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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Design and Construction of Detector and Data Acquisition Elements for Proton Computed Tomography

Proton computed tomography (pCT) offers an alternative to x-ray imaging with potential for three-dimensional imaging, reduced radiation exposure, and in-situ imaging. Northern Illinois University (NIU) is developing a second-generation proton computed tomography system with a goal of demonstrating the feasibility of three-dimensional imaging within clinically realistic imaging times. The second-generation pCT system is comprised of a tracking system, a calorimeter, data acquisition, a computing farm, and software algorithms. The proton beam encounters the upstream tracking detectors, the patient or phantom, the downstream tracking detectors, and a calorimeter. The schematic layout of the PCT system is shown. The data acquisition sends the proton scattering information to an offline computing farm. Major innovations of the second generation pCT project involve an increased data acquisition rate ( MHz range) and development of three-dimensional imaging algorithms. The Fermilab Particle Physics Division and Northern Illinois Center for Accelerator and Detector Development at Northern Illinois University worked together to design and construct the tracking detectors, calorimeter, readout electronics and detector mounting system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Sparse-view proton computed tomography using modulated proton beams

Purpose: Proton imaging that uses a modulated proton beam and an intensity detector allows a relatively fast image acquisition compared to the imaging approach based on a trajectory tracking detector. In addition, it requires a relatively simple implementation in a conventional proton therapy equipment. The model of geometric straight ray assumed in conventional computed tomography (CT) image reconstruction is however challenged by multiple-Coulomb scattering and energy straggling in the proton imaging. Radiation dose to the patient is another important issue that has to be taken care of for practical applications. In this work, the authors have investigated iterative image reconstructions after a deconvolution of the sparsely view-sampled data to address these issues in proton CT. Methods: Proton projection images were acquired using the modulated proton beams and the EBT2 film as an intensity detector. Four electron-density cylinders representing normal soft tissues and bone were used as imaged object and scanned at 40 views that are equally separated over 360°. Digitized film images were converted to water-equivalent thickness by use of an empirically derived conversion curve. For improving the image quality, a deconvolution-based image deblurring with an empirically acquired point spread function was employed. They have implemented iterative image reconstruction algorithms such as adaptive steepest descent-projection onto convex sets (ASD-POCS), superiorization method–projection onto convex sets (SM-POCS), superiorization method–expectation maximization (SM-EM), and expectation maximization-total variation minimization (EM-TV). Performance of the four image reconstruction algorithms was analyzed and compared quantitatively via contrast-to-noise ratio (CNR) and root-mean-square-error (RMSE). Results: Objects of higher electron density have been reconstructed more accurately than those of lower density objects. The bone, for example, has been reconstructed within 1% error. EM-based algorithms produced an increased image noise and RMSE as the iteration reaches about 20, while the POCS-based algorithms showed a monotonic convergence with iterations. The ASD-POCS algorithm outperformed the others in terms of CNR, RMSE, and the accuracy of the reconstructed relative stopping power in the region of lung and soft tissues. Conclusions: The four iterative algorithms, i.e., ASD-POCS, SM-POCS, SM-EM, and EM-TV, have been developed and applied for proton CT image reconstruction. Although it still seems that the images need to be improved for practical applications to the treatment planning, proton CT imaging by use of the modulated beams in sparse-view sampling has demonstrated its feasibility.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

A pencil beam approach to proton computed tomography

Purpose: A new approach to proton computed tomography (pCT) is presented. In this approach, protons are not tracked one-by-one but a beam of particles is considered instead. The elements of the pCT reconstruction problem (residual energy and path) are redefined on the basis of this new approach. An analytical image reconstruction algorithm applicable to this scenario is also proposed. Methods: The pencil beam (PB) and its propagation in matter were modeled by making use of the generalization of the Fermi–Eyges theory to account for multiple Coulomb scattering (MCS). This model was integrated into the pCT reconstruction problem, allowing the definition of the mean beam path concept similar to the most likely path (MLP) used in the single-particle approach. A numerical validation of the model was performed. The algorithm of filtered backprojection along MLPs was adapted to the beam-by-beam approach. The acquisition of a perfect proton scan was simulated and the data were used to reconstruct images of the relative stopping power of the phantom with the single-proton and beam-by-beam approaches. The resulting images were compared in a qualitative way. Results: The parameters of the modeled PB (mean and spread) were compared to Monte Carlo results in order to validate the model. For a water target, good agreement was found for the mean value of the distributions. As far as the spread is concerned, depth-dependent discrepancies as large as 2%–3% were found. For a heterogeneous phantom, discrepancies in the distribution spread ranged from 6% to 8%. The image reconstructed with the beam-by-beam approach showed a high level of noise compared to the one reconstructed with the classical approach. Conclusions: The PB approach to proton imaging may allow technical challenges imposed by the current proton-by-proton method to be overcome. In this framework, an analytical algorithm is proposed. Further work will involve a detailed study of the performances and limitations of this approach in terms of image quality. The paper shows how to account for the MCS in the reconstruction step with this new approach when an analytical reconstruction algorithm is used.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-J-184: Proton Computed Tomography Using 1D Silicon Diode Array

Purpose: Proton radiography and proton computed tomography (PCT) can be used to measure proton stopping power directly. However, practical and cost effective proton imaging detectors are not widely available. In this study, the authors investigated the feasibility of proton imaging using a silicon diode array. Methods: A one-dimensional silicon-diode detector array (1DSDA) was aligned with the central axis (CAX) of the proton beam. Polymethyl methacrylate (PMMA) slabs were used to find the correspondence between the water equivalent thickness (WET) and 1DSDA channel number. 2D proton radiographs (PR) were obtained by translation and rotation of a phantom relative to CAX while the proton nozzle and 1DSDA were kept stationary. A PCT image of one slice of the phantom was reconstructed using filtered backprojection. Results: PR and PCT images of the PMMA cube were successfully acquired using the 1DSDA. The WET of the phantom was measured using PR data with an accuracy of 4.2% or better. Structures down to 1 mm in size could be resolved. Reconstruction of a PCT image showed very good agreement with simulation. Limitations in spatial resolution are attributed to limited spatial sampling, beam collimation, and proton scatter. Conclusion: The results demonstrate the feasibility of using silicon diode arrays for proton imaging. Such a device can potentially offer fast image acquisition, high spatial and energy resolution for PR and PCT.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Improved proton computed tomography by dual modality image reconstruction

Purpose: Proton computed tomography (CT) is a promising image modality for improving the stopping power estimates and dose calculations for particle therapy. However, the finite range of about 33 cm of water of most commercial proton therapy systems limits the sites that can be scanned from a full 360° rotation. In this paper the authors propose a method to overcome the problem using a dual modality reconstruction (DMR) combining the proton data with a cone-beam x-ray prior. Methods: A Catphan 600 phantom was scanned using a cone beam x-ray CT scanner. A digital replica of the phantom was created in the Monte Carlo code Geant4 and a 360° proton CT scan was simulated, storing the entrance and exit position and momentum vector of every proton. Proton CT images were reconstructed using a varying number of angles from the scan. The proton CT images were reconstructed using a constrained nonlinear conjugate gradient algorithm, minimizing total variation and the x-ray CT prior while remaining consistent with the proton projection data. The proton histories were reconstructed along curved cubic-spline paths. Results: The spatial resolution of the cone beam CT prior was retained for the fully sampled case and the 90° interval case, with the MTF = 0.5 (modulation transfer function) ranging from 5.22 to 5.65 linepairs/cm. In the 45° interval case, the MTF = 0.5 dropped to 3.91 linepairs/cm For the fully sampled DMR, the maximal root mean square (RMS) error was 0.006 in units of relative stopping power. For the limited angle cases the maximal RMS error was 0.18, an almost five-fold improvement over the cone beam CT estimate. Conclusions: Dual modality reconstruction yields the high spatial resolution of cone beam x-ray CT while maintaining the improved stopping power estimation of proton CT. In the case of limited angles, the use of prior image proton CT greatly improves the resolution and stopping power estimate, but does not fully achieve the quality of a 360° proton CT scan.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2012

A CW FFAG for Proton Computed Tomography

An advantage of the cyclotron in proton therapy is the continuous (CW) beam output which reduces complexity and response time in the dosimetry requirements and beam controls. A CW accelerator requires isochronous particle orbits at all energie s through the acceleration cycle and present compact isochronous cyclotrons for proton therapy reach only 250 MeV (kinetic energy) which is required for patient treatment, but low for full Proton Computed Tomography (PCT) capability. PCT specifications ne ed 300-330 MeV in order for protons to transit the human body. Recent innovations in nonscaling FFAG design have achieved isochronous performance in a compact (~3 m radius) design at these higher energies. Preliminary isochronous designs are presented her e. Lower energy beams can be efficiently extracted for patient treatment without changes to the acceleration cycle and magnet currents.

43 PARTICLE ACCELERATORS↗
DOE OSTI2016

Development of a proton Computed Tomography Detector System

Computer tomography is one of the most promising new methods to image abnormal tissues inside the human body. Tomography is also used to position the patient accurately before radiation therapy. Hadron therapy for treating cancer has become one of the most advantegeous and safe options. In order to fully utilize the advantages of hadron therapy, there is a necessity of performing radiography with hadrons as well. In this paper we present the development of a proton computed tomography system. Our second-generation proton tomography system consists of two upstream and two downstream trackers made up of fibers as active material and a range detector consisting of plastic scintillators. We present details of the detector system, readout electronics, and data acquisition system as well as the commissioning of the entire system. We also present preliminary results from the test beam of the range detector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2013

A Detector for Proton Computed Tomography

Radiation therapy is a widely recognized treatment for cancer. Energetic protons have distinct features that set them apart from photons and make them desirable for cancer therapy as well as medical imaging. The clinical interest in heavy ion therapy is due to the fact that ions deposit almost all of their energy in a sharp peak – the Bragg peak- at the very end of their path. Proton beams can be used to precisely localize a tumor and deliver an exact dose to the tumor with small doses to the surrounding tissue. Proton computed tomography (pCT) provides direct information on the location on the target tumor, and avoids position uncertainty caused by treatment planning based on imaging with X-ray CT. The pCT project goal is to measure and reconstruct the proton relative stopping power distribution directly in situ. To ensure the full advantage of cancer treatment with 200 MeV proton beams, pCT must be realized.

Blazey, G.↗
DOE OSTI2021

Particle-Tracking Proton Computed Tomography—Data Acquisition, Preprocessing, and Preconditioning

Proton CT (pCT) is a promising new imaging technique that can reconstruct relative stopping power (RSP) more accurately than x-ray CT in each cubic millimeter voxel of the patient. This, in turn, will result in better proton range accuracy and, therefore, smaller planned tumor volumes (PTV). The hardware description and some reconstructed images have previously been reported. In a series of two contributions, we focus on presenting the software algorithms that convert pCT detector data to the final reconstructed pCT images for application in proton treatment planning. There were several options on how to accomplish this, and we will describe our solutions at each stage of the data processing chain. In the first paper of this series, we present the data acquisition with the pCT tracking and energy-range detectors and how the data are preprocessed, including the conversion to the well-formatted track information from tracking data and water-equivalent path length from the data of a calibrated multi-stage energy-range detector. These preprocessed data are then used for the initial image formation with an FDK cone-beam CT algorithm. The output of data acquisition, preprocessing, and FDK reconstruction is presented along with illustrative imaging results for two phantoms, including a pediatric head phantom. The second paper in this series will demonstrate the use of iterative solvers in conjunction with the superiorization methodology to further improve the images resulting from the upfront FDK image reconstruction and the implementation of these algorithms on a hybrid CPU/GPU computer cluster.

42 ENGINEERING↗
DOE OSTI2016

Electronic stopping power calculation for water under the Lindhard formalism for application in proton computed tomography

Because of the behavior that charged particles have when they interact with biological material, proton therapy is shaping the future of radiation therapy in cancer treatment. The planning of radiation therapy is made up of several stages. The first one is the diagnostic image, in which you have an idea of the density, size and type of tumor being treated; to understand this it is important to know how the particles beam interacts with the tissue. In this work, by using de Lindhard formalism and the Y.R. Waghmare model for the charge distribution of the proton, the electronic stopping power (SP) for a proton beam interacting with a liquid water target in the range of proton energies 10{sup 1} eV - 10{sup 10} eV taking into account all the charge states is calculated.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2012

Silicon photomultiplier choice for the scintillating fibre tracker in second generation proton computed tomography scanner

Scintillating fibers are capable of charged particle tracking with high position resolution, as demonstrated by the central fiber tracker of the D0 experiment. The charged particles will deposit less energy in the polystyrene scintillating fibers as opposed to a typical silicon tracker of the same thickness, while SiPM's are highly efficient at detecting photons created by the passage of the charged particle through the fibers. The current prototype of the Proton Computed Tomography (pCT) tracker uses groups of three 0.5 mm green polystyrene based scintillating fibers connected to a single SiPM, while first generation prototype tracker used Silicon strip detectors. The results of R&D for the Scintillating Fiber Tracker (SFT) as part of the pCT detector are outlined, and the premise for the selection of SiPM is discussed.

43 PARTICLE ACCELERATORS↗
DOE OSTI2015

Calibration and GEANT4 Simulations of the Phase II Proton Compute Tomography (pCT) Range Stack Detector

Northern Illinois University in collaboration with Fermi National Accelerator Laboratory (FNAL) and Delhi University has been designing and building a proton CT scanner for applications in proton treatment planning. The Phase II proton CT scanner consists of eight planes of tracking detectors with two X and two Y coordinate measurements both before and after the patient. In addition, a range stack detector consisting of a stack of thin scintillator tiles, arranged in twelve eight-tile frames, is used to determine the water equivalent path length (WEPL) of each track through the patient. The X-Y coordinates and WEPL are required input for image reconstruction software to find the relative (proton) stopping powers (RSP) value of each voxel in the patient and generate a corresponding 3D image. In this Note we describe tests conducted in 2015 at the proton beam at the Central DuPage Hospital in Warrenville, IL, focusing on the range stack calibration procedure and comparisons with the GEANT~4 range stack simulation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2012

On proton CT reconstruction using MVCT-converted virtual proton projections

Purpose: To describe a novel methodology of converting megavoltage x-ray projections into virtual proton projections that are otherwise missing due to the proton range limit. These converted virtual proton projections can be used in the reconstruction of proton computed tomography (pCT). Methods: Relations exist between proton projections and multispectral megavoltage x-ray projections for human tissue. Based on these relations, these tissues can be categorized into: (a) adipose tissue; (b) nonadipose soft tissues; and (c) bone. These three tissue categories can be visibly identified on a regular megavoltage x-ray computed tomography (MVCT) image. With an MVCT image and its projection data available, the x-ray projections through heterogeneous anatomy can be converted to the corresponding proton projections using predetermined calibration curves for individual materials, aided by a coarse segmentation on the x-ray CT image. To show the feasibility of this approach, mathematical simulations were carried out. The converted proton projections, plotted on a proton sinogram, were compared to the simulated ground truth. Proton stopping power images were reconstructed using either the virtual proton projections only or a blend of physically available proton projections and virtual proton projections that make up for those missing due to the range limit. These images were compared to a reference image reconstructed from theoretically calculated proton projections. Results: The converted virtual projections had an uncertainty of {+-}0.8% compared to the calculated ground truth. Proton stopping power images reconstructed using a blend of converted virtual projections (48%) and physically available projections (52%) had an uncertainty of {+-}0.86% compared with that reconstructed from theoretically calculated projections. Reconstruction solely from converted virtual proton projections had an uncertainty of {+-}1.1% compared with that reconstructed from theoretical projections. If these images are used for treatment planning, the average proton range uncertainty is estimated to be less than 1.5% for an imaging dose in the milligray range. Conclusions: The proposed method can be used to convert x-ray projections into virtual proton projections. The converted proton projections can be blended with existing proton projections or can be used solely for pCT reconstruction, addressing the range limit problem of pCT using current therapeutic proton machines.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

Water-equivalent path length calibration of a prototype proton CT scanner

Purpose: The authors present a calibration method for a prototype proton computed tomography (pCT) scanner. The accuracy of these measurements depends upon careful calibration of the energy detector used to measure the residual energy of the protons that passed through the object. Methods: A prototype pCT scanner with a cesium iodide (CsI(Tl)) crystal calorimeter was calibrated by measuring the calorimeter response for protons of 200 and 100 MeV initial energies undergoing degradation in polystyrene plates of known thickness and relative stopping power (RSP) with respect to water. Calibration curves for the two proton energies were obtained by fitting a second-degree polynomial to the water-equivalent path length versus calorimeter response data. Using the 100 MeV calibration curve, the RSP values for a variety of tissue-equivalent materials were measured and compared to values obtained from a standard depth-dose range shift measurement using a water-tank. A cylindrical water phantom was scanned with 200 MeV protons and its RSP distribution was reconstructed using the 200 MeV calibration. Results: It is shown that this calibration method produces measured RSP values of various tissue-equivalent materials that agree to within 0.5% of values obtained using an established water-tank method. The mean RSP value of the water phantom reconstruction was found to be 0.995 {+-} 0.006. Conclusions: The method presented provides a simple and reliable procedure for calibration of a pCT scanner.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

SU-C-207A-01: A Novel Maximum Likelihood Method for High-Resolution Proton Radiography/proton CT

Purpose: Multiple Coulomb scattering is the largest contributor to blurring in proton imaging. Here we tested a maximum likelihood least squares estimator (MLLSE) to improve the spatial resolution of proton radiography (pRad) and proton computed tomography (pCT). Methods: The object is discretized into voxels and the average relative stopping power through voxel columns defined from the source to the detector pixels is optimized such that it maximizes the likelihood of the proton energy loss. The length spent by individual protons in each column is calculated through an optimized cubic spline estimate. pRad images were first produced using Geant4 simulations. An anthropomorphic head phantom and the Catphan line-pair module for 3-D spatial resolution were studied and resulting images were analyzed. Both parallel and conical beam have been investigated for simulated pRad acquisition. Then, experimental data of a pediatric head phantom (CIRS) were acquired using a recently completed experimental pCT scanner. Specific filters were applied on proton angle and energy loss data to remove proton histories that underwent nuclear interactions. The MTF10% (lp/mm) was used to evaluate and compare spatial resolution. Results: Numerical simulations showed improvement in the pRad spatial resolution for the parallel (2.75 to 6.71 lp/cm) and conical beam (3.08 to 5.83 lp/cm) reconstructed with the MLLSE compared to averaging detector pixel signals. For full tomographic reconstruction, the improved pRad were used as input into a simultaneous algebraic reconstruction algorithm. The Catphan pCT reconstruction based on the MLLSE-enhanced projection showed spatial resolution improvement for the parallel (2.83 to 5.86 lp/cm) and conical beam (3.03 to 5.15 lp/cm). The anthropomorphic head pCT displayed important contrast gains in high-gradient regions. Experimental results also demonstrated significant improvement in spatial resolution of the pediatric head radiography. Conclusion: The proposed MLLSE shows promising potential to increase the spatial resolution (up to 244%) in proton imaging.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-147: Monte Carlo Study of the Precision and Accuracy of Proton CT Reconstructed Relative Stopping Power Maps

Purpose: The quantification of the intrinsic performances of proton computed tomography (pCT) as a modality for treatment planning in proton therapy. The performance of an ideal pCT scanner is studied as a function of various parameters. Methods: Using GATE/Geant4, we simulated an ideal pCT scanner and scans of several cylindrical phantoms with various tissue equivalent inserts of different sizes. Insert materials were selected in order to be of clinical relevance. Tomographic images were reconstructed using a filtered backprojection algorithm taking into account the scattering of protons into the phantom. To quantify the performance of the ideal pCT scanner, we study the precision and the accuracy with respect to the theoretical relative stopping power ratios (RSP) values for different beam energies, imaging doses, insert sizes and detector positions. The planning range uncertainty resulting from the reconstructed RSP is also assessed by comparison with the range of the protons in the analytically simulated phantoms. Results: The results indicate that pCT can intrinsically achieve RSP resolution below 1%, for most examined tissues at beam energies below 300 MeV and for imaging doses around 1 mGy. RSP maps accuracy of less than 0.5 % is observed for most tissue types within the studied dose range (0.2–1.5 mGy). Finally, the uncertainty in the proton range due to the accuracy of the reconstructed RSP map is well below 1%. Conclusion: This work explores the intrinsic performance of pCT as an imaging modality for proton treatment planning. The obtained results show that under ideal conditions, 3D RSP maps can be reconstructed with an accuracy better than 1%. Hence, pCT is a promising candidate for reducing the range uncertainties introduced by the use of X-ray CT alongside with a semiempirical calibration to RSP.Supported by the DFG Cluster of Excellence Munich-Centre for Advanced Photonics (MAP)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-148: Tools for Development of 4D Proton CT

Purpose: To develop tools for performing 4D proton computed tomography (CT). Methods: A suitable patient with a tumor in the right lower lobe was selected from a set of 4D CT scans. The volumetric CT images formed the basis for calculating the parameters of a breathing model that allows reconstruction of a static reference CT and CT images in each breathing phase. The images were imported into the TOPAS Monte Carlo simulation platform for simulating an experimental proton CT scan with 45 projections spaced by 4 degree intervals. Each projection acquired data for 2 seconds followed by a gantry rotation for 2 seconds without acquisition. The scan covered 180 degrees with individual protons passing through a 9-cm slab of the patient’s lung covering the moving tumor. An initial proton energy sufficient for penetrating the patient from all directions was determined. Performing the proton CT simulation, TOPAS provided output of the proton energy and coordinates registered in two planes before and after the patient, respectively. The set of projection data was then used with an iterative reconstruction algorithm to generate a volumetric proton CT image set of the static reference image and the image obtained under breathing motion, respectively. Results: An initial proton energy of 230 MeV was found to be sufficient, while for an initial energy of 200 MeV a substantial number of protons did not penetrate the patient. The reconstruction of the static reference image set provided sufficient detail for treatment planning. Conclusion: We have developed tools to perform studies of proton CT in the presence of lung motion based on the TOPAS simulation toolkit. This will allow to optimize 4D reconstruction algorithms by synchronizing the acquired proton CT data with a breathing signal and utilizing a breathing model obtained prior to the proton CT scan. This research has been supported by the National Institute Of Biomedical Imaging And Bioengineering of the National Institutes of Health under Award Number R01EB013118.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-I-54: Spatial Resolution Studies in Proton CT Using a Phase-II Prototype Head Scanner

Purpose: To characterize the modulation transfer function (MTF) of the pre-clinical (phase II) head scanner developed for proton computed tomography (pCT) by the pCT collaboration. To evaluate the spatial resolution achievable by this system. Methods: Our phase II proton CT scanner prototype consists of two silicon telescopes that track individual protons upstream and downstream from a phantom, and a 5-stage scintillation detector that measures a combination of the residual energy and range of the proton. Residual energy is converted to water equivalent path length (WEPL) of the protons in the scanned object. The set of WEPL values and associated paths of protons passing through the object over a 360° angular scan is processed by an iterative parallelizable reconstruction algorithm that runs on GP-GPU hardware. A custom edge phantom composed of water-equivalent polymer and tissue-equivalent material inserts was constructed. The phantom was first simulated in Geant4 and then built to perform experimental beam tests with 200 MeV protons at the Northwestern Medicine Chicago Proton Center. The oversampling method was used to construct radial and azimuthal edge spread functions and modulation transfer functions. The spatial resolution was defined by the 10% point of the modulation transfer function in units of lp/cm. Results: The spatial resolution of the image was found to be strongly correlated with the radial position of the insert but independent of the relative stopping power of the insert. The spatial resolution varies between roughly 4 and 6 lp/cm in both the the radial and azimuthal directions depending on the radial displacement of the edge. Conclusion: The amount of image degradation due to our detector system is small compared with the effects of multiple Coulomb scattering, pixelation of the image and the reconstruction algorithm. Improvements in reconstruction will be made in order to achieve the theoretical limits of spatial resolution.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗