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Lv T, Xu S, Wang Y, Zhang G, Niu T, Liu C, Sun B, Geng L, Zhu L, Zhao W. An indirect estimation of x-ray spectrum via convolutional neural network and transmission measurement. Phys Med Biol 2024; 69:115054. [PMID: 38722545 DOI: 10.1088/1361-6560/ad494f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2023] [Accepted: 05/09/2024] [Indexed: 05/31/2024]
Abstract
Objective.In this work, we aim to propose an accurate and robust spectrum estimation method by synergistically combining x-ray imaging physics with a convolutional neural network (CNN).Approach.The approach relies on transmission measurements, and the estimated spectrum is formulated as a convolutional summation of a few model spectra generated using Monte Carlo simulation. The difference between the actual and estimated projections is utilized as the loss function to train the network. We contrasted this approach with the weighted sums of model spectra approach previously proposed. Comprehensive studies were performed to demonstrate the robustness and accuracy of the proposed approach in various scenarios.Main results.The results show the desirable accuracy of the CNN-based method for spectrum estimation. The ME and NRMSE were -0.021 keV and 3.04% for 80 kVp, and 0.006 keV and 4.44% for 100 kVp, superior to the previous approach. The robustness test and experimental study also demonstrated superior performances. The CNN-based approach yielded remarkably consistent results in phantoms with various material combinations, and the CNN-based approach was robust concerning spectrum generators and calibration phantoms.Significance. We proposed a method for estimating the real spectrum by integrating a deep learning model with real imaging physics. The results demonstrated that this method was accurate and robust in estimating the spectrum, and it is potentially helpful for broad x-ray imaging tasks.
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Affiliation(s)
- Tie Lv
- School of Physics, Beihang University, Beijing, People's Republic of China
| | - Shouping Xu
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China
| | - Yanxin Wang
- School of Physics, Beihang University, Beijing, People's Republic of China
| | - Gaolong Zhang
- School of Physics, Beihang University, Beijing, People's Republic of China
| | - Tianye Niu
- Shenzhen Bay Laboratory, Shenzhen 518118, People's Republic of China
| | - Chunyan Liu
- Beijing WeMed Medical Equipment Co., Ltd, Beijing, People's Republic of China
| | - Baohua Sun
- School of Physics, Beihang University, Beijing, People's Republic of China
| | - Lisheng Geng
- School of Physics, Beihang University, Beijing, People's Republic of China
| | - Lihua Zhu
- School of Physics, Beihang University, Beijing, People's Republic of China
| | - Wei Zhao
- School of Physics, Beihang University, Beijing, People's Republic of China
- Zhongfa Aviation Institute, Beihang University, Hangzhou, People's Republic of China
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Ye P, Zhao W, Shimomura T, Li KW, Haga A, Geng LS. Pixel-by-pixel correction of beam hardening artifacts by bowtie filter in fan-beam CT. Phys Med Biol 2024; 69:105020. [PMID: 38640915 DOI: 10.1088/1361-6560/ad40fa] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Accepted: 04/19/2024] [Indexed: 04/21/2024]
Abstract
Objective. Beam hardening (BH) artifacts in computed tomography (CT) images originate from the polychromatic nature of x-ray photons. In a CT system with a bowtie filter, residual BH artifacts remain when polynomial fits are used. These artifacts lead to worse visuals, reduced contrast, and inaccurate CT numbers. This work proposes a pixel-by-pixel correction (PPC) method to reduce the residual BH artifacts caused by a bowtie filter.Approach. The energy spectrum for each pixel at the detector after the photons pass through the bowtie filter was calculated. Then, the spectrum was filtered through a series of water slabs with different thicknesses. The polychromatic projection corresponding to the thickness of the water slab for each detector pixel could be obtained. Next, we carried out a water slab experiment with a mono energyE= 69 keV to get the monochromatic projection. The polychromatic and monochromatic projections were then fitted with a 2nd-order polynomial. The proposed method was evaluated on digital phantoms in a virtual CT system and phantoms in a real CT machine.Main results. In the case of a virtual CT system, the standard deviation of the line profile was reduced by 23.8%, 37.3%, and 14.3%, respectively, in the water phantom with different shapes. The difference of the linear attenuation coefficients (LAC) in the central and peripheral areas of an image was reduced from 0.010 to 0.003cm-1and 0.007cm-1to 0 in the biological tissue phantom and human phantom, respectively. The method was also validated using CT projection data obtained from Activion16 (Canon Medical Systems, Japan). The difference in the LAC in the central and peripheral areas can be reduced by a factor of two.Significance. The proposed PPC method can successfully remove the cupping artifacts in both virtual and authentic CT images. The scanned object's shapes and materials do not affect the technique.
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Affiliation(s)
- Ping Ye
- School of Physics, Beihang University, Beijing 102206, People's Republic of China
| | - Wei Zhao
- School of Physics, Beihang University, Beijing 102206, People's Republic of China
- Hangzhou International Innovation Institute, Beihang University, Hangzhou 311115, People's Republic of China
| | - Taisei Shimomura
- Graduate School of Biomedical Sciences, Tokushima University, Tokushima 770-8503, Japan
| | - Kai-Wen Li
- Research and Development Department, CAS Ion Medical Technology Co., Ltd, Beijing 100190, People's Republic of China
| | - Akihiro Haga
- Graduate School of Biomedical Sciences, Tokushima University, Tokushima 770-8503, Japan
| | - Li-Sheng Geng
- School of Physics, Beihang University, Beijing 102206, People's Republic of China
- Beijing Key Laboratory of Advanced Nuclear Materials and Physics, Beihang University, Beijing 102206, People's Republic of China
- Peng Huanwu Collaborative Center for Research and Education, Beihang University, Beijing 100191, People's Republic of China
- Southern Center for Nuclear-Science Theory (SCNT), Institute of Modern Physics, Chinese Academy of Sciences, Huizhou 516000, People's Republic of China
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Richtsmeier D, Rodesch PA, Iniewski K, Bazalova-Carter M. Material decomposition with a prototype photon-counting detector CT system: expanding a stoichiometric dual-energy CT method via energy bin optimization and K-edge imaging. Phys Med Biol 2024; 69:055001. [PMID: 38306974 DOI: 10.1088/1361-6560/ad25c8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Accepted: 02/01/2024] [Indexed: 02/04/2024]
Abstract
Objective.Computed tomography (CT) has advanced since its inception, with breakthroughs such as dual-energy CT (DECT), which extracts additional information by acquiring two sets of data at different energies. As high-flux photon-counting detectors (PCDs) become available, PCD-CT is also becoming a reality. PCD-CT can acquire multi-energy data sets in a single scan by spectrally binning the incident x-ray beam. With this, K-edge imaging becomes possible, allowing high atomic number (high-Z) contrast materials to be distinguished and quantified. In this study, we demonstrated that DECT methods can be converted to PCD-CT systems by extending the method of Bourqueet al(2014). We optimized the energy bins of the PCD for this purpose and expanded the capabilities by employing K-edge subtraction imaging to separate a high-atomic number contrast material.Approach.The method decomposes materials into their effective atomic number (Zeff) and electron density relative to water (ρe). The model was calibrated and evaluated using tissue-equivalent materials from the RMI Gammex electron density phantom with knownρevalues and elemental compositions. TheoreticalZeffvalues were found for the appropriate energy ranges using the elemental composition of the materials.Zeffvaried slightly with energy but was considered a systematic error. Anex vivobovine tissue sample was decomposed to evaluate the model further and was injected with gold chloride to demonstrate the separation of a K-edge contrast agent.Main results.The mean root mean squared percent errors on the extractedZeffandρefor PCD-CT were 0.76% and 0.72%, respectively and 1.77% and 1.98% for DECT. The tissue types in theex vivobovine tissue sample were also correctly identified after decomposition. Additionally, gold chloride was separated from theex vivotissue sample with K-edge imaging.Significance.PCD-CT offers the ability to employ DECT material decomposition methods, along with providing additional capabilities such as K-edge imaging.
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Affiliation(s)
- Devon Richtsmeier
- Department of Physics and Astronomy, University of Victoria, 3800 Finnerty Road, Victoria, British Columbia V8P 5C2, Canada
| | - Pierre-Antoine Rodesch
- Department of Physics and Astronomy, University of Victoria, 3800 Finnerty Road, Victoria, British Columbia V8P 5C2, Canada
| | - Kris Iniewski
- Redlen Techologies, 1763 Sean Heights, Saanichton, British Columbia V8M 1X6, Canada
| | - Magdalena Bazalova-Carter
- Department of Physics and Astronomy, University of Victoria, 3800 Finnerty Road, Victoria, British Columbia V8P 5C2, Canada
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Haga A. Quantum annealing-based computed tomography using variational approach for a real-number image reconstruction. Phys Med Biol 2024; 69:04NT02. [PMID: 38252994 DOI: 10.1088/1361-6560/ad2155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 01/22/2024] [Indexed: 01/24/2024]
Abstract
Objective. Despite recent advancements in quantum computing, the limited number of available qubits has hindered progress in CT reconstruction. This study investigates the feasibility of utilizing quantum annealing-based computed tomography (QACT) with current quantum bit levels.Approach. The QACT algorithm aims to precisely solve quadratic unconstrained binary optimization problems. Furthermore, a novel approach is proposed to reconstruct images by approximating real numbers using the variational method. This approach allows for accurate CT image reconstruction using a small number of qubits. The study examines the impact of projection data quantity and noise on various image sizes ranging from 4 × 4 to 24 × 24 pixels. The reconstructed results are compared against conventional reconstruction algorithms, namely maximum likelihood expectation maximization (MLEM) and filtered back projection (FBP).Main result. By employing the variational approach and utilizing two qubits for each pixel of the image, accurate reconstruction was achieved with an adequate number of projections. Under conditions of abundant projections and lower noise levels, the image quality in QACT algorithm outperformed that of MLEM and FBP algorithms. However, in situations with limited projection data and in the presence of noise, the image quality in QACT was inferior to that in MLEM.Significance. This study developed the QACT reconstruction algorithm using the variational approach for real-number reconstruction. Remarkably, only 2 qubits were required for each pixel representation, demonstrating their sufficiency for accurate reconstruction.
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Affiliation(s)
- Akihiro Haga
- Graduate School of Biomedical Sciences, Tokushima University, Tokushima 770-8503, Japan
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