arXiv subjects

Hamid Sabet

Publications and source records attributed to Hamid Sabet.

11 recordsLinked to original sources

arXiv2026

Novel Asymmetrical High-Resolution and High-Sensitivity Brain Dedicated PET system: Design optimization and performance evaluation

Objective. This study investigates the best achievable performance of a brain-dedicated PET system with high resolution and sensitivity by evaluating different detector configurations, while maintaining a practical system design suitable for dynamic brain Imaging. Approach. Monte Carlo simulations were performed to evaluate system sensitivity and image quality under various timing resolutions (200 ps, 100 ps and 50 ps). The PET scanner geometry was optimized for human head imaging, featuring an elliptical cylindrical configuration with a neck cut-out, and front/back panels to enhance sensitivity and line of response (LOR) sampling. Detector configurations using LYSO:Ce crystals of varying thicknesses (15 mm and 20 mm) and depth of interaction (DOI) levels were simulated. Sensitivity was calculated using a point-like 511 keV back-to-back gamma source simulated at multiple locations within the field of view (FOV). Image reconstruction was conducted using list mode Maximum Likelihood Expectation Maximization (MLEM), assessing both a Derenzo-type phantom and a voxelated digital brain phantom. Main results. A location-dependent sensitivity ranging from 35.04% to 13.59% was achieved using a 20 mm thick LYSO:Ce crystal. Spatial resolution ranged from 0.8 mm to 1.5 mm within the FOV without applying resolution recovery techniques, measured using the FWHM of reconstructed hot rods. Previous results using 15 mm crystals with three DOI levels showed sensitivity between 23.42% and 15.99%, confirming the performance benefits of increased detector thickness and DOI capability. Significance. This study demonstrates the potential of a practical, brain-optimized PET system to achieve superior resolution and sensitivity for brain imaging. The findings offer valuable insights into optimal detector configurations, supporting the development of next-generation high-performance brain PET technologies.

physics.med-ph↗

arXiv2026

Maximum-Likelihood--Based Position Decoding of Laser Processed Converging Pixel CsI: Tl Detectors for High-Resolution SPECT

This study demonstrates the feasibility of a novel fabrication technique for high spatial resolution CsI: Tl scintillation detectors tailored for single photon emission computed tomography (SPECT) systems. Building upon our previously developed laser induced optical barrier (LIOB) method, which achieved high spatial resolution, excellent sensitivity, and 100% fabrication yield in CsI: Tl detectors, we extend this approach to a converging-pixel architecture. A CsI: Tl crystal array with converging pixels was designed and fabricated, featuring entrance-face pixels of 1.6x1.6 mm2 and photodetector side pixels of 2x2 mm2. To localize gamma-ray interactions, both the center of gravity (CoG) algorithm and a maximum-likelihood (ML) based decoding method were implemented. A custom built four axis motion platform was developed to deliver a finely collimated pencil beam at precisely controlled positions and angles across the array, enabling generation of a comprehensive dataset for prior knowledge and validation. The results demonstrate an energy resolution of 11.79+/-0.53% (collimated experiment) and a position localization accuracy of 1.00+/-0.42 mm (nearest neighbor interpolation), confirming that the proposed converging-pixel architecture, combined with statistical decoding algorithms, provides a promising path toward the development of high-performance SPECT detectors.

physics.med-ph↗

arXiv2025

Towards Integrated Clinical-Computational Nuclear Medicine

The field of Clinical-Computational Nuclear Medicine is rapidly advancing, fueled by AI, tracer kinetic modeling, radiomics, and integrated informatics. These technologies improve imaging quality, automate lesion detection, and enable personalized radiopharmaceutical therapy through physiologically based pharmacokinetic (PBPK) modeling and voxel-level dosimetry. Workflow automation and Natural Language Processing (NLP) further enhance operational efficiency. However, successful implementation and adoption of these tools require clinical oversight to ensure accuracy, interpretability, and patient safety. This paper highlights key computational innovations and emphasizes the critical role of clinician-guided evaluation in shaping the future of precision imaging and therapy.

physics.med-ph↗

arXiv2024

Flexible and Generic Framework for Complex Nuclear Medicine Scanners using FreeCAD/GDML Workbench

The design of nuclear imaging scanners is crucial for optimizing detection and imaging processes. While advancements have been made in simplistic, symmetrical modalities, current research is progressing towards more intricate structures, however, the widespread adoption of computer-aided design (CAD) tools for modeling and simulation is still limited. This paper introduces FreeCAD and the GDML Workbench as essential tools for designing and testing complex geometries in nuclear imaging modalities. FreeCAD is a parametric 3D CAD modeler, and GDML is an XML-based language for describing complex geometries in simulations. Their integration streamlines the design and simulation of nuclear medicine scanners, including PET and SPECT scanners. The paper demonstrates their application in creating calibration phantoms and conducting simulations with Geant4, showcasing their precision and versatility in generating sophisticated components for nuclear imaging. The integration of these tools is expected to streamline design processes, enhance efficiency, and facilitate widespread application in the nuclear imaging field.

physics.med-ph↗

arXiv2024

Collimator-less SPECT System Design for Dynamic Whole-body Imaging

In this study, we introduce a Compton SPECT system for whole-body imaging of Actinium-225 (225Ac), one of the trending radionuclides for targeted alpha therapy (TAT). The Compton SPECT system enables multi-energy gamma photon detection with higher efficiency compared to mechanically collimated SPECT. The system consists of two detectors, providing a field of view (FOV) adequate for whole-body imaging, while achieving high sensitivity and clinically usable imaging resolution within a reasonable scanning time. This work focuses on the system design and evaluation using the Monte Carlo simulation toolkit Gate. The imaging performance is evaluated at two energy peaks (218 keV, 440 keV), representing the major detectable gamma energies generated from 225Ac. We explore the possibility of using the Compton SPECT system for treatment response monitoring in TAT. Results demonstrate an image resolution of 1.0 cm using a NEMA IQ phantom with 5.7 MBq of 225Ac simulated in a cold background. An image resolution of 1.3 cm can be achieved with a hot to background ratio of 30:1, and a resolution of 3.7 cm can be achieved with an activity ratio of 12:1. The best achievable sensitivity at 10 cm distance to the detector is 0.5% with the two energy windows (211-225 keV, 430-450 keV) selected. The proposed system may serve as an alternative imaging tool for TAT scanning in clinical settings.

physics.med-ph↗

arXiv2024

A novel perspective on denoising using quantum localization with application to medical imaging

Background noise in many fields such as medical imaging poses significant challenges for accurate diagnosis, prompting the development of denoising algorithms. Traditional methodologies, however, often struggle to address the complexities of noisy environments in high dimensional imaging systems. This paper introduces a novel quantum-inspired approach for image denoising, drawing upon principles of quantum and condensed matter physics. Our approach views medical images as amorphous structures akin to those found in condensed matter physics and we propose an algorithm that incorporates the concept of mode resolved localization directly into the denoising process. Notably, unlike previous studies that considered localization as a hindrance, our approach considers quantum localization as a fundamental component of image reconstruction which is used to differentiate between noisy and non-noisy modes based on diffusivity and localization measurements. This perspective eliminates the need for hyperparameter tuning, making the proposed method a standalone algorithm which can be implemented with minimal manual intervention and can perform automatic filtering of noise regardless of noise level. Through numerical validation, we showcase the effectiveness of our approach in addressing noise-related challenges in imaging and especially medical imaging, underscoring its relevance for possible quantum computing applications.

eess.IV↗

arXiv2024

Limited-angle TOF-PET for intraoperative surgical applications: Simulation Study

In this work, we present modeling and imaging performance of a dual panel limited-angle TOF-PET system for intraoperative surgical applications using GATE monte carlo toolkit. Several detector parameters such as detector pixel dimensions, timing resolution and depth of interaction resolution along with tumor uptake ratio and phantom dimension are varied. Ultimately TOF-PET detector properties to achieve a specific imaging task are presented. To assess image resolution, we employed Simple Back Projection (SBP) reconstruction due to its fast speed compared to list-mode Maximum Likelihood Expectation Maximization (MLEM). We evaluated the quality of the reconstructed images using metrics contrast-to-noise ratio (CNR), contrast recovery coefficient (CRC), and signal-to-noise ratio (SNR). The purpose is to show effects of different detector parameters on the resolution of reconstructed images.

physics.med-ph↗

arXiv2023

Application of Spherical Convolutional Neural Networks to Image Reconstruction and Denoising in Nuclear Medicine

This work investigates use of equivariant neural networks as efficient and high-performance frameworks for image reconstruction and denoising in nuclear medicine. Our work aims to tackle limitations of conventional Convolutional Neural Networks (CNNs), which require significant training. We investigated equivariant networks, aiming to reduce CNN's dependency on specific training sets. Specifically, we implemented and evaluated equivariant spherical CNNs (SCNNs) for 2- and 3-dimensional medical imaging problems. Our results demonstrate superior quality and computational efficiency of SCNNs in both image reconstruction and denoising benchmark problems. Furthermore, we propose a novel approach to employ SCNNs as a complement to conventional image reconstruction tools, enhancing the outcomes while reducing reliance on the training set. Across all cases, we observed significant decrease in computational cost by leveraging the inherent inclusion of equivariant representatives while achieving the same or higher quality of image processing using SCNNs compared to CNNs. Additionally, we explore the potential of SCNNs for broader tomography applications, particularly those requiring rotationally variant representation.

eess.IV↗

arXiv2023

Controlling solar radiation forces with graphene in plasmonic metasurface

Controlling and harvesting solar radiation pressure is a significant challenge, however, there are few potential solutions, which are suitable for several key applications. In this study, an electrically tunable plasmonic metasurface is designed for the visible spectrum. Moreover, the normal and the tangential optical forces acting on the metasurface are calculated. Whilst presenting high efficiency in the anomalous reflection, the designed active metasurface provides tunability of optical forces acting on the metasurface. The metasurface is composed of tapered silver cells embedded on top of the graphene layer with 20 layers of graphene sheets. Hence, by tuning the Fermi level of graphene sheets, the transferred momentum to the metasurface can be controlled. Our results can provide a suitable platform for optical force control desired in tunable radiation pressure harvesting, micro vehicles, solar sailing and optical tweezers.

physics.optics↗

arXiv2022

Resolution recovery on list mode MLEM reconstruction for Dynamic Cardiac SPECT system

The Dynamic Cardiac SPECT (DC-SPECT) system is being developed at the Massachusetts General Hospital, featuring a static cardio focus asymmetrical geometry enabling simultaneous high resolution and high sensitivity imaging. Among 14 design iterations of the DC-SPECT with varying number of detector heads, system sensitivity and system resolution, the current version being fabricated features 10 mm FWHM geometrical resolution (without resolution recovery) and 0.07% sensitivity; this is 1.5x resolution gain and 7x sensitivity gain compared to a conventional dual head gamma camera. This work presents improvement in imaging resolution by implementing a spatially variant point spread function (SV-PSF) with list mode MLEM reconstruction. A resolution recovery method by PSF deconvolution is validated on list mode MLEM reconstruction for DC-SPECT. A spatial invariant PSF is included as an additional test to show the influence of the accuracy of PSF modelling on the reconstructed image quality. We compare the MLEM reconstruction with and without PSF deconvolution; an analytic model is used for the calculation of system response, and the results are compared to Monte Carlo (MC) based methods. Results show that with PSF modelling applied, the quality of the reconstructed image is improved, and the DC-SPECT system can achieve a 4.5 mm central spatial resolution with average 795 counts/(s*Mbq). The results show substantial improvement over the gold standard GE Discovery 570c performance (spatial resolution 7 mm with an average 460 counts/s*MBq, central resolution 5.8 mm). The impact of PSF deconvolution is significant, and the improvements of the reconstructed image quality is more evident compared to MC simulated system matrix with the same sampling size as in simulation.

physics.med-ph↗

arXiv2018

Simulation study of light transport in laser-processed LYSO:Ce detectors with single-side readout

A tightly focused pulsed laser can locally modify the crystal structure inside the bulk of a scintillator. The result is incorporation of so-called optical barriers with a refractive index (RI) different from that of the crystal bulk, that can be used to redirect the scintillation light and control the light spread in the detector. We systematically study the scintillation light transport in detectors fabricated using the Laser Induced Optical Barrier technique, and objectively compare their potential performance characteristics with the two mainstream detector types: monolithic and mechanically pixelated arrays. Among countless optical barrier patterns, we explore barriers arranged in a pixel-like pattern extending all-way or half-way through a 20 mm thick LYSO:Ce crystal. We analyze the performance of the detectors coupled to MPPC arrays, in terms of light response functions, position histograms, line profiles, and light collection efficiency. Our results show that laser-processed detectors constitute a new detector category with a behavior between the two standard detector types. When the barrier-crystal interface is smooth, no DOI information can be obtained regardless of barrier RI. However, with a rough barrier-crystal interface we can extract multiple DOI levels. Lower barrier RI results in larger light confinement, leading to better transverse resolution. Laser-processed crystals can also potentially increase the light collection efficiency, which could lead to improved energy resolution and timing resolution due to higher signals. For a laser-processed detector with smooth barrier-crystal interfaces the light collection efficiency is simulated to >44%, and for rough interfaces >73%. The numbers for a monolithic crystal is 39% with polished surfaces, and 71% with rough surfaces, and for a mechanically pixelated array 33% with polished pixel surfaces and 51% with rough surfaces.

physics.med-ph↗