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H Benali

Publications and source records attributed to H Benali.

At least 19 recordsLinked to original sources
PubMed2002

Estimating the effective degrees of freedom in univariate multiple regression analysis.

The general linear model provides the most widely applied statistical framework for analyzing functional MRI (fMRI) data. With the increasing temporal resolution of recent scanning protocols, and more elaborate data preprocessing schemes, data independency is no longer a valid assumption. In this paper, we revise the statistical background of the general linear model in the presence of temporal autocorrelations. First, when detecting the activation signal, we explicitly account for the temporal autocorrelation structure, which yields a generalized F-test and the associated corrected (or effective) degrees of freedom (DOF). The proposed approach is data driven and thus independent of any specific preprocessing method. Then, for event-related protocols, we propose a new model for the temporal autocorrelations ("damped oscillator" model) and compare this model to another, previously used in the field (first-order autoregressive model, or AR(1) model). In the case of long fMRI time series, an efficient approximation for the number of effective DOF is provided for both models. Finally, the validity of our approach is assessed using simulated and real fMRI data and is compared with more conventional methods.

Analysis of Variance↗
PubMed2000

Should scatter be corrected in both transmission and emission data for accurate quantitation in cardiac SPET?

Ideally, reliable quantitation in single-photon emission tomography (SPET) requires both emission and transmission data to be scatter free. Although scatter in emission data has been extensively studied, it is not well known how scatter in transmission data affects relative and absolute quantitation in reconstructed images. We studied SPET quantitative accuracy for different amounts of scatter in emission and transmission data using a Utah phantom and a cardiac Data Spectrum phantom including different attenuating media. Acquisitions over 180 degrees were considered and three projection sets were derived: 20% images and Jaszczak and triple-energy-window scatter-corrected projections. Transmission data were acquired using gadolinium-153 line sources in a 90-110 keV window using a narrow or wide scanning window. The transmission scans were performed either simultaneously with the emission acquisition or 24 h later. Transmission maps were reconstructed using filtered backprojection and mu values were linearly scaled from 100 to 140 keV. Attenuation-corrected images were reconstructed using a conjugate gradient minimal residual algorithm. The mu value underestimation varied between 4% with a narrow transmission window in soft tissue and 22% with a wide window in a material simulating bone. Scatter in the emission and transmission data had little effect on the uniformity of activity distribution in the left ventricle wall and in a uniformly hot compartment of the Utah phantom. Correcting the transmission data for scatter had no impact on contrast between a hot and a cold region or on signal-to-noise ratio (SNR) in regions with uniform activity distribution, while correcting the emission data for scatter improved contrast and reduced SNR. For absolute quantitation, the most accurate results (bias <4% in both phantoms) were obtained when reducing scatter in both emission and transmission data. In conclusion, trying to obtain the same amount of scatter in emission and transmission data, in addition to being impractical because of the difficulty in knowing the precise scatter components, did not yield such accurate absolute activity quantitation as when emission and transmission scatter were reduced.

Heart↗
PubMed2000

Relative impact of scatter, collimator response, attenuation, and finite spatial resolution corrections in cardiac SPECT.

UNLABELLED: We determined the relative effect of corrections for scatter, depth-dependent collimator response, attenuation, and finite spatial resolution on various image characteristics in cardiac SPECT. METHODS: Monte Carlo simulations and real acquisition of a 99mTc cardiac phantom were performed under comparable conditions. Simulated and acquired data were reconstructed using several correction schemes that combined different methods for scatter correction (3 methods), depth-dependent collimator response correction (frequency-distance principle), attenuation correction (nonuniform Chang correction or within an iterative reconstruction algorithm), and finite spatial resolution correction (use of recovery coefficients). Five criteia were considered to assess the effect of the processing schemes: bull's-eye map (BEM) uniformity, contrast between the left ventricle (LV) wall and the LV cavity, spatial resolution, signal-to-noise ratio (SNR), and percent errors with respect to the known LV wall and liver activities. RESULTS: Similar results were obtained for the simulated and acquired data. Scatter correction significantly improved contrast and absolute quantitation but did not have noticeable effects on BEM uniformity or on spatial resolution and reduced the SNR. Correction for the depth-dependent collimator response improved spatial resolution from 13.3 to 9.5 mm in the LV region, improved absolute quantitation and contrast, but reduced the SNR. Correcting for attenuation was essential for restoring BEM uniformity (78% and 89% without and with attenuation correction, respectively [ideal value being 100%]) and accurate absolute activity quantitation (errors in estimated LV wall and liver activity decreased from 90% without attenuation correction to approximately20% with attenuation correction only). Although accurate absolute activity quantitation was achieved in the liver using scatter and attenuation corrections only, correction for finite spatial resolution was needed to estimate LV wall activity within 10%. CONCLUSION: The respective effects of corrections for scatter, depth-dependent collimator response, attenuation, and finite spatial resolution on different image features in cardiac SPECT were quantified for a specific acquisition configuration. These results give indications regarding the improvements to be expected when using a specific processing scheme involving some or all corrections.

Heart↗
PubMed1999

Respective roles of scatter, attenuation, depth-dependent collimator response and finite spatial resolution in cardiac single-photon emission tomography quantitation: a Monte Carlo study.

The purpose of this study was to investigate the relative influence of scatter, attenuation, depth-dependent collimator response and finite spatial resolution upon the image characteristics in cardiac single-photon emission tomography (SPET). An acquisition of an anthropomorphic cardiac phantom was performed together with corresponding SPET Monte Carlo simulations. The cardiac phantom and the Monte Carlo simulations were designed so that the effect of scatter, attenuation, depth-dependent collimator response and finite spatial resolution could be studied individually and in combination. The impact of each physical effect and of combinations of effects was studied in terms of absolute and relative quantitative accuracy, spatial resolution and signal-to-noise ratio (SNR) in the resulting images. No corrections for these effects were assessed. Results obtained from Monte Carlo simulations and real acquisitions were in excellent agreement. Attenuation introduced about 90% activity underestimation in a 10-mm-thick left ventricle wall while finite spatial resolution alone introduced about 30% activity underestimation. Scatter had a negligible impact on quantitative accuracy in the recontructed slices when attenuation was present. Neither bull's eye map homogeneity nor contrast between a hot and a cold region were affected by depth-dependent collimator response or finite spatial resolution. Bull's eye map homogeneity was severely affected by attenuation but not by scatter. Attenuation and scatter reduced contrast by about 20% each. Both attenuation and scatter increased the full-width at half-maximum (FWHM) characterizing the spatial resolution of the imaging system by approximately 1 mm each but the main effect responsible for the observed 11-mm FWHM spatial resolution was the depth-dependent collimator response. SNR was reduced by a factor of approximately 2.5 because of attenuation, while scattered counts increased SNR by approximately 10%. In conclusion, the quantification of the relative influence of the different physical effects showed that attenuation is definitely the major phenomenon affecting cardiac SPET imaging accuracy, but that finite spatial resolution, scatter and depth-dependent collimator response also contribute significantly to the errors in absolute and relative quantitation and to the poor spatial resolution.

Computer Simulation↗
PubMed1999

A spline-regularized minimal residual algorithm for iterative attenuation correction in SPECT.

In SPECT, regularization is necessary to avoid divergence of the iterative algorithms used for non uniform attenuation compensation. In this paper, we propose a spline-based regularization method for the minimal residual algorithm. First, the acquisition noise is filtered using a statistical model involving spline smoothing so that the filtered projections belong to a Sobolev space with specific continuity and derivability properties. Then, during the iterative reconstruction procedure, the continuity of the inverse Radon transform between Sobolev spaces is used to design a spline-regularized filtered backprojection method, by which the known regularity properties of the projections determine those of the corresponding reconstructed slices. This ensures that the activity distributions estimated at each iteration present regularity properties, which avoids computational noise amplification, thus stabilizing the iterative process. Analytical and Monte Carlo simulations are used to show that the proposed spline-regularized minimal residual algorithm converges to a satisfactory stable solution in terms of restored activity and homogeneity, using at most 25 iterations, whereas the non regularized version of the algorithm diverges. Choosing the number of iterations is therefore no longer a critical issue for this reconstruction procedure.

Algorithms↗
PubMed1999

Experimental comparison of data transformation procedures for analysis of principal components.

Results of principal component analysis depend on data scaling. Recently, based on theoretical considerations, several data transformation procedures have been suggested in order to improve the performance of principal component analysis of image data with respect to the optimum separation of signal and noise. The aim of this study was to test some of those suggestions, and to compare several procedures for data transformation in analysis of principal components experimentally. The experiment was performed with simulated data and the performance of individual procedures was compared using the non-parametric Friedman's test. The optimum scaling found was that which unifies the variance of noise in the observed images. In data with a Poisson distribution, the optimum scaling was the norm used in correspondence analysis. Scaling mainly affected the definition of the signal space. Once the dimension of the signal space was known, the differences in error of data and signal reproduction were small. The choice of data transformation depends on the amount of available prior knowledge (level of noise in individual images, number of components, etc), on the type of noise distribution (Gaussian, uniform, Poisson, other), and on the purpose of analysis (data compression, filtration, feature extraction).

Computer Simulation↗
PubMed1998

Two-dimensional statistical model for regularized backprojection in SPECT.

In SPECT, both the noise affecting the data and the discretization of the inverse Radon transform are responsible for the ill-posed nature of the reconstruction. To constrain the problem, we propose a regularized backprojection method (RBP) which takes advantage of the relationships existing between the continuity properties of the projections and those of the reconstructed object. The RBP method involves two stages: first, a statistical model (the fixed-effect model) is used to estimate the noise-free part of the projections. Then, the filtered projections are reconstructed using a backprojection algorithm (spline filtered backprojection) which ensures that the reconstructed object belongs to a space consistent with that containing the projections. The method is illustrated using analytical simulations, and the RBP approach is compared to the conventional filtered backprojection. The effect on the reconstructed slices of the parameters involved in RBP is studied in terms of spatial resolution, homogeneity in uniform regions and quantification. It is shown that appropriate combinations of these parameters yield a better compromise between homogeneity and spatial resolution than conventional FBP, with similar quantification performances.

Algorithms↗
PubMed1998

Statistical distribution of factors and factor images in factor analysis of medical image sequences.

From a time or energy image sequence, factor analysis of medical image sequences (FAMIS) estimates factors, representing kinetics or spectra in a given physiological compartment, and associated factor images, showing the compartments corresponding to each curve. In this paper, we show that the statistical properties of factor images and associated factors can be determined using a well known result from elementary probability theory. Numerical experiments are conducted to demonstrate that the variance observed in factor images can be predicted when the statistical properties of the original data are known. It is shown how these theoretical results can be used to relax the non-negativity constraints during FAMIS oblique analysis and to improve the quantitative interpretation of the factor images by associating a confidence interval with each pixel value.

Biophysical Phenomena↗
PubMed1996

Functional MR imaging of the human sensorimotor cortex during haptic discrimination.

This study attempted to determine whether haptic discriminations of shape (haptic task) activate the same tissue in the central cortical region of normal human subjects as do finger movements (opposition task). Opposition and haptic tasks both activated the central sulcus, as expected from previous imaging studies. The haptic task activated about 50% of the cortical territory activated by the opposition task. The results suggest that exploratory digital movements performed to collect precise somatosensory information and automatic movements performed during finger positioning activate partially overlapping parts of the sensorimotor cortex.

Brain Mapping↗
PubMed1996

Polyhedral microcalcifications on mammograms: prevalence and morphometric analysis.

OBJECTIVE: The purpose of this study was to determine the incidence and the mammographic appearance of polyhedral microcalcifications. MATERIALS AND METHODS: Prospectively, we evaluated screening mammograms in 2000 women for polyhedral microcalcifications. The number of polyhedral microcalcifications on routine and magnification views was established, and a quantitative analysis was done to determine if the shape of the polyhedral microcalcifications varied in the different projections. The ratio between the longer axis (R) and the shorter axis (r) was calculated. RESULTS: Two radiologists detected at least two polyhedral microcalcifications on one projection in 58 (3%) women. The number of polyhedral microcalcifications detected ranged from 2 to 47 (mean, 8.2) for screening mammograms and from 2 to 62 (mean, 13.4) on magnification views. Polyhedral microcalcifications were bilateral in 22 cases, scattered in one breast in 19 cases, segmental in 10 cases, and grouped in a cluster in seven cases. Lateral projections showed more rhombohedral microcalcifications, and craniocaudal projections showed more square microcalcifications. CONCLUSION: The frequency of polyhedral microcalcifications is 3%. The shape of polyhedral microcalcifications varies: craniocaudal views show them to be square and lateral views show them to be rhombohedral.

Breast↗
PubMed1995

A new correction method for gamma camera non-uniformity due to energy response variability.

We present a new uniformity correction (Fourier energy correction) which is designed to correct for gamma camera non-uniformity caused by variations of the energy response function within a wide spectral range. A convolution model is used to describe the spatial distortions of the energy response function. The model is solved in Fourier space. A preliminary flood acquisition is required to obtain energy-dependent Fourier weights which are used to correct subsequent acquisitions. The influence of the parameters involved in the correction procedure is studied and the Fourier energy correction is compared to a conventional multiplicative energy correction for different acquisition geometries. The Fourier energy correction appears especially useful when the energy information associated with each detected photon is analysed using a fine sampling, or when windows different from the photopeak window are used.

Biophysical Phenomena↗
PubMed1995

A fractal approach to the segmentation of microcalcifications in digital mammograms.

This paper presents a computerized method for the automated segmentation of individual microcalcifications in a region of interest (ROI) known to contain a cluster in digital mammograms. Mammographic parenchyma caj be accurately modeled with the fractal approach, but not areas with microcalcifications. The digitized image is divided into 16 x 16-pixel overlapping windows and those accurately modeled by the fractal model are eliminated. The next steps include local thresholding of the ROIs using an iterative method, the elimination of some of the artifacts and identification of the clustered microcalcifications using a clustering algorithm. The evaluation was performed on 81 simulated clusters superimposed on normal mammographic backgrounds and on a representative database of 408 real mammograms. Microcalcification locations were identified by two radiologists independently. These locations were compared to those found by the computer algorithm. An average of 59% of the simulated microcalcifications and 69% of the microcalcifications common to both radiologists were detected. The algorithm described provides a fully automated method for the segmentation of individual microcalcifications in an area of the mammogram known to contain a cluster.

Biopsy↗
PubMed1995

Comparative assessment of nine scatter correction methods based on spectral analysis using Monte Carlo simulations.

UNLABELLED: We compared nine scatter correction methods based on spectral analysis which process SPECT projections. METHODS: Monte Carlo simulation was used to generate histories of photons emitted from a realistic 99mTc phantom. A particular projection was considered. Information regarding the history, location and energy of the photons detected in this projection was analyzed to test the assumptions underlying each scatter correction method. Relative and absolute quantification and signal-to-noise ratio were assessed for each scatter corrected image. RESULTS: For the simulated data, two methods do not enable activity quantification. Among the methods requiring some parameters to be calibrated, the dual-energy window method shows the best compromise between accuracy and ease of implementation but introduces a bias in relative quantification. In this respect, a triple-energy window technique is more accurate than the dual-window method. A factor analysis approach results in more stable quantitative accuracy (error approximately 10%) for a wide range of activity but requires a more sophisticated acquisition mode (30 energy windows). CONCLUSION: These results show that a scatter correction method using spectral analysis can be used to substantially improve accurate quantification.

Humans↗
PubMed1994

A comparative study of scatter correction methods for scintigraphic images.

Phantom studies have demonstrated that factor analysis of medical image sequences using target apex-seeking (FAMIS-TAS) applied to spectral scintigraphic image sequences is an efficient adaptive scatter correction method. We assessed the improvement in quality of clinical images using FAMIS-TAS as compared with two other scatter correction techniques: conventional 20% photopeak window (PW) and scatter window subtraction (SWS). Thirty normal technetium-99m hydroxymethylene diphosphonate bone scans were processed. Bone to soft tissue contrasts and signal-to-noise and contrast-to-noise ratios were measured. The overall image quality was evaluated using an observer testing questionnaire submitted to four physicians. Quantitative parameters showed that FAMIS-TAS images displayed the best bone to soft tissue contrasts and contrast-to-noise ratios, but the lowest signal-to-noise ratios. PW images presented the lowest contrasts and contrast-to-noise ratios, and the highest signal-to-noise ratios. SWS gave intermediate results. According to the observer testing results, PW images showed the lowest bone to soft tissue contrasts and the highest signal-to-noise ratios. FAMIS-TAS images showed the lowest signal-to-noise ratios. The images processed by the three methods displayed the same anatomical information.

Adolescent↗
PubMed1994

Scatter correction in scintigraphy: the state of the art.

In scintigraphy, the detection of scattered photons degrades both visual image analysis and quantitative accuracy. Many methods have been proposed and are still under investigation to cope with scattered photons. The main features of the problem of scattering in radionuclide imaging are presented first, to provide a sound foundation for a critical review of the existing scatter correction techniques. These are described using a classification relating to their aims and principles. Their theoretical potentials are analysed, as well as the difficulties of their practical implementation. Finally, the problems of their evaluation and comparison are discussed.

Humans↗
PubMed1994

A simulation model of clustered breast microcalcifications.

A simulation model of clustered microcalcifications superimposed on normal mammographic backgrounds has been developed and evaluated. A cluster is described according to its size, the number of microcalcifications it contains, and their density. A microcalcification is defined on the basis of its size, shape, location within the cluster, its contrast, and the distribution of the gray-level values between pixels that belong to it. Gray-level parameters are dependent on the surrounding tissue, which is also slightly modified. The main dependencies between the parameters are taken into account. All the parameters are randomly sampled using distribution laws determined from the statistical analysis of 408 real clusters containing a total of 8611 microcalcifications. Some statistical characteristics depend on the structural mammographic pattern on which the cluster is superimposed. The evaluation of the simulation model, performed by two radiologists on a test set of 100 real and simulated clusters, did not reveal any statistically significant difference between the simulated clusters and the real ones. This method provides clusters of microcalcifications with well-defined characteristics and can be used to evaluate the accuracy of computerized detection methods.

Biophysical Phenomena↗