|   | 
Details
   web
Records
Author Cabello, J.; Torres-Espallardo, I.; Gillam, J.E.; Rafecas, M.
Title PET Reconstruction From Truncated Projections Using Total-Variation Regularization for Hadron Therapy Monitoring Type Journal Article
Year 2013 Publication IEEE Transactions on Nuclear Science Abbreviated Journal IEEE Trans. Nucl. Sci.
Volume 60 Issue 5 Pages 3364-3372
Keywords
Abstract Hadron therapy exploits the properties of ion beams to treat tumors by maximizing the dose released to the target and sparing healthy tissue. With hadron beams, the dose distribution shows a relatively low entrance dose which rises sharply at the end of the range, providing the characteristic Bragg peak that drops quickly thereafter. It is of critical importance in order not to damage surrounding healthy tissues and/or avoid targeting underdosage to know where the delivered dose profile ends-the location of the Bragg peak. During hadron therapy, short-lived beta(+)-emitters are produced along the beam path, their distribution being correlated with the delivered dose. Following positron annihilation, two photons are emitted, which can be detected using a positron emission tomography (PET) scanner. The low yield of emitters, their short half-life, and the wash out from the target region make the use of PET, even only a few minutes after hadron irradiation, a challenging application. In-beam PET represents a potential candidate to estimate the distribution of beta(+)-emitters during or immediately after irradiation, at the cost of truncation effects and degraded image quality due to the partial rings required of the PET scanner. Time-of-flight (ToF) information can potentially be used to compensate for truncation effects and to enhance image contrast. However, the highly demanding timing performance required in ToF-PET makes this option costly. Alternatively, the use of maximum-a-posteriori-expectation-maximization (MAP-EM), including total variation (TV) in the cost function, produces images with low noise, while preserving spatial resolution. In this paper, we compare data reconstructed with maximum-likelihood-expectation-maximization (ML-EM) and MAP-EM using TV as prior, and the impact of including ToF information, from data acquired with a complete and a partial-ring PET scanner, of simulated hadron beams interacting with a polymethyl methacrylate (PMMA) target. The results show that MAP-EM, in the absence of ToF information, produces lower noise images and more similar data compared to the simulated beta(+) distributions than ML-EM with ToF information in the order of 200-600 ps. The investigation is extended to the combination of MAP-EM and ToF information to study the limit of performance using both approaches.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (up) 0018-9499 ISBN Medium
Area Expedition Conference
Notes WOS:000325827200023 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 1610
Permanent link to this record
 

 
Author Oliver, J.F.; Fuster-Garcia, E.; Cabello, J.; Tortajada, S.; Rafecas, M.
Title Application of Artificial Neural Network for Reducing Random Coincidences in PET Type Journal Article
Year 2013 Publication IEEE Transactions on Nuclear Science Abbreviated Journal IEEE Trans. Nucl. Sci.
Volume 60 Issue 5 Pages 3399-3409
Keywords
Abstract Positron Emission Tomography (PET) is based on the detection in coincidence of the two photons created in a positron annihilation. In conventional PET, this coincidence identification is usually carried out through a coincidence electronic unit. An accidental coincidence occurs when two photons arising from different annihilations are classified as a coincidence. Accidental coincidences are one of the main sources of image degradation in PET. Some novel systems allow coincidences to be selected post-acquisition in software, or in real time through a digital coincidence engine in an FPGA. These approaches provide the user with extra flexibility in the sorting process and allow the application of alternative coincidence sorting procedures. In this work a novel sorting procedure based on Artificial Neural Network (ANN) techniques has been developed. It has been compared to a conventional coincidence sorting algorithm based on a time coincidence window. The data have been obtained from Monte-Carlo simulations. A small animal PET scanner has been implemented to this end. The efficiency (the ratio of correct identifications) can be selected for both methods. In one case by changing the actual value of the coincidence window used, and in the other by changing a threshold at the output of the neural network. At matched efficiencies, the ANN-based method always produces a sorted output with a smaller random fraction. In addition, two differential trends are found: the conventional method presents a maximum achievable efficiency, while the ANN-based method is able to increase the efficiency up to unity, the ideal value, at the cost of increasing the random fraction. Images reconstructed using ANN sorted data (no compensation for randoms) present better contrast, and those image features which are more affected by randoms are enhanced. For the image quality phantom used in the paper, the ANN method decreases the spill-over ratio by a factor of 18%.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (up) 0018-9499 ISBN Medium
Area Expedition Conference
Notes WOS:000325827200027 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 1611
Permanent link to this record
 

 
Author Oliver, J.F.; Rafecas, M.
Title Improving the singles rate method for modeling accidental coincidences in high-resolution PET Type Journal Article
Year 2010 Publication Physics in Medicine and Biology Abbreviated Journal Phys. Med. Biol.
Volume 55 Issue 22 Pages 6951-6971
Keywords
Abstract Random coincidences ('randoms') are one of the main sources of image degradation in PET imaging. In order to correct for this effect, an accurate method to estimate the contribution of random events is necessary. This aspect becomes especially relevant for high-resolution PET scanners where the highest image quality is sought and accurate quantitative analysis is undertaken. One common approach to estimate randoms is the so-called singles rate method (SR) widely used because of its good statistical properties. SR is based on the measurement of the singles rate in each detector element. However, recent studies suggest that SR systematically overestimates the correct random rate. This overestimation can be particularly marked for low energy thresholds, below 250 keV used in some applications and could entail a significant image degradation. In this work, we investigate the performance of SR as a function of the activity, geometry of the source and energy acceptance window used. We also investigate the performance of an alternative method, which we call 'singles trues' (ST) that improves SR by properly modeling the presence of true coincidences in the sample. Nevertheless, in any real data acquisition the knowledge of which singles are members of a true coincidence is lost. Therefore, we propose an iterative method, STi, that provides an estimation based on ST but which only requires the knowledge of measurable quantities: prompts and singles. Due to inter-crystal scatter, for wide energy windows ST only partially corrects SR overestimations. While SR deviations are in the range 86-300% (depending on the source geometry), the ST deviations are systematically smaller and contained in the range 4-60%. STi fails to reproduce the ST results, although for not too high activities the deviation with respect to ST is only a few percent. For conventional energy windows, i.e. those without inter-crystal scatter, the ST method corrects the SR overestimations, and deviations from the true random rate are of the order of 1% or less. In addition, in the case of conventional energy window STi results reproduce ST results and therefore the former can be used to obtain the true random rate.
Address [Oliver, Josep F.; Rafecas, Magdalena] Univ Valencia, CSIC, Inst Fis Corpuscular, IFIC, E-46003 Valencia, Spain, Email: josep.f.oliver@uv.es
Corporate Author Thesis
Publisher Iop Publishing Ltd Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (up) 0031-9155 ISBN Medium
Area Expedition Conference
Notes ISI:000283789700025 Approved no
Is ISI yes International Collaboration no
Call Number IFIC @ elepoucu @ Serial 344
Permanent link to this record
 

 
Author Cabello, J.; Rafecas, M.
Title Comparison of basis functions for 3D PET reconstruction using a Monte Carlo system matrix Type Journal Article
Year 2012 Publication Physics in Medicine and Biology Abbreviated Journal Phys. Med. Biol.
Volume 57 Issue 7 Pages 1759-1777
Keywords
Abstract In emission tomography, iterative statistical methods are accepted as the reconstruction algorithms that achieve the best image quality. The accuracy of these methods relies partly on the quality of the system response matrix (SRM) that characterizes the scanner. The more physical phenomena included in the SRM, the higher the SRM quality, and therefore higher image quality is obtained from the reconstruction process. High-resolution small animal scanners contain as many as 10(3)-10(4) small crystal pairs, while the field of view (FOV) is divided into hundreds of thousands of small voxels. These two characteristics have a significant impact on the number of elements to be calculated in the SRM. Monte Carlo (MC) methods have gained popularity as a way of calculating the SRM, due to the increased accuracy achievable, at the cost of introducing some statistical noise and long simulation times. In the work presented here the SRM is calculated using MC methods exploiting the cylindrical symmetries of the scanner, significantly reducing the simulation time necessary to calculate a high statistical quality SRM and the storage space necessary. The use of cylindrical symmetries makes polar voxels a convenient basis function. Alternatively, spherically symmetric basis functions result in improved noise properties compared to cubic and polar basis functions. The quality of reconstructed images using polar voxels, spherically symmetric basis functions on a polar grid, cubic voxels and post-reconstruction filtered polar and cubic voxels is compared from a noise and spatial resolution perspective. This study demonstrates that polar voxels perform as well as cubic voxels, reducing the simulation time necessary to calculate the SRM and the disk space necessary to store it. Results showed that spherically symmetric functions outperform polar and cubic basis functions in terms of noise properties, at the cost of slightly degraded spatial resolution, larger SRM file size and longer reconstruction times. However, we demonstrate that post-reconstruction smoothing, usually applied in emission imaging to reduce the level of noise, can produce a spatial resolution degradation of similar to 50%, while spherically symmetric basis functions produce a degradation of only similar to 6%, compared to polar and cubic voxels, at the same noise level. Therefore, the image quality trade-off obtained with blobs is higher than that obtained with cubic or polar voxels.
Address [Cabello, Jorge; Rafecas, Magdalena] Univ Valencia, Inst Fis Corpuscular, CSIC, Valencia, Spain, Email: jorge.cabello@ific.uv.es
Corporate Author Thesis
Publisher Iop Publishing Ltd Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (up) 0031-9155 ISBN Medium
Area Expedition Conference
Notes WOS:000302121000004 Approved no
Is ISI yes International Collaboration no
Call Number IFIC @ pastor @ Serial 955
Permanent link to this record
 

 
Author Blume, M.; Navab, N.; Rafecas, M.
Title Joint image and motion reconstruction for PET using a B-spline motion model Type Journal Article
Year 2012 Publication Physics in Medicine and Biology Abbreviated Journal Phys. Med. Biol.
Volume 57 Issue 24 Pages 22pp
Keywords
Abstract We present a novel joint image and motion reconstruction method for PET. The method is based on gated data and reconstructs an image together with amotion function. The motion function can be used to transform the reconstructed image to any of the input gates. All available events (from all gates) are used in the reconstruction. The presented method uses a B-spline motion model, together with a novel motion regularization procedure that does not need a regularization parameter (which is usually extremely difficult to adjust). Several image and motion grid levels are used in order to reduce the reconstruction time. In a simulation study, the presented method is compared to a recently proposed joint reconstruction method. While the presented method provides comparable reconstruction quality, it is much easier to use since no regularization parameter has to be chosen. Furthermore, since the B-spline discretization of the motion function depends on fewer parameters than a displacement field, the presented method is considerably faster and consumes less memory than its counterpart. The method is also applied to clinical data, for which a novel purely data-driven gating approach is presented.
Address [Blume, Moritz; Rafecas, Magdalena] Univ Valencia, CSIC, Inst Fis Corpuscular IFIC, E-46071 Valencia, Spain, Email: moritz.blume@fasterplan.com
Corporate Author Thesis
Publisher Iop Publishing Ltd Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (up) 0031-9155 ISBN Medium
Area Expedition Conference
Notes WOS:000312106200009 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 1267
Permanent link to this record