IEEE 2021 NSS MIC

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Dec 5, 2021, 9:10:42 AM
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Imaging

Session chair: Iwanczyk , Jan S. (DxRay, Inc., Northridge, USA); Verger , Loick (CEA-LETI, Optics & Photonics Division, GRENOBLE, France)
 
Shortcut: R-05
Date: Wednesday, 20 October, 2021, 7:00 AM - 8:45 AM
Room: RTSD
Session type: RTSD Session

Contents

Click on an contribution to preview the abstract content.

7:00 AM R-05-01

A new concept for a low-dose stationary tomographic Molecular Breast Imaging camera using 3D position sensitive CZT detectors (#1055)

A. Cherlin1, A. Wirth1, K. Erlandsson2, I. Baistow1, K. Thielemans2, B. Hutton2

1 Kromek Group plc, Sedgefield, United Kingdom
2 University College London, The Institute of Nuclear Medicine, London, United Kingdom

Abstract

Pixelated CZT detectors have been used in molecular imaging applications for many years. The interplay of gamma camera and collimator geometric design, gantry motion, and image reconstruction determines the image quality and dosetime-FOV trade-offs. In particular, Molecular Breast Imaging (MBI) has been shown to provide excellent diagnostic results in patients with dense breast tissue [1], but higher than mammography patient dose and long imaging time impede its wide adoption. We propose a new transformative system concept combining the advantages of CZT detectors (superior energy and position resolution and depth of interaction sensing), multi-pinhole collimation and novel image reconstruction to mitigate those drawbacks without compromising diagnostic content. The system is comprised of four 7.3 mm thick CZT detectors with 2 mm pixels combined with densely packed multi-pinhole collimators. The detectors have 3D position sensitivity provided by 2x2 sub-pixelisation and depth of interaction (DOI) capability. The closely spaced pinholes allow tomographic image reconstruction, improve sensitivity and angular sampling, but result in significant multiplexing. Novel de-multiplexing algorithms have been developed to mitigate the adverse multiplexing artefacts using the DOI. GATE simulations of the new camera demonstrate a potential to reduce the patient dose by at least a factor of 5 in comparison to planar MBI, thus reducing the dose to the level of an average mammography scan. The first prototype has been built at Kromek and is being evaluated using an “activity-painting” setup incorporating an XYZ motorised stage assembly and a point 57Co source. Initial results demonstrate the expected performance improvement with the use of sub-pixelisation and DOI. The next steps of the development will include accurate evaluation of the image quality and the dose reduction followed by building a larger scale clinical prototype using optimised detector design.

Keywords: CZT, Multi-pinhole collimator, Molecular Breast Imaging, MBI, Multiplexing
7:15 AM R-05-02

Wide-gap CdTe Strip Detectors for High-Resolution Imaging in Hard X-rays (#502)

S. Nagasawa1, 2, T. Minami1, 2, S. Watanabe3, 2, T. Takahashi2, 1

1 The University of Tokyo, Department of Physics, Tokyo, Japan
2 The University of Tokyo, Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU, WPI), Chiba, Japan
3 Japan Aerospace Exploration Agency (JAXA), Institute of Space and Astronautical Science (ISAS), Kanagawa, Japan

Abstract

We propose a new strip configuration as “Wide-gap CdTe strip detector”, in which a gap between strips is much wider than the width of strips. By utilizing the information on the sharing energies between adjacent strips, a position resolution finer than strip pitch could be achieved.  However, the percentage of charge sharing events is limited and it is expected to enhance charge sharing events by widening the gap between the strips. To confirm this concept, we developed a wide-gap CdTe strip detector, which has 64 Pt strip electrodes on the cathode side varied from 60 um strip pitch (30 um strip and 30 um gap width) to 80 um strip pitch (30 um strip and 50 um gap width). We conducted a evaluation test by uniformly irradiated X-rays using Am-241. 
In terms of spectroscopic performance, just the sum of the energies detected in adjacent strips causes a degradation of energy resolution because of the charge loss of wider gap. Therefore, to keep spectroscopic performance and accurately assess the energy dependence of charge sharing properties, we first developed a new energy reconstruction method to compensate this charge loss effect. By applying this method, we confirmed that the charge sharing events for 17.8 keV events are increased from 24.3 to 49.9 percent by making a gap wider. We also conducted a theoretical calculation based on Shockley-Ramo theorem and confirmed the consistency with the results of evaluation test.

AcknowledgmentThis work was supported by JSPS, Japan KAKENHI Grant Number 18H05457 and 20H00153, FoPM, WINGS Program and JSR Fellowship, the University of Tokyo, Japan.
Keywords: CdTe, Charge Sharing, Strip Detector, X-rays
7:30 AM R-05-03

Event Reconstruction in Radiation Detectors using Convolutional Neural Networks (#1004)

S. Banerjee1, M. Rodrigues2, A. H. Vija2, A. K. Katsaggelos1

1 Northwestern University, Electrical and Computer Engineering, Evanston/Chicago, Illinois, United States of America
2 Siemens Medical Solutions USA Inc, SHS DI MI PLM-R & D, R SPECT, Hoffman Estates, Illinois, United States of America

Abstract

Room Temperature Semiconductor Detectors (RTSD) (e.g., CdZnTe and CdZnTeSe) have been recently proposed in novel space, homeland security and medical applications, which provide sub-millimeter position information of interacting γ-rays and excellent spectroscopic performance. These detectors have been constructed using a large variety of anode configurations. The virtual Frisch-grid concept with reduced readout channels has been proposed recently. To fully utilize the potential of RTSD, advanced single-polarity charge sensing reconstruction algorithms are needed. Energy and position of interaction reconstruction algorithms rely on physics-based models, with Principal Component Analysis being introduced recently. Proposed deep learning (DL) techniques have the potential to perform event reconstruction with improved position information and better energy resolution than conventional non-DL methods. In this paper, we present a novel DL approach based on Convolutional Neural Networks (CNN) for identifying the energy deposition and position of interaction of the γ-rays interacting within the RTSD. The network is trained with input-output data pairs. The input data consists of signals at the electrodes corresponding to each incident event and the output data the position and energy spectrum of those events. Our network consists of 5 stages of convolutional layers, each followed by a batch normalization layer and a max-pooling layer. These layers extract features from the input signals fed to the model. This is followed by 2 stages of fully connected layers. Our model outputs the interaction positions and energies within the RTSD. The model is trained using gradient descent steps using the backpropagation method in Tensorflow library of Python. The network has been tested with unseen signals. The Root Mean Squared Error (RMSE) for test cases was 1.24 % and 0.42 % for position and energy respectively.

Keywords: RTSD, Detector Response, Event Reconstruction, Deep Learning, Convolutional Neural Networks
7:45 AM R-05-04

Development of a η-function for high spatial resolution neutron imaging with Lithium indium diselenide semiconductors (#1166)

J. Gallagher1, M. A. Benkechkache1, L. Drouet1, R. Golduber1, E. Lukosi1

1 University of Tennessee, Department of Nuclear Engineering, Knoxville, Tennessee, United States of America

Abstract

Lithium indium diselenide (LiInSe2 or LISe) semiconductors are a potential option for energy resolved neutron imaging due to their high neutron detection efficiency and excellent spatial resolution. This report summarizes our current efforts to enhance LISe-based neutron imaging systems to achieve our end goal of ~5 μm spatial resolution and ~1 μs timing. In order to overcome the limited spatial and temporal resolution of state-of-the-art imagers at neutron imaging facilities, we have created a modified η-function to identify the location of neutron absorptions by sharing charge across strips using a double-sided strip design (DSSD). MATLAB simulations are being conducted to create a training data set based upon simulated 6Li(n,3H)4He reactions throughout the LISe bulk material for three different strip pitches/widths. This training data set is then used to determine the particle’s interaction location within the sensor. Furthermore, the addition of noise to our training dataset and the resulting performance of our models, different pattern classification/machine learning techniques, and the effect of charge collection efficiency on the sensor’s performance is presented. We plan to benchmark simulated data with experiments at the Spallation Neutron Source (SNS).

AcknowledgmentPart of this work was conducted in the Micro-Processing Research Facility, a University of Tennessee Core Facility. This material is based upon work supported by the U.S. Department of Energy under grant no. DOE-BES-R015010058.
Keywords: LISe, Neutron imaging, Semiconductor detector, Silvaco simulation, Table lookup
8:00 AM R-05-05

Optimization of conventional Compton camera using electron track algorithm (#1297)

J. Wen1, 2, X. Zheng1, M. Zeng1, Y. Zhang1, G. Ma1, Z. Zhao2

1 Tsinghua University, Department of Engineering Physics, Beijing, China
2 China Academy of Engineering Physics, Laser Fusion Research Center, Miangyang, China

Abstract

Compton camera has been regarded as one of the most promising technologies for gamma-ray imaging thus be of interest for various fields. High spatial resolution detectors with small pixel pitch are widely used for the creation of Compton camera with high angular resolution. However, the angular resolution of the Compton camera is degraded in imaging of high energy gamma sources, because the diffusion of energetic Compton electron or photoelectron could make many pixels triggered and the measurement of scattering and absorption position would be distorted. In this study, we use the electron track algorithm to reconstruct the interaction point in a Timepix3-based single layer Compton camera. The experimental results demonstrate that the resolution of the conventional Compton camera can be improved with the reconstruction of the electron track.

AcknowledgmentThis work was supported by the National Natural Science Foundation of China (Grant No. 11975214 and 12004353), Science Challenge Project (Grant No. TZ2018005), and National Key R&D Program of China (Grant No. 2016YFA0401100).
Keywords: Compton camera, Timepix3, Electron track algorithm

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