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Paul R, Murali K, Chetia S, Varma HM. A simple algorithm for diffuse optical tomography without Jacobian inversion. Biomed Phys Eng Express 2022; 8. [PMID: 35447616 DOI: 10.1088/2057-1976/ac6909] [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: 03/02/2022] [Accepted: 04/21/2022] [Indexed: 11/11/2022]
Abstract
A computationally simpler algorithm to reconstruct the optical property distribution of turbid media using diffuse optical tomographic principles is presented. The proposed algorithm eliminates the requirement of large Jacobian matrix inversion which otherwise is essential for tomographic imaging. The most significant Jacobians are identified based on proper thresholding of the measurement and the intersection of these Jacobians gives the approximate spatial location of the inhomogeneity. The algorithm is tested and optimized using simulations and further validated using tissue-mimicking phantom-based experiments andin-vivosmall-animal experiments.
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Affiliation(s)
- Ria Paul
- Indian Institute of Technology Bombay (IITB), Mumbai-400076, India
| | - K Murali
- Indian Institute of Technology Bombay (IITB), Mumbai-400076, India
| | - Sumana Chetia
- Indian Institute of Technology Bombay (IITB), Mumbai-400076, India
| | - Hari M Varma
- Indian Institute of Technology Bombay (IITB), Mumbai-400076, India
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Doulgerakis M, Eggebrecht AT, Wojtkiewicz S, Culver JP, Dehghani H. Toward real-time diffuse optical tomography: accelerating light propagation modeling employing parallel computing on GPU and CPU. JOURNAL OF BIOMEDICAL OPTICS 2017; 22:1-11. [PMID: 29197176 PMCID: PMC5709934 DOI: 10.1117/1.jbo.22.12.125001] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/28/2017] [Accepted: 11/06/2017] [Indexed: 05/18/2023]
Abstract
Parameter recovery in diffuse optical tomography is a computationally expensive algorithm, especially when used for large and complex volumes, as in the case of human brain functional imaging. The modeling of light propagation, also known as the forward problem, is the computational bottleneck of the recovery algorithm, whereby the lack of a real-time solution is impeding practical and clinical applications. The objective of this work is the acceleration of the forward model, within a diffusion approximation-based finite-element modeling framework, employing parallelization to expedite the calculation of light propagation in realistic adult head models. The proposed methodology is applicable for modeling both continuous wave and frequency-domain systems with the results demonstrating a 10-fold speed increase when GPU architectures are available, while maintaining high accuracy. It is shown that, for a very high-resolution finite-element model of the adult human head with ∼600,000 nodes, consisting of heterogeneous layers, light propagation can be calculated at ∼0.25 s/excitation source.
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Affiliation(s)
- Matthaios Doulgerakis
- University of Birmingham, School of Computer Science, Birmingham, United Kingdom
- Address all correspondence to: Matthaios Doulgerakis, E-mail:
| | - Adam T. Eggebrecht
- Washington University School of Medicine, Department of Radiology, St. Louis, Missouri, United States
| | | | - Joseph P. Culver
- Washington University School of Medicine, Department of Radiology, St. Louis, Missouri, United States
- Washington University in St. Louis, Department of Biomedical Engineering, St. Louis, Missouri, United States
- Washington University School of Medicine, Division of Biology and Biomedical Sciences, St. Louis, Missouri, United States
| | - Hamid Dehghani
- University of Birmingham, School of Computer Science, Birmingham, United Kingdom
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Jia M, Jiang J, Ma W, Li C, Wang S, Zhao H, Gao F. Accelerating nonlinear reconstruction in laminar optical tomography by use of recursive SVD inversion. BIOMEDICAL OPTICS EXPRESS 2017; 8:4275-4293. [PMID: 28966864 PMCID: PMC5611940 DOI: 10.1364/boe.8.004275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/27/2017] [Revised: 08/21/2017] [Accepted: 08/28/2017] [Indexed: 06/07/2023]
Abstract
Image reconstruction in the most model-based biophotonic imaging modalities essentially poses an ill-posed nonlinear inverse problem, which has been effectively tackled in the diffusion-approximation-satisfied scenarios such as diffuse optical tomography. Nevertheless, a nonlinear implementation in high-resolution laminar optical tomography (LOT) is normally computationally-costly due to its strong dependency on a dense source-detector configuration and a physically-rigorous photon-transport model. To circumvent the adversity, we herein propose a practical nonlinear LOT approach to the absorption reconstruction. The scheme takes advantage of the numerical stability of the singular value decomposition (SVD) for the ill-posed linear inversion, and is accelerated by adopting an explicitly recursive strategy for the time-consuming repeated SVD inversion, which is based on a scaled expression of the sensitivity matrix. Experiments demonstrate that the proposed methodology can perform as well as the traditional nonlinear one, while the computation time of the former is merely 26.27% of the later on average.
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Affiliation(s)
- Mengyu Jia
- College of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin, 300072, China
| | - Jingying Jiang
- College of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin, 300072, China
| | - Wenjuan Ma
- Tianjin Medical University Cancer Institute & Hospital Tianjin, 300072, China
| | - Chenxi Li
- College of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin, 300072, China
| | - Shuang Wang
- College of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin, 300072, China
| | - Huijuan Zhao
- College of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin, 300072, China
| | - Feng Gao
- Tianjin Key Laboratory of Biomedical Detecting Techniques and Instruments, Tianjin, 300072, China
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Wu X, Eggebrecht AT, Ferradal SL, Culver JP, Dehghani H. Fast and efficient image reconstruction for high density diffuse optical imaging of the human brain. BIOMEDICAL OPTICS EXPRESS 2015; 6:4567-84. [PMID: 26601019 PMCID: PMC4646563 DOI: 10.1364/boe.6.004567] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/31/2015] [Revised: 10/14/2015] [Accepted: 10/16/2015] [Indexed: 05/18/2023]
Abstract
Real-time imaging of human brain has become an important technique within neuroimaging. In this study, a fast and efficient sensitivity map generation based on Finite Element Models (FEM) is developed which utilises a reduced sensitivitys matrix taking advantage of sparsity and parallelisation processes. Time and memory efficiency of these processes are evaluated and compared with conventional method showing that for a range of mesh densities from 50000 to 320000 nodes, the required memory is reduced over tenfold and computational time fourfold allowing for near real-time image recovery.
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Affiliation(s)
- Xue Wu
- School of Computer Science, University of Birmingham, Birmingham, B15 2TT, UK
| | - Adam T. Eggebrecht
- Department of Radiology, Washington University School of Medicine, 4525 Scott Avenue, St. Louis, MO, 63110, USA
| | - Silvina L. Ferradal
- Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Joseph P. Culver
- Department of Radiology, Washington University School of Medicine, 4525 Scott Avenue, St. Louis, MO, 63110, USA
- Department of Biomedical Engineering, Washington University, One Brookings Drive, St. Louis, MO, 63130, USA
| | - Hamid Dehghani
- School of Computer Science, University of Birmingham, Birmingham, B15 2TT, UK
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Yi X, Wang B, Wan W, Wang Y, Zhang Y, Zhao H, Gao F. Full time-resolved diffuse fluorescence tomography accelerated with parallelized Fourier-series truncated diffusion approximation. JOURNAL OF BIOMEDICAL OPTICS 2015; 20:56003. [PMID: 25965088 DOI: 10.1117/1.jbo.20.5.056003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/17/2014] [Accepted: 04/17/2015] [Indexed: 06/04/2023]
Abstract
Of the three measurement schemes established for diffuse fluorescence tomography (DFT), the time-domain scheme is well known to provide the richest information about the distribution of the targeting fluorophore in living tissues. However, the explicit use of the full time-resolved data usually leads to a considerably lengthy time for image reconstruction, limiting its applications to three-dimensional or small-volume imaging. To cope with the adversity, we propose herein a computationally efficient scheme for DFT image reconstruction where the time-dependent photon density is expanded to a Fourier-series and calculated by solving the independent frequency-domain diffusion equations at multiple sampling frequencies with the support of a combined multicore CPU-based coarse-grain and multithread GPU-based fine-grain parallelization strategy. With such a parallelized Fourier-series truncated diffusion approximation, both the time- and frequency-domain inversion procedures are developed and validated for their effectiveness and accuracy using simulative and phantom experiments. The results show that the proposed method can generate reconstructions comparable to the explicit time-domain scheme, with significantly reduced computational time.
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Affiliation(s)
- Xi Yi
- Tianjin University, College of Precision Instrument and Optoelectronics Engineering, Weijinlu Avenue #92, Tianjin 300072, China
| | - Bingyuan Wang
- Tianjin University, College of Precision Instrument and Optoelectronics Engineering, Weijinlu Avenue #92, Tianjin 300072, China
| | - Wenbo Wan
- Tianjin University, College of Precision Instrument and Optoelectronics Engineering, Weijinlu Avenue #92, Tianjin 300072, China
| | - Yihan Wang
- Tianjin University, College of Precision Instrument and Optoelectronics Engineering, Weijinlu Avenue #92, Tianjin 300072, China
| | - Yanqi Zhang
- Tianjin University, College of Precision Instrument and Optoelectronics Engineering, Weijinlu Avenue #92, Tianjin 300072, China
| | - Huijuan Zhao
- Tianjin University, College of Precision Instrument and Optoelectronics Engineering, Weijinlu Avenue #92, Tianjin 300072, ChinabTianjin Key Laboratory of Biomedical Detecting Techniques and Instruments, Tianjin 300072, China
| | - Feng Gao
- Tianjin University, College of Precision Instrument and Optoelectronics Engineering, Weijinlu Avenue #92, Tianjin 300072, ChinabTianjin Key Laboratory of Biomedical Detecting Techniques and Instruments, Tianjin 300072, China
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