rozenholc, MAP5, CNRS, Univ. Paris Descartes (France)
J. A. Hernandez-Tamames, Univ. Rey Juan Carlos (Spain)
Madrid-MIT M+Vision Consortium (Spain)
E. Adalsteinsson, Madrid-MIT M+Vision Consortium (Spain)
Massachusetts Institute of Technology (United States)
Harvard-MIT Health Sciences and Technology (United States)
L. L. Wald, Madrid-MIT M+Vision Consortium (Spain)
Harvard-MIT Health Sciences and Technology (United States)
Massachusetts General Hospital (United States)
N. Malpica, Univ. Rey Juan Carlos (Spain)
Madrid-MIT M+Vision Consortium (Spain)


Published in SPIE Proceedings Vol. 9681:
11th International Symposium on Medical Information Processing and Analysis
Eduardo Romero; Natasha Lepore; Juan D. García-Arteaga; Jorge Brieva, Editor(s)

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