In this study, we intend to use diffuse optical tomography dot as a noninvasive, safe and low cost technique that can be considered as a functional imaging method and mention the importance of image reconstruction in accuracy and procession of image. Models and algorithms for diffuse optical tomographic system. Image reconstruction in diffuse optical tomography based. The algorithm is robust against the choice of initial guesses. In diffuse optical imaging, the resolution is in general low. Introduction the diffuse optical tomography dot is a noninvasive and nonionizing imaging technique that has got considerable attention in recent years. Diffuse optical tomography and imaging can be performed with different experimental approaches. Nearinfrared nir light in the range of 750900 nm, named as body window, has been used in dot systems. The current approaches to imaging the tissue blood flow index bfi from diffuse correlation tomography dct data are either an analytical solution or a finite element method, both of which are unable to simultaneously account for the tissue heterogeneity and fully utilize the dct data. Diffuse optical tomography dot is a relatively low cost and portable imaging modality for reconstruction of optical properties in a highly scattering. Backpropagation neural networkbased reconstruction. Image reconstruction for frequencydomain diffuse optical. Overview of diffuse optical tomography and its clinical. By combining a singlephoton timeofflight camera with computational processing of the spatial and full temporal photon distribution data, an object embedded inside a strongly diffusive medium.
Breast cancer detection with diffuse optical tomography by changqing li. One often employed setup uses timeresolved excitation and detection schemes, in which multiple picosecond diode laser pulses are introduced into the tissue under study. Multisubject and multitask experimental validation of. The comparison of reconstruction algorithms for diffuse. Pdf reconstruction in diffuse optical tomography using. The comparison of reconstruction algorithms for diffuse optical tomography. Diffuse optical tomography, also known as near infrared tomography, has been under investigation, for noninvasive functional imaging of tissue, speci. Hyperspectral image reconstruction for diffuse optical tomography fridrik larusson,1.
Applying conventional inversion algorithms and denoising the artifacts using the cnns are unsatisfactory since they rely on heavy assumptions and linearization. Diffuse optical tomography dot provides spatial distributions of intrinsic tissue optical. Pdf image reconstruction for diffuse optical tomography using. Miss lin chen, a graduate student in our lab, gave me lots of help in. Dimensionality reduction based optimization algorithm for. Diffuse optical tomography, also known as near infrared tomography, has been under investigation, for noninvasive functional imaging of tissue, specifically for the detection and characterization of breast cancer or other soft tissue lesions. A fast algorithm for fluorescence diffuse optical tomography is proposed. Diffuse optical tomography using generalized music algorithm okkyun lee 1, jongmin kim 1, yoram bresler 2 and jong chul ye 1 1 dept. When used to create 3d volumetric models of the imaged material doi is referred to as diffuse optical tomography, whereas 2d imaging methods are classified as diffuse optical. The direct measurements of the uncalibrated light fluence rates by a camera are used for the reconstructions. Overview of diffuse optical tomography and its clinical applications. Computational timeofflight diffuse optical tomography.
Numerous imaging algorithms exist, and more are being developed. The aim of this paper is to develop an efficient reconstruction algorithm for ultrasoundmodulated diffuse optical tomography. Image reconstruction for diffuse optical tomography using. Reconstruction algorithms for diffuse optical tomography dot and bioluminescence tomography blt have been developed based on diffusion theory. For noisefree data, ga can find exact solutions with a probability of 80%. There is a critical need to develop an efficient image reconstruction algorithm for dot. Diffuse optical tomography can be solved by global optimization method genetic algorithm. Image reconstruction for diffuse optical tomography using sparsity regularization and expectationmaximization algorithm nannan cao1, arye nehorai1. Fast algorithms for hyperspectral diffuse optical tomography. The quality of dot images depends on several factors, including the spatial resolution, image contrast, and artifacts that may be present.
It uses nearinfrared nir light for determination of optical properties of tissue from boundary measurement 1. In diffuse optical tomography 57, 15, 16, the basic assumption is that light scattering prevails over absorption. Reducing image artifact in diffuse optical tomography by. The forward problem solves the diffusion equation using the finite element method for calculating the transmitted light distribution under the condition of presumed light. Image reconstruction for diffuse optical tomography using sparsity regularization and expectationmaximization algorithm. The image reconstruction algorithm of diffuse optical tomography dot is based on the diffusion equation and involves both the forward problem and inverse solution. Fast tomographic reconstruction strategy for diffuse optical tomography. Miller1 1department of electrical and computer engineering, tufts university, medford, massachusetts 02155, usa 2department of biomedical engineering, tufts university, medford, massachusetts 02155, usa fridrik. Improvement of diffuse optical tomography image quality.
Many of these algorithms rely on assumptions which linearize the relationship between the optical contrast and the perturbed signal. Osa image reconstruction for diffuse optical tomography. Image reconstruction in diffuse optical tomography based on simplified spherical harmonics approximation. An algorithm to solve the diffuse optical tomography dot problem is described which uses the anatomical information from xray ct images. Nthorder linear algorithm for diffuse correlation tomography. Typical image reconstruction approaches in dot employ tikhonovtype. Text pdf advanced tomographic image reconstruction algorithms for diffuse optical imaging. Multisubject and multitask experimental validation of the hierarchical bayesian diffuse optical tomography algorithm okito yamashitaa,b. There is a critical need to develop an efficient image reconstruction algorithm. Qiang wangs suggestions on the experiments were always impressive. Advanced tomographic image reconstruction algorithms for diffuse.
Principles and applications is a longawaited profile of a revolutionary imaging method. Her research interests are cancer detection, diagnosis, and treatment assessment, using ultrasoundguided diffuse optical tomography, photoacoustic imaging, and optical coherent tomography. Request pdf fast algorithms for hyperspectral diffuse optical tomography the image reconstruction of chromophore concentrations using diffuse optical tomography dot data can be described. Louis, bryan hall, room 201, campus box 1127, one brookings drive, st. These factors are affected by the dot algorithms as well as the quality of the instruments. An adaptive multigrid algorithm for region of interest diffuse optical tomography. In this case, the propagation of light can be modeled by the diffusion equation. Diffuse optical imaging doi is a method of imaging using nearinfrared spectroscopy nirs or fluorescencebased methods.
Reconstruction algorithm for diffuse optical tomography. We estimate the position of a fluorescent target by assuming a cuboid rectangular parallelepiped for the fluorophore target. Pdf image reconstruction for frequencydomain diffuse optical. The approach is capable of reconstructing the quantitative optical parameters absorption coefficient and scattering coefficient of a soft tissue.
Regularization methods for diffuse optical tomography. Pdf a reconstruction algorithm for ultrasoundmodulated. Diffuse optical tomography dot has shown a great potential for breast imaging 1 9 and functional brain imaging, 10 12 which use nearinfrared light in the spectral range of 600 to 950 nm to quantify tissue optical absorption and scattering coefficients. In this study, a new imaging concept for dct, namely nldct, was created by us in which the medical images. Nannan cao, arye nehorai, and mathews jacob, image reconstruction for diffuse optical tomography using sparsity regularization and expectationmaximization algorithm, opt. Osa a fundamental limitation of linearized algorithms. Pdf the image reconstruction algorithm of diffuse optical tomography dot is based on the diffusion equation and involves both the forward problem. In summary, we have presented novel reconstruction algorithms and experimental methods that extend the capability of timedomain fluorescence diffuse optical tomography.
Pdf image reconstruction for diffuse optical tomography. Diffuse optical tomography is rapidly developing as a new imaging modality for characterizing the spatially varying optical properties of media which strongly scatter light e. Data in the dot system were acquired in transmission or back. Diffuse optical tomography dot is an ongoing medical imaging modality in which tissue is illuminated by nearinfrared light from an array of sources, the multiplyscattered light which emerges. One of the most important and fastest methods in image reconstruction is the boundary element method bem. Diffuse optical tomography dot using nearinfrared nir light is a promising tool for noninvasive imaging of deep tissue. Because of this image reconstruction algorithms utilizing diffusive photons were. Salehi 2, and quing zhu1,2 1department of biomedical engineering, university of connecticut, storrs, ct, usa 2department of electrical and computer engineering, university of connecticut, storrs, ct, usa. Pdf the comparison of reconstruction algorithms for diffuse. Timedomain fluorescence diffuse optical tomography.
Forward model analysis in diffuse optical tomography. The motivation for reconstructing the optical property variation is that it and, in particular, the absorption coefficient. The proposed numerical algorithm is verified by a numerical experiment and an experiment with a meat phantom. Adaptive meshing algorithms for fluorescence diffuse optical tomography in the presence of measurement noise lu zhou, and birsen yaz. Diffuse optical tomography 14 journal of lasers in medical sciences volume 5 number 1 winter 2014 imaging is related to the accuracy of image reconstruction. Diffuse optical tomography dot is an emerging technology for improving the spatial resolution and spatial specificity of conventional multichannel nearinfrared spectroscopy nirs by the use of highdensity measurements and an image reconstruction algorithm.
Third, we show using planar imaging and tomography, the in vivo recovery of multiple anatomically targeted nearinfrared fluorophores. Assessment of diffuse optical tomography image reconstruction methods using a photon transport model murad m. System implementation and validation of reconstruction algorithms. Miller, estimationtheoretic algorithms and bounds for threedimensional polar shape based imaging in diffuse optical tomography, in proceedings of ieee. A semianalytic reconstruction method for diffuse optical. These provide a priori information about the distribution of the optical properties hence reducing the number of variables and permitting a. Diffuse optical tomography dot is one of the emerging modalities for the noninvasive imaging of thick biological tissues using nearinfrared nir light.
The image reconstruction of chromophore concentrations using diffuse optical tomography dot data can be described. Tomographic image reconstruction from optical projections in light. Guven et al discretization error analysis and adaptive meshing algorithms for fluorescence diffuse optical tomography 231 ered separately for each problem disregarding its impact on the solution of the other problem. Nearinfrared diffuse optical tomography dot, one of the most sophisticated optical imaging. A reconstruction algorithm for ultrasoundmodulated diffuse optical tomography habib ammari, emmanuel bossy, josselin garnier, loc hoang nguyen, and laurent seppecher abstract. Regularization methods for diffuse optical tomography petri hiltunen doctoral dissertation for the degree of doctor of science in technology to be presented with due permission of the school of science for public examination and debate in auditorium e at the aalto university school of science espoo, finland on the 8th of november 2011 at 12 noon. Image reconstruction for diffuse optical tomography using sparsity. The algorithms numerically solve the diffusion equation using the finite element method. Over the past two decades, diffuse optical tomography dot techniques have been developed to estimate optical properties of interior tissue for diagnostic proposes 16. In this twopart study, as well as in 16 and 22, we intro. Pdf image correction algorithm for functional three. Image correction algorithm for functional threedimensional diffuse optical tomography brain imaging.