1
|
Kumari K, Goswami M. Gamma radiation detector selection for CT scanner. Z Med Phys 2023:S0939-3889(23)00088-0. [PMID: 37586961 DOI: 10.1016/j.zemedi.2023.07.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 06/16/2023] [Accepted: 07/24/2023] [Indexed: 08/18/2023]
Abstract
Three types of gamma radiation detectors associated with distributed electronics namely, NaI (Tl), HPGe and LaBr3(Ce) are compared primarily focusing on electronic noise and scattering noise. Additionally, detectors of same make, material, size and electronics are also compared. A methodology is proposed to select the most suitable detector for computed tomography (CT) among the available options. Standard deviation parameter is employed to estimate electronic noise without performing CT experiment. Kanpur theorem-1(KT-1) is used to estimate the scattering noise quantitatively after verifying its sensitivity to scattering noise. The impact of scattering noise on CT profiles is evaluated using dice similarity dice coefficient. A good resemblance between KT-1 and dice coefficient is observed. A maximum difference of 56% in scattering noise is observed when five detectors used simultaneously instead of single detector whereas a discrepancy of 85% is observed between different types of radiation detectors. As far as ease of handling, operational and capital cost is concern one has to compromise minimum 12% of accuracy in CT reconstruction if NaI (Tl) detector is used with respect to best alternative available. The proposed methodology can be applied to measurement that require minimal scattering interference data other than CT experiments. The manufacturer can add noise level of detector as a characteristic parameter in the data sheet.
Collapse
Affiliation(s)
- Kajal Kumari
- Divyadrishti Imaging Laboratory, Department of Physics, IIT Roorkee, Roorkee, India
| | - Mayank Goswami
- Divyadrishti Imaging Laboratory, Department of Physics, IIT Roorkee, Roorkee, India.
| |
Collapse
|
2
|
Anam C, Triadyaksa P, Naufal A, Arifin Z, Muhlisin Z, Setiawati E, Budi WS. Impact of ROI Size on the Accuracy of Noise Measurement in CT on Computational and ACR Phantoms. J Biomed Phys Eng 2022; 12:359-368. [PMID: 36059282 PMCID: PMC9395624 DOI: 10.31661/jbpe.v0i0.2202-1457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Accepted: 03/15/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND The effect of region of interest (ROI) size variation on producing accurate noise levels is not yet studied. OBJECTIVE This study aimed to evaluate the influence of ROI sizes on the accuracy of noise measurement in computed tomography (CT) by using images of a computational and American College of Radiology (ACR) phantoms. MATERIAL AND METHODS In this experimental study, two phantoms were used, including computational and ACR phantoms. A computational phantom was developed by using Matlab R215a software (Mathworks Inc., Natick, MA Natick, MA) with a homogeneously +100 Hounsfield Unit (HU) value and an added-Gaussian noise with various levels of 5, 10, 25, 50, 75, and 100 HU. The ACR phantom was scanned with a Philips MX-16 slice CT scanner in different slice thicknesses of 1.5, 3, 5, and 7 mm to obtain noise variation. Noise measurement was conducted at the center of the phantom images and four locations close to the edge of the phantom images using different ROI sizes from 3 × 3 to 41 × 41 pixels, with an increased size of 2 × 2 pixels. RESULTS The use of a minimum ROI size of 21 × 21 pixels shows noise in the range of ± 5% ground truth noise. The measured noise increases above the ± 5% range if the used ROI is smaller than 21 × 21 pixels. CONCLUSION A minimum acceptable ROI size is required to maintain the accuracy of noise measurement with a size of 21 × 21 pixels.
Collapse
Affiliation(s)
- Choirul Anam
- PhD, Department of Physics, Faculty of Sciences and Mathematics, Diponegoro University, Jl. Prof. Soedarto SH, Tembalang, Semarang 50275, Central Java, Indonesia
| | - Pandji Triadyaksa
- PhD, Department of Physics, Faculty of Sciences and Mathematics, Diponegoro University, Jl. Prof. Soedarto SH, Tembalang, Semarang 50275, Central Java, Indonesia
| | - Ariij Naufal
- MSc, Department of Physics, Faculty of Sciences and Mathematics, Diponegoro University, Jl. Prof. Soedarto SH, Tembalang, Semarang 50275, Central Java, Indonesia
| | - Zaenal Arifin
- MSc, Department of Physics, Faculty of Sciences and Mathematics, Diponegoro University, Jl. Prof. Soedarto SH, Tembalang, Semarang 50275, Central Java, Indonesia
| | - Zaenul Muhlisin
- MSc, Department of Physics, Faculty of Sciences and Mathematics, Diponegoro University, Jl. Prof. Soedarto SH, Tembalang, Semarang 50275, Central Java, Indonesia
| | - Evi Setiawati
- MSc, Department of Physics, Faculty of Sciences and Mathematics, Diponegoro University, Jl. Prof. Soedarto SH, Tembalang, Semarang 50275, Central Java, Indonesia
| | - Wahyu Setia Budi
- PhD, Department of Physics, Faculty of Sciences and Mathematics, Diponegoro University, Jl. Prof. Soedarto SH, Tembalang, Semarang 50275, Central Java, Indonesia
| |
Collapse
|
3
|
Wu P, Boone JM, Hernandez AM, Mahesh M, Siewerdsen JH. Theory, method, and test tools for determination of 3D MTF characteristics in cone-beam CT. Med Phys 2021; 48:2772-2789. [PMID: 33660261 DOI: 10.1002/mp.14820] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Revised: 02/19/2021] [Accepted: 02/23/2021] [Indexed: 11/11/2022] Open
Abstract
PURPOSE The modulation transfer function (MTF) is widely used as an objective metric of spatial resolution of medical imaging systems. Despite advances in capability for three-dimensional (3D) isotropic spatial resolution in computed tomography (CT) and cone-beam CT (CBCT), MTF evaluation for such systems is typically reported only in the axial plane, and practical methodology for assessment of fully 3D spatial resolution characteristics is lacking. This work reviews fundamental theoretical relationships of two-dimensional (2D) and 3D spread functions and reports practical methods and test tools for analysis of 3D MTF in CBCT. METHODS Fundamental aspects of 2D and 3D MTF measurement are reviewed within a common notational framework, and three MTF test tools with analysis code are reported and made available online (https://istar.jhu.edu/downloads/): (a) a multi-wire tool for measurement of the axial plane MTF [denoted as M T F ( f r ; φ = 0 ∘ ) , where φ is the measurement angle out of the axial plane] as a function of position in the axial plane; (b) a wedge tool for measurement of the MTF in any direction in the 3D Fourier domain [e.g., φ = 45°, denoted as M T F ( f r ; φ = 45 ∘ ) ]; and (c) a sphere tool for measurement of the MTF in any or all directions in the 3D Fourier domain. Experiments were performed on a mobile C-arm with CBCT capability, showing that M T F ( f r ; φ = 45 ∘ ) yields an informative one-dimensional (1D) representation of the overall 3D spatial resolution characteristics, capturing important characteristics of the 3D MTF that might be missed in conventional analysis. The effects of anisotropic filters and detector readout mode were investigated, and the extent to which a system can be said to provide "isotropic" resolution was evaluated by quantitative comparison of MTF at various φ . RESULTS All three test tools provided consistent measurement of M T F ( f r ; φ = 0 ∘ ) , and the wedge and sphere tools demonstrated how measurement of the MTF in directions outside the axial plane ( φ > 0 ∘ ) can reveal spatial resolution characteristics to which conventional axial MTF measurement is blind. The wedge tool was shown to reduce statistical measurement error compared to the sphere tool due to improved sampling, and the sphere tool was shown to provide a basis for measurement of the MTF in any or all directions (outside the null cone) from a single scan. The C-arm system exhibited non-isotropic spatial resolution with conventional non-isotropic 1D apodization filters (i.e., frequency cutoff filters) - which is common in CBCT - and implementation of isotropic 2D apodization yielded quantifiably isotropic MTF. Asymmetric pixel binning modes were similarly shown to impart non-isotropic effects on the 3D MTF, and the overall 3D MTF characteristics were evident in each case with a single, 1D measurement of the 1D M T F ( f r ; φ = 45 ∘ ). CONCLUSION Three test tools and corresponding MTF analysis methods were presented within a consistent framework for analysis of 3D spatial resolution characteristics in a manner amenable to routine, practical measurements. Experiments on a CBCT C-arm validated many intuitive aspects of 3D spatial resolution and quantified the extent to which a CBCT system may be considered to have isotropic resolution. Measurement of M T F ( f r ; φ = 45 ∘ ) provided a practical 1D measure of the underlying 3D MTF characteristics and is extensible to other CT or CBCT systems offering high, isotropic spatial resolution.
Collapse
Affiliation(s)
- Pengwei Wu
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, 21205, USA
| | - John M Boone
- Department of Radiology, University of California, Davis, Davis, CA, 95616, USA
| | - Andrew M Hernandez
- Department of Radiology, University of California, Davis, Davis, CA, 95616, USA
| | - Mahadevappa Mahesh
- Department of Radiology, Johns Hopkins University, Baltimore, MD, 21205, USA
| | - Jeffrey H Siewerdsen
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, 21205, USA.,Department of Radiology, Johns Hopkins University, Baltimore, MD, 21205, USA
| |
Collapse
|
4
|
Sisniega A, Stayman JW, Capostagno S, Weiss CR, Ehtiati T, Siewerdsen JH. Accelerated 3D image reconstruction with a morphological pyramid and noise-power convergence criterion. Phys Med Biol 2021; 66:055012. [PMID: 33477131 DOI: 10.1088/1361-6560/abde97] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Model-based iterative reconstruction (MBIR) for cone-beam CT (CBCT) offers better noise-resolution tradeoff and image quality than analytical methods for acquisition protocols with low x-ray dose or limited data, but with increased computational burden that poses a drawback to routine application in clinical scenarios. This work develops a comprehensive framework for acceleration of MBIR in the form of penalized weighted least squares optimized with ordered subsets separable quadratic surrogates. The optimization was scheduled on a set of stages forming a morphological pyramid varying in voxel size. Transition between stages was controlled with a convergence criterion based on the deviation between the mid-band noise power spectrum (NPS) measured on a homogeneous region of the evolving reconstruction and that expected for the converged image, computed with an analytical model that used projection data and the reconstruction parameters. A stochastic backprojector was developed by introducing a random perturbation to the sampling position of each voxel for each ray in the reconstruction within a voxel-based backprojector, breaking the deterministic pattern of sampling artifacts when combined with an unmatched Siddon forward projector. This fast, forward and backprojector pair were included into a multi-resolution reconstruction strategy to provide support for objects partially outside of the field of view. Acceleration from ordered subsets was combined with momentum accumulation stabilized with an adaptive technique that automatically resets the accumulated momentum when it diverges noticeably from the current iteration update. The framework was evaluated with CBCT data of a realistic abdomen phantom acquired on an imaging x-ray bench and with clinical CBCT data from an angiography robotic C-arm (Artis Zeego, Siemens Healthineers, Forchheim, Germany) acquired during a liver embolization procedure. Image fidelity was assessed with the structural similarity index (SSIM) computed with a converged reconstruction. The accelerated framework provided accurate reconstructions in 60 s (SSIM = 0.97) and as little as 27 s (SSIM = 0.94) for soft-tissue evaluation. The use of simple forward and backprojectors resulted in 9.3× acceleration. Accumulation of momentum provided extra ∼3.5× acceleration with stable convergence for 6-30 subsets. The NPS-driven morphological pyramid resulted in initial faster convergence, achieving similar SSIM with 1.5× lower runtime than the single-stage optimization. Acceleration of MBIR to provide reconstruction time compatible with clinical applications is feasible via architectures that integrate algorithmic acceleration with approaches to provide stable convergence, and optimization schedules that maximize convergence speed.
Collapse
Affiliation(s)
- A Sisniega
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD United States of America
| | | | | | | | | | | |
Collapse
|
5
|
Wu P, Sisniega A, Stayman JW, Zbijewski W, Foos D, Wang X, Khanna N, Aygun N, Stevens RD, Siewerdsen JH. Cone-beam CT for imaging of the head/brain: Development and assessment of scanner prototype and reconstruction algorithms. Med Phys 2020; 47:2392-2407. [PMID: 32145076 PMCID: PMC7343627 DOI: 10.1002/mp.14124] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2019] [Revised: 02/06/2020] [Accepted: 02/21/2020] [Indexed: 01/14/2023] Open
Abstract
PURPOSE Our aim was to develop a high-quality, mobile cone-beam computed tomography (CBCT) scanner for point-of-care detection and monitoring of low-contrast, soft-tissue abnormalities in the head/brain, such as acute intracranial hemorrhage (ICH). This work presents an integrated framework of hardware and algorithmic advances for improving soft-tissue contrast resolution and evaluation of its technical performance with human subjects. METHODS Four configurations of a CBCT scanner prototype were designed and implemented to investigate key aspects of hardware (including system geometry, antiscatter grid, bowtie filter) and technique protocols. An integrated software pipeline (c.f., a serial cascade of algorithms) was developed for artifact correction (image lag, glare, beam hardening and x-ray scatter), motion compensation, and three-dimensional image (3D) reconstruction [penalized weighted least squares (PWLS), with a hardware-specific statistical noise model]. The PWLS method was extended in this work to accommodate multiple, independently moving regions with different resolution (to address both motion compensation and image truncation). Imaging performance was evaluated quantitatively and qualitatively with 41 human subjects in the neurosciences critical care unit (NCCU) at our institution. RESULTS The progression of four scanner configurations exhibited systematic improvement in the quality of raw data by variations in system geometry (source-detector distance), antiscatter grid, and bowtie filter. Quantitative assessment of CBCT images in 41 subjects demonstrated: ~70% reduction in image nonuniformity with artifact correction methods (lag, glare, beam hardening, and scatter); ~40% reduction in motion-induced streak artifacts via the multi-motion compensation method; and ~15% improvement in soft-tissue contrast-to-noise ratio (CNR) for PWLS compared to filtered backprojection (FBP) at matched resolution. Each of these components was important to improve contrast resolution for point-of-care cranial imaging. CONCLUSIONS This work presents the first application of a high-quality, point-of-care CBCT system for imaging of the head/ brain in a neurological critical care setting. Hardware configuration iterations and an integrated software pipeline for artifacts correction and PWLS reconstruction mitigated artifacts and noise to achieve image quality that could be valuable for point-of-care detection and monitoring of a variety of intracranial abnormalities, including ICH and hydrocephalus.
Collapse
Affiliation(s)
- P Wu
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, 21205, USA
| | - A Sisniega
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, 21205, USA
| | - J W Stayman
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, 21205, USA
| | - W Zbijewski
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, 21205, USA
| | - D Foos
- Carestream Health, Rochester, NY, 14608, USA
| | - X Wang
- Carestream Health, Rochester, NY, 14608, USA
| | - N Khanna
- Department of Radiology, Johns Hopkins University, Baltimore, MD, 21205, USA
| | - N Aygun
- Department of Radiology, Johns Hopkins University, Baltimore, MD, 21205, USA
| | - R D Stevens
- Department of Radiology, Johns Hopkins University, Baltimore, MD, 21205, USA
- Department of Anesthesiology and Critical Care Medicine, Johns Hopkins University, Baltimore, MD, 21205, USA
- Department of Neurology, Johns Hopkins University, Baltimore, MD, 21205, USA
- Department of Neurosurgery, Johns Hopkins University, Baltimore, MD, 21205, USA
| | - J H Siewerdsen
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, 21205, USA
- Department of Radiology, Johns Hopkins University, Baltimore, MD, 21205, USA
- Department of Neurosurgery, Johns Hopkins University, Baltimore, MD, 21205, USA
| |
Collapse
|