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Proceedings Paper

Super-resolution reconstruction for tongue MR images
Author(s): Jonghye Woo; Ying Bai; Snehashis Roy; Emi Z. Murano; Maureen Stone; Jerry L. Prince
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Paper Abstract

Magnetic resonance (MR) images of the tongue have been used in both clinical medicine and scientific research to reveal tongue structure and motion. In order to see different features of the tongue and its relation to the vocal tract it is beneficial to acquire three orthogonal image stacks-e.g., axial, sagittal and coronal volumes. In order to maintain both low noise and high visual detail, each set of images is typically acquired with in-plane resolution that is much better than the through-plane resolution. As a result, any one data set, by itself, is not ideal for automatic volumetric analyses such as segmentation and registration or even for visualization when oblique slices are required. This paper presents a method of super-resolution reconstruction of the tongue that generates an isotropic image volume using the three orthogonal image stacks. The method uses preprocessing steps that include intensity matching and registration and a data combination approach carried out by Markov random field optimization. The performance of the proposed method was demonstrated on five clinical datasets, yielding superior results when compared with conventional reconstruction methods.

Paper Details

Date Published: 14 February 2012
PDF: 8 pages
Proc. SPIE 8314, Medical Imaging 2012: Image Processing, 83140C (14 February 2012); doi: 10.1117/12.911445
Show Author Affiliations
Jonghye Woo, Univ. of Maryland, Baltimore (United States)
The Johns Hopkins Univ. (United States)
Ying Bai, HeartFlow, Inc. (United States)
Snehashis Roy, The Johns Hopkins Univ. (United States)
Emi Z. Murano, The Johns Hopkins Univ. (United States)
Maureen Stone, Univ. of Maryland, Baltimore (United States)
Jerry L. Prince, The Johns Hopkins Univ. (United States)

Published in SPIE Proceedings Vol. 8314:
Medical Imaging 2012: Image Processing
David R. Haynor; Sébastien Ourselin, Editor(s)

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