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Radiographic restoration technique based on a simple scatter-and-noise degradation model to enhance image visibility in cone-beam computed tomography systems using an offset detector

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JOURNAL OF INSTRUMENTATION 2025年第2期20卷 C02042-C02042页

作者： Park, Jiwon Jeon, Duhee Han, Seohee Kim, Woosung Park, Sungmin Cho, Hyosung Yonsei Univ Dept Radiat Convergence Engn Wonju 26493 South Korea

This study presents a novel radiographic restoration technique based on a simple scatter- and-noise degradation model to enhance image visibility in cone-beam computed tomography (CBCT) systems using an offset detector. This method aims to address the challenges of scatter and noise in CBCT images. It involves three main steps: estimating the scattering intensity and transmission function from the acquired projections, restoring projections by removing scatter and noise using the estimated quantities, and reconstructing the image using the standard filtered-backprojection algorithm. To verify the efficacy of the proposed method, we conducted an experiment on a commercially available test phantom using a tabletop setup of the micro-CT configuration, demonstrating significant improvements in key image quality metrics such as contrast-to-noise ratio (CNR), noise power spectrum (NPS), and modulation transfer function (MTF). The CNR value of the restored CBCT image was approximately 2.1, representing a 5.3-fold improvement over the original image;the NPS value evaluated at a spatial frequency of 3 lp/mm was approximately 4.2 x 105, 55.3 times smaller than that for the descattered image;and the spatial resolution evaluated at an MTF value of 0.1 was approximately 1.1 lp/mm, 8.4 times greater than that of the original. Accordingly, our experimental results demonstrate that the proposed method significantly enhances the visibility and quality of CBCT images. The method is entirely software-based, making it practical for implementation without requiring additional hardware or higher radiation doses.

关键词： medical-image reconstruction methods and algorithms computer-aided diagnosis computer-aided software X-ray radiography and digital radiography (DR)

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Background reduction in PET by double Compton scattering of quantum entangled annihilation photons

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JOURNAL OF INSTRUMENTATION 2023年第7期18卷 P07007页

作者： Kim, Donghwan Rachman, Agus Nur Taisei, Ueki Uenomachi, Mizuki Shimazoe, Kenji Takahashi, Hiroyuki Univ Tokyo Dept Nucl Engn & Management 7-3-1 Hongo Bunkyo City Tokyo 1138654 Japan Univ Tokyo Dept Bioengn 7-3-1 Hongo Bunkyo City Tokyo 1138654 Japan RIKEN Nishina Ctr Accelerator Based Sci 2-1 Hirosawa Wako Saitama 3510198 Japan

The reduction of background events, such as random and scatter events, can improve positron emission tomography (PET) images quantitatively. The quantum entanglement property of annihilation photons has been theoretically studied and experimentally validated. Recently, simulation studies on PET image reconstruction using the quantum entanglement property of annihilation photons and studies on the measurement of entanglement and polarization properties with scintillation crystal arrays demonstrated that PET images with less background can be achieved. This study utilized the quantum entanglement property of annihilation photons in a typical PET system with block detectors. A data acquisition method for quantum entanglement PET (QEPET) and system response modelling for QEPET image reconstruction were proposed and implemented. An experimental study was conducted using a small animal PET system composed of Ce:GAGG scintillation crystals whose dimensions are 2.5 x 2.5 x 4mm3. The diameter of the system was 79.3 mm. Signals from all individual crystals were processed parallelly and independently;thus, Compton scatter and absorption crystals within a module were obtained directly. The 28 MBq experiment result revealed the random background ratio of QEPET was approximately 20% lower than that of PET and the count rate of QEPET was approximately 0.1% that of PET. Evaluation on reconstructed images from the 28 MBq experiment revealed that the signal-to-background ratio of QEPET was approximately two times better than that of PET while the signal-to-noise ratio of QEPET was about 77% of that of PET. The method proposed in this study is expected to improve PET images with high background, such as those with a high activity and high background gamma rays and improve range verification in proton therapy.

关键词： Gamma camera SPECT PET PET/CT coronary CT angiography (CTA) medical-image reconstruction methods and algorithms computer-aided software

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Chest shape measurement by multi-sensors for pulmonary electrical impedance tomography

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JOURNAL OF INSTRUMENTATION 2023年第2期18卷 P02008页

作者： Liu, J. Z. Zhang, L. Y. Xiong, H. TianGong Univ Sch Control Sci & Engn Tianjin 300387 Peoples R China TianGong Univ Key Lab Intelligent Control Elect Equipment Tianjin 300387 Peoples R China

Electrical impedance tomography (EIT) has been gradually used in lung health detection. When the lungs are measured using EIT, the image quality is compromised by contour changes outside the thorax. In this paper, the shape measurement belts made by bend and inertial sensors are used to determine the specific information of the chest boundary of subjects. Three measurement belts are used to measure the chest cavity model. The measured model data are used to perform the simulation experiment of pulmonary EIT. The results indicate that the model measurement accuracy and the image accuracy are higher by the multi-sensor measurement belt. The multi -sensor measurement belt provides conditions for the wearable of pulmonary EIT equipment.

关键词： Bioinstrumentation medical-image reconstruction methods and algorithms computer-aided software computer-aided diagnosis Miniaturized sensory systems (MEMS microfluidics)

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DIDR-Net: a sparse-view CT deep iterative reconstruction network with an independent detail recovery network

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JOURNAL OF INSTRUMENTATION 2023年第5期18卷 P05038页

作者： Wang, Xiang He, Jichun Liu, Yi Zhang, Pengcheng Cheng, Weiting Wang, Bin Gui, Zhiguo North Univ China Sch Comp Sci & Technol Taiyuan Peoples R China Northeastern Univ Sch Med & Bioinformat Engn Shenyang Peoples R China North Univ China Sch Informat & Commun Engn Taiyuan Peoples R China

Sparse-view CT is an effective method to reduce X-ray radiation dose in clinical CT imaging. However, sparse view image reconstruction is still challenging due to highly undersampled data. To this end, we propose a new deep learning-based reconstruction model of CT images, called DIDR-Net. Unlike existing methods, DIDR-Net employs a dual network structure, including an iterative reconstruction sub-network and a detail recovery sub-network. The iterative reconstruction sub-network expands the FISTA (Fast Iterative Soft Thresholding Algorithm) into a deep network, utilizing learnable nonlinear sparse transform and shrinkage thresholding to improve reconstruction performance. To avoid loss of image details while removing artifacts, we design a detail recovery sub-network. Specifically, this sub-network captures the local details and global information of the initial image through local and global branches, and adaptively fuses the results of these two branches through a fusion module. DIDR-Net generates both the initial reconstruction map and the detail feature map in a parallel manner, and finally fuses the two sides to reconstruct a high-quality CT image. Experimental results on the AAPM public dataset show that DIDR-Net exhibits better performance in both streak artifact removal and detail structure preservation compared to other advanced reconstruction algorithms.

关键词： Computerized Tomography (CT) and Computed Radiography (CR) image reconstruc-tion in medical imaging medical-image reconstruction methods and algorithms computer-aided diagnosis

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Deformable 3D medical image registration with convolutional neural network and transformer

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JOURNAL OF INSTRUMENTATION 2023年第4期18卷 P04029页

作者： Deng, Liwei Zou, Yanchao Huang, Sijuan Yang, Xin Wang, Jing Harbin Univ Sci & Technol Sch Automation Xuefu Rd Harbin 150080 Peoples R China Sun Yat Sen Univ Canc Ctr Dept Radiat Oncol Dungfung Rd East Guangzhou 510060 Peoples R China South China Normal Univ Inst Brain Res & Rehabil Zhongshan Ave West Guangzhou 510631 Peoples R China

Deformable registration of medical images based on deep learning has been the research focus this year. Convolutional Neural Network (CNN) and the transformer are the most common backbone and have been shown to enhance registration accuracy. However, CNN lacks the ability to contact long-distance information, and the transformer lacks the ability to capture local information. Whichever subtle feature loss may lead to disastrous consequences in the analysis of clinical medicine. This paper presented a novel registration network named Information Complementation Network (ICN). We aim to improve the registration accuracy by complementing the lost information. Pure transformers can establish long-distance spatial information about the image. Proposed meshing patch embedding can minimize the loss of local information and expand the receptive field to extract long-distance information. The dual-path decoder in ICN is designed to restore information furthest. We experimented on 3D brain MRI data and quantitatively compared several excellent registration models. Compared with conventional methods, the dice coefficient increased by 3%. Compared with the advanced methods, the dice coefficient increased by 1%. The number of foldings was reduced by about 50% without any loss of registration accuracy. Each evaluation metric of the trained models on liver CT images was higher than other methods. By fully complementing the lost or invalid information, ICN achieved higher registration accuracy and smoother deformation field. The innovation and contribution of this paper have the potential to be applied to clinical research or medical image processing.

关键词： medical-image reconstruction methods and algorithms computer-aided diagnosis image processing MRI (whole body cardiovascular breast others) MR-angiography (MRA)

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Large-Area SiPM Pixels (LASiPs) in SPECT

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NUCLEAR INSTRUMENTS & methods IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT 2023年 1048卷

作者： Wunderlich, C. Guberman, D. Paoletti, R. Rugliancich, A. Passeri, A. Ist Nazl Fis Nucl INFN Sez Pisa Largo Bruno Pontecorvo 3 Edificio C I-56126 Pisa Italy Univ Siena Dipartimento Sci Fis Terra & Ambiente Via Roma 56 I-53100 Siena Italy Univ Barcelona UB Dept Fis Quant & Astrofis FQA Marti & Franques 1 Barcelona 08028 Spain Univ Barcelona UB Inst Ciencies Cosmos ICCUB Marti & Franques 1 Barcelona 08028 Spain Univ Firenze Dipartimento Sci Biomed Sperimentali & Clin SBSC Viale Morgagni 50 I-50134 Florence Italy

A standard camera for Single Photon Emission Computed Tomography (SPECT) contains 50-100 photomulti-plier tubes (PMTs). It is shielded by a thick layer of lead which makes it heavy and bulky. Its weight and size could be significantly reduced if replacing the PMTs by silicon photomultipliers (SiPMs). However, one would need a few thousands channels to fill a camera with SiPMs due to their small sensitive area. Alternatively, we propose to use Large-Area SiPM Pixels (LASiPs), built by summing individual currents of several SiPMs into a single output. We extended the simulation of a small camera employed with LASiPs that was presented in Guberman et al. (2021) to a large camera. The extension allowed us to study the feasibility of using larger LASiPs in a full-body SPECT camera. We found an intrinsic spatial resolution of-4 mm for a simulated pixel summing 25 SiPMs including SiPM noise at room temperature. Reducing the dark count rate (DCR) could improve the intrinsic spatial resolution to-3 mm.

关键词： Gamma camera SPECT PET PET CT coronary CT angiography (CTA) medical-image reconstruction methods and algorithms computer-aided diagnosis computer-aided software

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Preliminary study of integrated C-arm CT/SPECT imaging system for online adaptive 3D brachytherapy using Monte Carlo simulation

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JOURNAL OF INSTRUMENTATION 2023年第4期18卷 C04005-C04005页

作者： Lee, M. Lee, H. Seong, S. Park, H. Kim, H. Min, C. Choi, H. Choa, H. Yonsei Univ Dept Radiat Convergence Engn Wonju South Korea Yonsei Univ Wonju Severance Christian Hosp Dept Radiat Oncol Wonju Coll Med Wonju South Korea

Recent advancements in high-dose-rate brachytherapy have led to remarkable clinical outcomes. However, these new developments can cause unknown uncertainties with respect to actual dose delivery, which are yet to be clarified. Therefore, an accurate dose verification system is required. Currently, procedures for image-guided adaptive brachytherapy are constrained by the following limitations: (1) patient transportation between the treatment room and CT/MR (computerized tomography/magnetic resonance) imaging room can displace the application position, (2) the physiological and anatomical changes in the patient's body cannot be observed during the treatment schedule involving 3-10 fraction, and (3) the movement of the radioactive source inside the body is impossible to track. This study proposes a concept of an integrated online imaging system, which is based on integrated CT and single-photon emission computed tomography (SPECT), namely, the C-arm CT/SPECT system-a combination of a C-arm fluoro-scopic x-ray imaging system and an attachable parallel-hole collimator over the imaging detector. The Geant4 software is used to simulate the application of the C-arm CT/SPECT system for Ir-192-based brachytherapy in a pelvis-like phantom. To improve the image quality of C-arm CT/SPECT acquired with limited-angle information, we utilized an adaptive-steepest-descent -projection-onto-convex-sets framework that incorporates additional prior information for the proposed system. Furthermore, we confirmed that SPECT images can be obtained using a parallel -hole collimator and estimated the dose distribution in the medium and CT/SPECT fusion imaging during treatment. This strategy is expected to be effectively implemented in online image-guided adaptive brachytherapy and patient-dose verification.

关键词： Multi-modality systems Gamma camera SPECT medical-image reconstruction methods and algorithms C-arm online adaptive 3D brachytherapy

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Experiment and simulation of microwave detection using IQ demodulation method for breast tumor screening

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JOURNAL OF INSTRUMENTATION 2022年第3期17卷

作者： Li, C. P. Yao, Y. Li, Z. H. Cheng, L. Zhang, Y. Liu, H. Q. Lanzhou Univ Lanzhou 730000 Gansu Peoples R China Chinese Acad Sci Inst Plasma Phys Hefei 230031 Anhui Peoples R China Univ Sci & Technol China Hefei 230026 Anhui Peoples R China Hefei Comprehens Natl Sci Ctr Inst Energy Hefei 230071 Anhui Peoples R China

Breast cancer has become the most diagnosed cancer in the world. Microwave detection the breast tumor is attractive due to its high dielectric property contrast between different tissues of tumor. In this paper, we proposed an In-phase-Quadrature (IQ) demodulation-based method to detect the breast tumor with microwave at a frequency of 1.3 GHz. The microwave detection system consists of two signal generators, 12 transmitting/receiving antennas, two talent switches, a phantom and an IQ-Mixer. The amplitude information at the receiving antennas can be obtained by analyzing the difference frequency signals generated with two microwave signal generators. We also use the finite-difference time-domain (FDTD) method for simulation verification, which can simulate the propagation of the electromagnetic wave. Through experiments and simulations of microwave hardware system and FDTD method, it can be proved that the results are consistent. The experimental and simulation results show that when the tumor phantom diameter decreases or its depth from the receiving antenna increases, whether there is a tumor phantom can be clearly distinguished. Moreover, we also explore the effects of different tumor phantom locations on the receiving antennas. The results show that it is feasible to detect the breast tumor with the IQ demodulation method based on microwave.

关键词： medical-image reconstruction methods and algorithms computer-aided diagnosis Plasma diagnostics interferometry spectroscopy and imaging

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Depth resolved pencil beam radiography using AI - a proof of principle study

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JOURNAL OF INSTRUMENTATION 2022年第6期17卷 P06012页

作者： Haggstrom, I Carter, L. M. Fuchs, T. J. Kesner, A. L. Mem Sloan Kettering Canc Ctr Dept Radiol 1275 York Ave New York NY 10021 USA Mem Sloan Kettering Canc Ctr Dept Med Phys 1275 York Ave New York NY 10021 USA Mt Sinai Sch Med Hasso Plattner Inst Digital Hlth Dept Pathol 1468 Madison Ave New York NY USA

Aims: clinical radiographic imaging is seated upon the principle of differential keV photon transmission through an object. At clinical x-ray energies the scattering of photons causes signal noise and is utilized solely for transmission measurements. However, scatter ??? particularly Compton scatter, is characterizable. In this work we hypothesized that modern radiation sources and detectors paired with deep learning techniques can use scattered photon information constructively to resolve superimposed attenuators in planar x-ray imaging. methods: we simulated a monoenergetic x-ray imaging system consisting of a pencil beam x-ray source directed at an imaging target positioned in front of a high spatial-and energy-resolution detector array. The setup maximizes information capture of transmitted photons by measuring off-axis scatter location and energy. The signal was analyzed by a convolutional neural network, and a description of scattering material along the axis of the beam was derived. The system was virtually designed/tested using Monte Carlo processing of simple phantoms consisting of 10 pseudo-randomly stacked air/bone/water materials, and the network was trained by solving a classification problem. RESULTS: from our simulations we were able to resolve traversed material depth information to a high degree, within our simple imaging task. The average accuracy of the material identification along the beam was 0.91 ?? 0.01, with slightly higher accuracy towards the entrance/exit peripheral surfaces of the object. The average sensitivity and specificity was 0.91 and 0.95, respectively. Conclusions: our work provides proof of principle that deep learning techniques can be used to analyze scattered photon patterns which can constructively contribute to the information content in radiography, here used to infer depth information in a traditional 2D planar setup. This principle, and our results, demonstrate that there is information in Compton scattered photons, and

关键词： Compton imaging medical-image reconstruction methods and algorithms computer-aided diagnosis medical-image reconstruction methods and algorithms computer-aided software

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A new limited-angle CT reconstruction algorithm based on the local anisotropic total variation restoration of continuity

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JOURNAL OF INSTRUMENTATION 2022年第12期17卷 P12018页

作者： Xiao, Yu Zhong, Wang Li, Yongcun Hu, Xiaofang Xu, Feng Univ Sci & Technol China Chinese Acad Sci Key Lab Mech Behav & Design Mat 96 JinZhai Rd Hefei 230027 Peoples R China Taiyuan Univ Technol Coll Mech Shanxi Key Lab Mat Strength & Struct Impact 79 Yingzexi Dajie Taiyuan 030024 Peoples R China

A new limited-angle computed tomography(CT) reconstruction algorithm based on local detail information restoration in the CT image projection domain was proposed in this paper. The lost projection information could be repaired with the new algorithm called local anisotropic total variation repair method of sinogram (LATV). According to the continuity of local gradient in sinogram, local high frequency characteristics can be improved which are blurred by conventional TVM. A series of numerical reconstruction experiments were conducted to validate the new algorithm. The overall quality of images reconstructed by new algorithm was better than conventional TVM algorithm when quantitatively evaluated. Then, a local region with rich details was selected in order to evaluate the reconstruction effect of the internal details. From the perspective of three image quality evaluation parameters, it was shown that the local high frequency details were well repaired. Finally, the reconstruction quality was evaluated by actual CT experimental data. The new method also performed better than conventional method. Therefore, the new LATV algorithm proposed in this paper may be a new method suitable for limited-angle CT reconstruction problems.

关键词： Computerized Tomography (CT) and Computed Radiography (CR) image reconstruc-tion in medical imaging medical-image reconstruction methods and algorithms computer-aided diagnosis

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