Abstract
A procedure to improve the convergence rate for affine registration methods of medical brain images when the images differ greatly from the template is presented. The methodology is based on a histogram matching of the source images with respect to the reference brain template before proceeding with the affine registration. The preprocessed source brain images are spatially normalized to a template using a general affine model with 12 parameters. A sum of squared differences between the source images and the template is considered as objective function, and a Gauss-Newton optimization algorithm is used to find the minimum of the cost function. Using histogram equalization as a preprocessing step improves the convergence rate in the affine registration algorithm of brain images as we show in this work using SPECT and PET brain images.
Highlights
Emission computed tomography (ECT) has been widely employed in biomedical research and clinical medicine during the last three decades
We choose 50 images labelled by experts as Normal Controls, the results presented here do not change if brain images labelled as late Alzheimer’s disease subjects are chosen
We have shown that this approach can be used in the context of affine registration of brain images, when the intensity values of the reference template differ from the source image which is the case in intermodality image fusion of brain images
Summary
Emission computed tomography (ECT) has been widely employed in biomedical research and clinical medicine during the last three decades. ECT differs fundamentally from many other medical imaging modalities in that it produces a mapping of physiological functions as opposed to imaging anatomical structure. Tomographic radiopharmaceutical imaging, or ECT, provides in vivo three-dimensional maps of a pharmaceutical labeled with a gamma ray emitting radionuclide. Two different image modalities will be used: positron emission tomography (PET) and single photon emission computed tomography (SPECT). Positron emission tomography (PET) is noninvasive, nuclear medicine imaging technique which produces a threedimensional image of functional processes in the body. The system detects pairs of gamma rays emitted indirectly by a positron-emitting radionuclide (tracer), which is introduced into the body on a biologically active molecule. Images of tracer concentration in 3-dimensional space within the brain are reconstructed by computer analysis
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