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M Defrise

Publications and source records attributed to M Defrise.

At least 19 recordsLinked to original sources

Fast fully 3-D image reconstruction in PET using planograms.

We present a method of performing fast and accurate three-dimensional (3-D) backprojection using only Fourier transform operations for line-integral data acquired by planar detector arrays in positron emission tomography. This approach is a 3-D extension of the two-dimensional (2-D) linogram technique of Edholm. By using a special choice of parameters to index a line of response (LOR) for a pair of planar detectors, rather than the conventional parameters used to index a LOR for a circular tomograph, all the LORs passing through a point in the field of view (FOV) lie on a 2-D plane in the four-dimensional (4-D) data space. Thus, backprojection of all the LORs passing through a point in the FOV corresponds to integration of a 2-D plane through the 4-D "planogram." The key step is that the integration along a set of parallel 2-D planes through the planogram, that is, backprojection of a plane of points, can be replaced by a 2-D section through the origin of the 4-D Fourier transform of the data. Backprojection can be performed as a sequence of Fourier transform operations, for faster implementation. In addition, we derive the central-section theorem for planogram format data, and also derive a reconstruction filter for both backprojection-filtering and filtered-backprojection reconstruction algorithms. With software-based Fourier transform calculations we provide preliminary comparisons of planogram backprojection to standard 3-D backprojection and demonstrate a reduction in computation time by a factor of approximately 15.

Algorithms↗

HeinzelCluster: accelerated reconstruction for FORE and OSEM3D.

Using iterative three-dimensional (3D) reconstruction techniques for reconstruction of positron emission tomography (PET) is not feasible on most single-processor machines due to the excessive computing time needed, especially so for the large sinogram sizes of our high-resolution research tomograph (HRRT). In our first approach to speed up reconstruction time we transform the 3D scan into the format of a two-dimensional (2D) scan with sinograms that can be reconstructed independently using Fourier rebinning (FORE) and a fast 2D reconstruction method. On our dedicated reconstruction cluster (seven four-processor systems, Intel PIII@700 MHz, switched fast ethernet and Myrinet, Windows NT Server), we process these 2D sinograms in parallel. We have achieved a speedup > 23 using 26 processors and also compared results for different communication methods (RPC, Syngo, Myrinet GM). The other approach is to parallelize OSEM3D (implementation of C Michel), which has produced the best results for HRRT data so far and is more suitable for an adequate treatment of the sinogram gaps that result from the detector geometry of the HRRT. We have implemented two levels of parallelization for four dedicated cluster (a shared memory fine-grain level on each node utilizing all four processors and a coarse-grain level allowing for 15 nodes) reducing the time for one core iteration from over 7 h to about 35 min.

Algorithms↗

180 degree pinhole SPET with a tilted detector and OS-EM reconstruction: phantom studies and potential clinical applications.

This study investigated the feasibility of ordered subsets expectation maximisation (OS-EM) reconstruction of pinhole single-photon emission tomography (SPET) acquired with a tilted detector head and a 180 degrees orbit. Phantom and patient data were recorded using a standard single-head camera. Reconstructions were performed using a dedicated OS-EM algorithm. Reconstructed images of line, uniformity and Picker's thyroid phantoms showed that the geometry, physical size and uniformity of the radioactive objects were preserved. For the range of radius corresponding to the patient studies, the measured full-widths at half-maximum lay between 4.90+/-0.25 mm and 6.05+/-0.25 mm. Finally, the gain in resolution associated with the use of the pinhole collimator instead of a parallel-hole collimator was highlighted in a parathyroid exploration and in a shoulder bone study.

Aged↗

Efficient cardiac diffusion tensor MRI by three-dimensional reconstruction of solenoidal tensor fields.

Tensor tomography is being investigated as a technique for reconstruction of in vivo diffusion tensor fields that can potentially be used to reduce the number of magnetic resonance imaging (MRI) measurements. Specifically, assessments are being made of the reconstruction of cardiac diffusion tensor fields from 3D Radon planar projections using a filtered backprojection algorithm in order to specify the helical fiber structure of myocardial tissue. Helmholtz type decomposition is proposed for 3D second order tensor fields. Using this decomposition a Fourier projection theorem is formulated in terms of the solenoidal and irrotational components of the tensor field. From the Fourier projection theorem, two sets of Radon directional measurements, one that reconstructs the solenoidal component and one that reconstructs the irrotational component of the tensor field, are prescribed. Based on these observations filtered backprojection reconstruction formulae are given for the reconstruction of a 3D second order tensor field and its solenoidal and irrotational components from Radon projection measurements. Computer simulations demonstrate the validity of the mathematical formulations and demonstrate that a realistic model of the helical fiber structure of the myocardial tissue specifies a diffusion tensor field for which the first principal vector (the vector associated with the maximum eigenvalue) of the solenoidal component accurately approximates the first principal vector of the diffusion tensor. A priori knowledge of this allows the orientation of the myocardial fiber structure to be specified utilizing one half of the number of MRI measurements of a normal diffusion tensor field study.

Computer Simulation↗

Rebinning-based algorithms for helical cone-beam CT.

Several image reconstruction algorithms based on rebinning have been proposed recently for helical cone-beam CT. These algorithms separate the 3D reconstruction into a set of independent 2D reconstructions for a set of surfaces: planar or non-planar surfaces are defined and then reconstructed using 2D filtered backprojection from a 2D fan-beam or parallel-beam set of data estimated from the cone-beam (CB) measurements. The first part of this paper presents a unified derivation of rebinning algorithms for planar and non-planar surfaces. An integral equation is derived for the surface allowing the best rebinning and an iterative algorithm converging to the solution of that equation is given. The second part presents an efficient method to correct the residual reconstruction artefacts observed with rebinning algorithms when the cone-angle is too large for the required accuracy. This correction algorithm involves a CB backprojection and the reconstruction time is slightly longer than for the zero-boundary (ZB) method.

Algorithms↗

Comparison of 3-D reconstruction with 3D-OSEM and with FORE+OSEM for PET.

The combination of Fourier rebinning (FORE) and the ordered subsets expectation-maximization (OSEM), a fast statistical algorithm, appears as a promising alternative to the fully three-dimensional (3-D) iterative approach for clinical positron emission tomography (PET) data. In this paper, we evaluated the properties of FORE+OSEM and compared it with fully 3-D OSEM using both simulations and data acquired by commercial scanners. The aim is to determine to what extent the speed advantage of FORE+OSEM is paid for by a possible degradation of image quality in the case of noisy clinical PET data. A forward- and back-projection pair based on a line integral model was used in two-dimensional OSEM and 3-D OSEM (3D-OSEM) instead of a system matrix. Different variants of both approaches have been studied with simulations in terms of contrast-noise tradeoff. Two variants--FORE+OSEM with attenuation weighting (AW) [FORE+OSEM(AW)] and 3D-OSEM with attenuation-normalization weighting (ANSP) and a shifted-Poisson (SP) model [3D-OSEM(ANSP)]--were compared with measured phantom data and patient data. Based on the results from both simulations and measured data, we conclude that: 1) both attenuation (-normalization) weighting and the SP model improve the image quality but slow down the convergence and 2) despite its approximate nature, FORE+OSEM does not show apparent image degradation compared with 3D-OSEM for data with a noise level typical of a whole-body FDG scan.

Algorithms↗

Automatic determination of left ventricular ejection fraction from gated blood-pool tomography.

UNLABELLED: The aim of this study was to develop and validate a new algorithm to automatically compute left ventricular ejection fraction (LVEF) from gated blood-pool tomography (GBPT). The results were compared with those of conventional planar radionuclide angiocardiography (PRNA). METHODS: Fifty-three consecutive patients received an injection of 740 MBq (99m)Tc-labeled human serum albumin. PRNA and GBPT were performed consecutively in a random sequence. PRNA served as the reference, and GBPT images were processed using a new edge detection algorithm. The algorithm is fast (<45 s), fully automatic, and works in three-dimensional space. The method includes identification of the valve plane and the septum. The left ventricular cavity at end-diastole is delineated by segmentation using an iterative threshold technique. An optimal threshold is reached when the corresponding isocontour best fits the first derivative of the end-diastolic count distribution in three dimensions. This optimal threshold is then applied to delineate the left ventricular cavity on the other time bins. The data are corrected for the partial-volume effect. Left ventricular volumes are determined using a geometry-based method and are used to calculate the ejection fraction. RESULTS: The success rate of the new algorithm was 94%. LVEFs calculated from GBPT agreed well with those calculated from PRNA (r = 0.78; GBPT = 0.94 PRNA + 6.33). The systematic error was 2.8%, and the random error was 8.8%. Excellent inter- and intraobserver reproducibility was found, with average differences of 1.1% +/- 4.6% and 1.1% +/- 5.0%, respectively, between the two measurements. CONCLUSION: This new algorithm provides a fast, automated, and objective method to calculate LVEF from GBPT.

Adult↗

Interest of the ordered subsets expectation maximization (OS-EM) algorithm in pinhole single-photon emission tomography reconstruction: a phantom study.

Pinhole single-photon emission tomography (SPET) has been proposed to improve the trade-off between sensitivity and resolution for small organs located in close proximity to the pinhole aperture. This technique is hampered by artefacts in the non-central slices. These artefacts are caused by truncation and by the fact that the pinhole SPET data collected in a circular orbit do not contain sufficient information for exact reconstruction. The ordered subsets expectation maximization (OS-EM) algorithm is a potential solution to these problems. In this study a three-dimensional OS-EM algorithm was implemented for data acquired on a single-head gamma camera equipped with a pinhole collimator (PH OS-EM). The aim of this study was to compare the PH OS-EM algorithm with the filtered back-projection algorithm of Feldkamp, Davis and Kress (FDK) and with the conventional parallel-hole geometry as a whole, using a line source phantom, Picker's thyroid phantom and a phantom mimicking the human cervical column. Correction for the angular dependency of the sensitivity in the pinhole geometry was based on a uniform flood acquisition. The projection data were shifted according to the measured centre of rotation. No correction was made for attenuation, scatter or distance-dependent camera resolution. The resolution measured with the line source phantom showed a significant improvement with PH OS-EM as compared with FDK, especially in the axial direction. Using Picker's thyroid phantom, one iteration with eight subsets was sufficient to obtain images with similar noise levels in uniform regions of interest to those obtained with the FDK algorithm. With these parameters the reconstruction time was 2.5 times longer than for the FDK method. Furthermore, there was a reduction in the artefacts caused by the circular orbit SPET acquisition. The images obtained from the phantom mimicking the human cervical column indicated that the improvement in image quality with PH OS-EM is relevant for future clinical use and that the improvements obtained using the OS-EM algorithm are more significant for the pinhole geometry than for the conventional parallel-hole geometry. We conclude that PH OS-EM is a practical and promising alternative for pinhole SPET reconstruction.

Algorithms↗

A solution to the long-object problem in helical cone-beam tomography.

This paper presents a new algorithm for the long-object problem in helical cone-beam (CB) computerized tomography (CT). This problem consists in reconstructing a region-of-interest (ROI) bounded by two given transaxial slices, using axially truncated CB projections corresponding to a helix segment long enough to cover the ROI, but not long enough to cover the whole axial extent of the object. The new algorithm is based on a previously published method, referred to as CB-FBP (Kudo et al 1998 Phys. Med. Biol. 43 2885-909), which is suitable for quasi-exact reconstruction when the helix extends well beyond the support of the object. We first show that the CB-FBP algorithm simplifies dramatically, and furthermore constitutes a solution to the long-object problem, when the object under study has line integrals which vanish along all PI-lines. (A PI line is a line which connects two points of the helix separated by less than one pitch.) Exploiting a geometric property of the helix, we then show how the image can be expressed as the sum of two images, where the first image can be reconstructed from the measured CB projections by a simple backprojection procedure, and the second image has zero PI-line integrals and hence can be reconstructed using the simplified CB-FBP algorithm. The resulting method is a quasi-exact solution to the long-object problem, called the ZB method. We present its implementation and illustrate its performance using simulated CB data of the 3D Shepp phantom and of a more challenging head-like phantom.

Algorithms↗

Quasi-exact filtered backprojection algorithm for long-object problem in helical cone-beam tomography.

Exact reconstruction from axially truncated cone-beam projections acquired with a helical vertex path is a challenging problem for which solutions are currently under investigation by some researchers. This paper deals with a difficult class of this problem called the long-object problem. Its purpose is to reconstruct a central region of interest (ROI) of a long object when the helical path extends only a little bit above and below the ROI. By extending the authors' recent approach based on the triangular decomposition of the Grangeat formula, we derive quasi-exact reconstruction algorithms whose overall structure is of filtered backprojection (FBP) style. Unlike the previous similar approaches to the long-object problem, the proposed FBP algorithms do not require additional two circular scans at the ends of the helical path. Furthermore, the algorithms require a significantly smaller detector area and achieve improved image quality even for a large pitch compared with the approximate Feldkamp algorithms. One drawback of the proposed algorithms is the computational time, which is much longer than for the Feldkamp algorithms. We show some simulation results to demonstrate the performances of the proposed algorithms.

Algorithms↗

Attenuation correction in whole-body FDG oncological studies: the role of statistical reconstruction.

Whole-body fluorine-18 fluoro-2-d-deoxyglucose positron emission tomography (FDG-PET) is widely used in clinical centres for diagnosis, staging and therapy monitoring in oncology. Images are usually not corrected for attenuation since filtered backprojection (FBP) reconstruction methods require a 10 to 15-min transmission scan per bed position on most current PET devices equipped with germanium-68 rod transmission sources. Such an acquisition protocol would increase the total scanning time beyond acceptable limits. The aim of this work is to validate the use of iterative reconstruction methods, on both transmission and emission scans, in order to obtain a fully corrected whole-body study within a reasonable scanning time of 60 min. Five minute emission and 3-min transmission scans are acquired at each of the seven bed positions. The transmission data are reconstructed with OSEM (ordered subsets expectation maximization) and the last iteration is reprojected to obtain consistent attenuation correction factors (ACFs). The emission image is then also reconstructed with OSEM, using the emission scan corrected for normalization, scatter and decay together with the set of consistent ACFs as inputs. The total processing time is about 35 min, which is acceptable in a clinical environment. The image quality, readability and accuracy of uptake quantification were assessed in 38 patients scanned for various malignancies. The sensitivity for tumour detection was the same for the non-attenuation-corrected (NAC-FBP) and the attenuation-corrected (AC-OSEM) images. The AC-OSEM images were less noisy and easier to interpret. The interobserver reproducibility was significantly increased when compared with non-corrected images (96.1% vs 81.1%, P<0.01). Standardized uptake values (SUVs) measured on images reconstructed with OSEM (AC-OSEM) and filtered backprojection (AC-FBP) were similar in all body regions except in the pelvic area, where SUVs were higher on AC-FBP images (mean increase 7.74%, P<0. 01). Our results show that, when statistical reconstruction is applied to both transmission and emission data, high quality quantitative whole-body images are obtained within a reasonable scanning (60 min) and processing time, making it applicable in clinical practice.

Adult↗

Single-slice rebinning method for helical cone-beam CT.

In this paper, we present reconstruction results from helical cone-beam CT data, obtained using a simple and fast algorithm, which we call the CB-SSRB algorithm. This algorithm combines the single-slice rebinning method of PET imaging with the weighting schemes of spiral CT algorithms. The reconstruction is approximate but can be performed using 2D multislice fan-beam filtered backprojection. The quality of the results is surprisingly good, and far exceeds what one might expect, even when the pitch of the helix is large. In particular, with this algorithm comparable quality is obtained using helical cone-beam data with a normalized pitch of 10 to that obtained using standard spiral CT reconstruction with a normalized pitch of 2.

Algorithms↗

Exact rebinning methods for three-dimensional PET.

The high computational cost of data processing in volume PET imaging is still hindering the routine application of this successful technique, especially in the case of dynamic studies. This paper describes two new algorithms based on an exact rebinning equation, which can be applied to accelerate the processing of three-dimensional (3-D) PET data. The first algorithm, FOREPROJ, is a fast-forward projection algorithm that allows calculation of the 3-D attenuation correction factors (ACF's) directly from a two-dimensional (2-D) transmission scan, without first reconstructing the attenuation map and then performing a 3-D forward projection. The use of FOREPROJ speeds up the estimation of the 3-D ACF's by more than a factor five. The second algorithm, FOREX, is a rebinning algorithm that is also more than five times faster, compared to the standard reprojection algorithm (3DRP) and does not suffer from the image distortions generated by the even faster approximate Fourier rebinning (FORE) method at large axial apertures. However, FOREX is probably not required by most existing scanners, as the axial apertures are not large enough to show improvements over FORE with clinical data. Both algorithms have been implemented and applied to data simulated for a scanner with a large axial aperture (30 degrees), and also to data acquired with the ECAT HR and the ECAT HR+ scanners. Results demonstrate the excellent accuracy achieved by these algorithms and the important speedup when the sinogram sizes are powers of two.

Algorithms↗

Cone-beam filtered-backprojection algorithm for truncated helical data.

This paper investigates 3D image reconstruction from truncated cone-beam (CB) projections acquired with a helical vertex path. First, we show that a rigorous derivation of Grangeat's formula for truncated projections leads to a small additional term compared with previously published similar formulations. This correction term is called the boundary term. Next, this result is used to develop a CB filtered-backprojection (FBP) algorithm for truncated helical projections. This new algorithm only requires the CB projections to be measured within the region that is bounded, in the detector, by the projections of the upper and lower turns of the helix. Finally, simulations with mathematical phantoms demonstrate that: (i) the boundary term is necessary to obtain high-quality imaging of low-contrast structures and (ii) good image quality is obtained even with large values of the pitch of the helix.

Algorithms↗

Iterative reconstruction for helical CT: a simulation study.

Iterative reconstruction algorithms for helical CT are presented. The algorithms are derived from two-dimensional reconstruction algorithms, by adapting the projector/backprojector to the helical orbit of the source, and by constraining the axial frequencies with a Gaussian sieve. Simulations have been carried out and the performance of the iterative algorithms is compared to that of filtered backprojection of synthetic (interpolated) two-dimensional sinograms. The iterative algorithms produce superior bias-noise curves. Axial resolution is superior, but disturbing edge-artefacts are introduced.

Algorithms↗

Exact and approximate rebinning algorithms for 3-D PET data.

This paper presents two new rebinning algorithms for the reconstruction of three-dimensional (3-D) positron emission tomography (PET) data. A rebinning algorithm is one that first sorts the 3-D data into an ordinary two-dimensional (2-D) data set containing one sinogram for each transaxial slice to be reconstructed; the 3-D image is then recovered by applying to each slice a 2-D reconstruction method such as filtered-backprojection. This approach allows a significant speedup of 3-D reconstruction, which is particularly useful for applications involving dynamic acquisitions or whole-body imaging. The first new algorithm is obtained by discretizing an exact analytical inversion formula. The second algorithm, called the Fourier rebinning algorithm (FORE), is approximate but allows an efficient implementation based on taking 2-D Fourier transforms of the data. This second algorithm was implemented and applied to data acquired with the new generation of PET systems and also to simulated data for a scanner with an 18 degrees axial aperture. The reconstructed images were compared to those obtained with the 3-D reprojection algorithm (3DRP) which is the standard "exact" 3-D filtered-backprojection method. Results demonstrate that FORE provides a reliable alternative to 3DRP, while at the same time achieving an order of magnitude reduction in processing time.

Algorithms↗

Optimal collimator choice for sequential iodine-123 and technetium-99m imaging.

Dual-isotope studies with technetium-99m and iodine-123 may be useful for various organs, including brain and myocardium. For the images obtained with each of the tracers to be comparable, it is important that activity ratios (activity in one part of the image/reference activity in the image) are preserved by the imaging method. We have used a Rollo phantom to study how collimator response affects such ratios. All investigations were performed with 123I(p,5n) and on a Siemens Orbiter 3700 camera fitted with either a low-energy high-resolution (LEHR) or a medium-energy (ME) collimator. Images were made of a Rollo phantom filled with an aqueous solution of either 99Tc or 123I, and placed on the collimator surface with 8 cm of methyl-methacrylate interposed. Count densities were measured in ROIs drawn in each cell of the phantom, and normalised to the maximal ROI value in the image. The mean square error (MSE) was used to assess how well the ratios of count densities approximated the known activity ratios based on the dimensions of the cells of the phantom. For 99mTc, regardless of the collimator used, the count density ratios approximated the activity ratios fairly well (LEHR: MSE=0.008; ME: MSE=0.020). For 123I, count density ratios obtained with the LEHR were consistently higher than activity ratios (MSE=0. 235), whereas the differences between the measured and the theoretical values were less with the ME collimator (MSE=0.013). Contrast fidelity of the 123I images obtained with the LEHR collimator could be improved with Jaszczak scatter correction with k=1, but this led to unfavourable signal-to-noise ratios. For sequential 99mTc/123I studies with extended sources, ME is to be preferred because of its higher contrast accuracy. Spatial resolution is less for the ME than for the LEHR collimator (FWHM with scatter: LEHR/99mTc=6.9 mm, LEHR/123I=7.4 mm, ME/99mTc= 10.1 mm, ME/123I=11.1 mm), but remains similar for both tracers when the ME is used.

Gamma Cameras↗