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Proceedings Paper

Localization of perfusion abnormalities in brain SPECT imaging (Honorable Mention Poster Award)
Author(s): Elise Nguyen; Jean Meunier; Jean-Paul Soucy; Luc Boucher; Louis Laflamme
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Paper Abstract

SPECT (Single Photon Emission Computed Tomography) imagery has become widely available and is particularly useful for regional cerebral blood flow (rCBF) studies. Distribution of rCBF is still essentially studied by visual observation, searching for abnormalities, and comparing with other studies. In order to facilitate the localization of these abnormalities, we propose a simple, automatic and direct method to register a SPECT rCBF study with a commonly used atlas in the neurological community, the Talairach Atlas. The Talairach atlas still gives today the most extensive information of regions of interests, coupled with a coordinate system. The proposed method will therefore allow a physician to precisely navigate in a SPECT image by interpreting the abnormalities coordinates. The registration of these two volumes is carried out in two steps, a rough alignment followed by an elastic registration. The rough alignment step consists in computing the mass centroid of each volume and in scaling the volumes accordingly if necessary. A simple threshold method (30% of the maximum intensity of the SPECT image) is used to determine the volume of the brain being studied. In order to facilitate the fine registration, the Talairach atlas was previously segmented in three classes: cerebrospinal fluid (CSF), white and gray matters. Then, an automatic intensity transformation as well as a low-pass filtering is performed to closely resemble the spatial resolution and intensities of the SPECT volume. This intensity transformation is a simple method which combines the use of a joint 2D histogram of the segmented atlas and the individual volume as well as a clustering algorithm. The fine registration is then computed with an optical flow methodology. The effectiveness of this scheme was tested on a database of virtual patients, simulated from a database of 45 healthy and diseased brains. The rate of pixels misclassification in each class within a one pixel neighborhood (CSF 0.5%; white matter 1.37%, gray matter 2.80%) indicates that this proposed method will be useful for the nuclear physician in helping localize abnormalities.

Paper Details

Date Published: 29 April 2005
PDF: 8 pages
Proc. SPIE 5747, Medical Imaging 2005: Image Processing, (29 April 2005); doi: 10.1117/12.595972
Show Author Affiliations
Elise Nguyen, Univ. of Montreal (Canada)
Jean Meunier, Univ. of Montreal (Canada)
Jean-Paul Soucy, Univ. Hospital, Univ. of Montreal (Canada)
Luc Boucher, Univ. Hospital, Univ. of Montreal (Canada)
Louis Laflamme, Univ. Hospital, Univ. of Montreal (Canada)


Published in SPIE Proceedings Vol. 5747:
Medical Imaging 2005: Image Processing
J. Michael Fitzpatrick; Joseph M. Reinhardt, Editor(s)

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