Wavelet-based methodology for [15O]-H20 PET brain activation assessment

[Abstract] AMI International Conference 2003, September 21-27, Madrid, Spain: "High Resolution Molecular Imaging: from Basic Science to Clinical Applications"Statistical parametric mapping (SPM) is a voxel-byvoxel analysis method commonly used for the detection of brain activation patterns. An alternative approach is the use of multiscale information by means of wavelet analysis. In this study, we have compared the detection of brain activations using conventional SPM and a statistical wavelet analysis in a set of realistic simulated [15O]-H20 positron emission tomography (PET) phantomsPublicad

ROC evaluation of statistical wavelet-based analysis of brain activation in [15O]-H2O PET scans

This paper presents and evaluates a wavelet-based statistical analysis of PET images for the detection of brain activation areas. Brain regions showing significant activations were obtained by performing Student's t tests in the wavelet domain, reconstructing the final image from only those wavelet coefficients that passed the statistical test at a given significance level, and discarding artifacts introduced during the reconstruction process. Using Receiver Operating Characteristic (ROC) curves, we have compared this statistical analysis in the wavelet domain to the conventional image-domain Statistical Parametric Mapping (SPM) method. For obtaining an accurate assessment of sensitivity and specificity, we have simulated realistic single subject [15O]-H2O PET studies with different hyperactivation levels of the thalamic region. The results obtained from an ROC analysis show that the wavelet approach outperforms conventional SPM in identifying brain activation patterns. Using the wavelet method, activation areas detected were closer in size and shape to the region actually activated in the reference image.Publicad

Method for bias field correction of brain T1-weighted magnetic resonance images minimizing segmentation error

This work presents a new algorithm (nonuniform intensity correction; NIC) for correction of intensity inhomogeneities in T1-weighted magnetic resonance (MR) images. The bias field and a bias-free image are obtained through an iterative process that uses brain tissue segmentation. The algorithm was validated by means of realistic phantom images and a set of 24 real images. The first evaluation phase was based on a public domain phantom dataset, used previously to assess bias field correction algorithms. NIC performed similar to previously described methods in removing the bias field from phantom images, without introduction of degradation in the absence of intensity inhomogeneity. The real image dataset was used to compare the performance of this new algorithm to that of other widely used methods (N3, SPM'99, and SPM2). This dataset included both low and high bias field images from two different MR scanners of low (0.5 T) and medium (1.5 T) static fields. Using standard quality criteria for determining the goodness of the different methods, NIC achieved the best results, correcting the images of the real MR dataset, enabling its systematic use in images from both low and medium static field MR scanners. A limitation of our method is that it might fail if the bias field is so high that the initial histogram does not show bimodal distribution for white and gray matterPublicad

Statistical power maps for SPM analysis of PET scans

[Abstract] The 10th International Conference on Functional Mapping of the Human Brain, June 13-17, 2004, Budapest, HungaryThis work presents an alternative method for reporting negative results in statistical parametric maps, consisting in estimating the maximum effect size that the test would not detect as significant with a certain probabilityPublicad

Simultaneous Dual-tracer PET Imaging of the Rat Brain and its Application in the Study of Cerebral Ischemia

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SPM analysis of FDG rat PET scans

[Abstract] AMI Annual Conference 2002, October 23 - 27, San Diego, CaliforniaPublicad

Inhomogeneity correction of magnetic resonance images by minimization of intensity overlapping

Proceeding of: IEEE 2003 International Conference on Image Processing (ICIP), Barcelona, Spain, 14-17 Sept. 2003This work presents a new algorithm (NIC; Non uniform Intensity Correclion) for the correction of intensity inhomogeneities in magnetic resonance images. The algorithm has been validated by means of realistic phantom images and a set of 24 real images. Evaluation using previously proposed phantom images for inhomogeneity correction algorithms allowed us to obtain results fully comparable to the previous literature on the topic. This new algorithm was also compared, using a real image dataset, to other widely used methods which are freely available in the Internet (N3, SPM'99 and SPM2). Standard quality criteria have been used for determining the goodness of the different methods. The new algorithm showed better results removing the intensity inhomogeneities and did not produce degradation when used on images free from this artifact

Detection of rat brain activation using statistical parametric mapping analysis in FDG-PET studies

[Abstract] AMI International Conference 2003, September 21 - 27, Madrid, Spain: High Resolution Molecular Imaging: from Basic Science to Clinical ApplicationsStatistical parametric mapping (SPM) is an analysis technique long been used in clinical research to detect subtle activity changes in brain; it is an excellent exploratory tool as it does not require a priori assumptions about the expected brain region activations. Research in animal imaging may also take benefit from this technique, if properly adapted to the new scenario. This is the case of brain activation studies in murine models using PET tracers and dedicated imaging devices. This work proposes the use of an SPM methodology adapted to the analysis of 2-deoxy-2-[18F] fluoro-D-Glucose (FDG) positron emission tomography (PET) scans of rat brains. Advantages over conventional region of interest (ROI) based analysis were assessed in an experiment addressing the detection of brain activation in of rats which underwent three different visual stimulation paradigmsPublicad

Repeatability of brain tissue volume quantification using magnetic resonance images

[Abstract] The 10th International Conference on Functional Mapping of the Human Brain, June 13-17, 2004, Budapest, HungaryThe aim of this work is to study the repeatability of brain tissue volume quantification achieved by different MRI segmentation methodsPublicad