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A Boudraa

Publications and source records attributed to A Boudraa.

6 recordsLinked to original sources
PubMed2002

Fuzzy clustering-based segmented attenuation correction in whole-body PET imaging.

Segmented attenuation correction is now a widely accepted technique to reduce noise propagation from transmission scanning in positron emission tomography (PET). In this paper, we present a new method for segmenting transmission images in whole-body scanning. This reduces the noise in the correction maps while still correcting for differing attenuation coefficients of specific tissues. Based on the fuzzy C-means (FCM) algorithm, the method segments the PET transmission images into a given number of clusters to extract specific areas of differing attenuation such as air, the lungs and soft tissue, preceded by a median filtering procedure. The reconstructed transmission image voxels are, therefore, segmented into populations of uniform attenuation based on knowledge of the human anatomy. The clustering procedure starts with an overspecified number of clusters followed by a merging process to group clusters with similar properties (redundant clusters) and removal of some undesired substructures using anatomical knowledge. The method is unsupervised, adaptive and allows the classification of both pre- or post-injection transmission images obtained using either coincident 68Ge or single-photon 137Cs sources into main tissue components in terms of attenuation coefficients. A high-quality transmission image of the scanner bed is obtained from a high statistics scan and added to the transmission image. The segmented transmission images are then forward projected to generate attenuation correction factors to be used for the reconstruction of the corresponding emission scan. The technique has been tested on a chest phantom simulating the lungs, heart cavity and the spine, the Rando-Alderson phantom, and whole-body clinical PET studies showing a remarkable improvement in image quality, a clear reduction of noise propagation from transmission into emission data allowing for reduction of transmission scan duration. There was very good correlation (R2 = 0.96) between maximum standardized uptake values (SUVs) in lung nodules measured on images reconstructed with measured and segmented attenuation correction with a statistically significant decrease in SUV (17.03% +/- 8.4%, P < 0.01) on the latter images, whereas no proof of statistically significant differences on the average SUVs was observed. Finally, the potential of the FCM algorithm as a segmentation method and its limitations as well as other prospective applications of the technique are discussed.

Algorithms↗
PubMed2001

Neuro-fuzzy systems for computer-aided myocardial viability assessment.

This paper describes a multimodality framework for computer-aided myocardial viability assessment based on neuro-fuzzy techniques. The proposed approach distinguishes two main levels: the modality-independent inference level and the modality-dependent application level. This two-level distinction releases the hard constraint of multimodality image registration. An abstract description template is used to describe the different myocardial functions (contractile function, perfusion, metabolism). Parameters extracted from different image modalities are combined to derive a diagnostic image. The neuro-fuzzy techniques make our system transparent, adaptive and easily extendable. Its effectiveness and robustness are demonstrated in a positron emission tomography/magnetic resonance imaging data fusion application.

Artificial Intelligence↗
PubMed2001

Regional differences and metabolic changes in normal aging of the human brain: proton MR spectroscopic imaging study.

BACKGROUND AND PURPOSE: Aging is recognized to originate from a diversity of mechanisms that blur the limits between normal and pathologic processes. The purpose of this study was to determine the early effect of normal aging on the regional distribution of brain metabolite concentrations, including N-acetylaspartate (NAA), a major neuronal marker, choline (Cho), and creatine (Cr). METHODS: Thirty-two healthy participants, ages 21 to 61 years, were examined by proton MR spectroscopic (1H MRS) imaging. 1H MRS imaging acquisitions were performed in two brain locations: the centrum semiovale and the temporal lobe. Thirty voxels were selected in four cerebral regions, cortical, semioval, temporal, and hippocampal, and 1H MR spectra were processed to determine the metabolite ratios. RESULTS: With advancing age of the participants, the ratios of %NAA, NAA:Cho, and NAA:Cr were significantly decreased, whereas the ratios of %Cho and %Cr were significantly increased in the cortical, semioval, and temporal regions. On the basis of the significant metabolic difference determined by cluster analysis, two groups of 16 participants with ages ranging from 21 to 39 years (younger group) and 40 to 61 years (older group) were compared. Repeated measures analysis of variance tests, with multiple comparison procedures between the two age groups and among the four brain region groups, showed significant decreases of the %NAA, NAA:Cho, and NAA:Cr ratios in the semioval and temporal regions of the older group compared with the younger group. When compared with other cerebral regions, %NAA and %Cho ratios were significantly decreased in the hippocampal and cortical regions, respectively. CONCLUSION: These metabolic changes suggest that brain aging is characterized by a reduction in neuronal viability or function associated with an accelerated membrane degradation and/or an increase in glial cell numbers.

Adult↗
PubMedDate not supplied

Myocardium extraction in positron emission tomography based on soft computing.

This paper presents an efficient and accurate approach to myocardium extraction in Positron Emission Tomography (PET) images based on a careful application of soft computing techniques. PET images present a noisy background, making the automatic myocardium extraction and uptake quantification a difficult task. In this work a Self Organized Radial Basis Function Network (SRBFN) is designed to focus on the myocardium in an iterative process until the total extraction of the myocardium from the noisy background is achieved. Fuzzy sets and fuzziness measures are used to compute the error of the network. The method was tested on a set of nine images of different patients and its effectiveness is illustrated in two patients showing tracer uptake defects.

Fluorodeoxyglucose F18↗
PubMedDate not supplied

A pyramidal approach for automatic segmentation of multiple sclerosis lesions in brain MRI.

Quantitative assessment of Magnetic Resonance Imaging (MRI) lesion load of patients with multiple sclerosis (MS) is the most objective approach for a better understanding of the history of the pathology, either natural or modified by therapies. To achieve an accurate and reproducible quantification of MS lesions in conventional brain MRI, an automatic segmentation algorithm based on a multiresolution approach using pyramidal data structures is proposed. The systematic pyramidal decomposition in the frequency domain provides a robust and flexible low level tool for MR image analysis. Context-dependent rules regarding MRI findings in MS are used as high level considerations for automatic lesion detection.

Algorithms↗