A Volume of Interest (VOI) Atlas for the Analysis of Neurophysiological Image Data

S. Marrett; A. C. Evans; L. Collins; T. M. Peters

doi:10.1117/12.953288

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25 May 1989 A Volume of Interest (VOI) Atlas for the Analysis of Neurophysiological Image Data

S. Marrett, A. C. Evans, L. Collins, T. M. Peters

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Proceedings Volume 1092, Medical Imaging III: Image Processing; (1989) https://doi.org/10.1117/12.953288
Event: Medical Imaging III, 1989, Newport Beach, CA, United States

Abstract

Accurate and precise neuroanatomical descriptions are essential for the meaningful quantification of Positron Emission Tomographic (PET) images of the human brain. This task is difficult since the radio-tracer distribution imaged by PET does not neccessarily reflect structure. A two-dimensional brain atlas that features the use of a deformable Region-of-Interest (ROI) template has previously been shown to be an effective method for integrating anatomical (Magnetic Resonance Imaging - MRI) images and physiological (PET) data, with an observed reduction in the coefficient of variation amongst observers from 8.1% to 3.4% 1. This method has been adopted for routine MRI image correlation and PET image analysis at our centre. The atlas is most effective when used in studies in which PET and MRI images are acquired in planes parallel to those of the original brain atlas. To allow arbitrary image/atlas orientation, we have implemented a Volume of Interest (VOI) atlas that extends the ROI methodology to three dimensions. The major advantage is that, given adequate axial sampling, arbitrary orientations of PET and MRI scans can be matched to the VOI atlas with no loss in structural recovery. In addition, the VOI atlas can be employed in the quantification of metabolic parameters directly from volumetric PET studies rather than performing the analysis on a slice by slice basis.

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S. Marrett, A. C. Evans, L. Collins, and T. M. Peters "A Volume of Interest (VOI) Atlas for the Analysis of Neurophysiological Image Data", Proc. SPIE 1092, Medical Imaging III: Image Processing, (25 May 1989); https://doi.org/10.1117/12.953288

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