Diffuse optical tomography with a priori anatomical information

Abstract

Diffuse optical imaging is an emerging modality that uses Near Infrared (NIR) light to reveal structural and functional information of deep biological tissue. It provides contrast mechanisms for molecular, chemical, and anatomical imaging that is not available from other imaging modalities. Diffuse Optical Tomography (DOT) deals with 3D reconstruction of optical properties of tissue given the measurements and a forward model of photon propagation. DOT has inherently low spatial resolution due to diffuse nature of photons. In this work, we focus to improve the spatial resolution and the quantitative accuracy of DOT by using a priori anatomical information specific to unknown image. Such specific a priori information can be obtained from a secondary high-resolution imaging modality such as Magnetic Resonance (MR) or X-ray. Image reconstruction is formulated within a Bayesian framework to determine the spatial distribution of the absorption coefficients of the medium. A spatially varying a priori probability density function is designed based on the segmented anatomical information. Conjugate gradient method is utilized to solve the resulting optimization problem. Proposed method is evaluated using simulation and phantom measurements collected with a novel timeresolved optical imaging system. Results demonstrate that the proposed method leads to improved spatial resolution, quantitative accuracy and faster convergence than standard least squares approach.

Magnetic resonance–coupled fluorescence tomography scanner for molecular imaging of tissue

“…Additional information may be used to guide image recovery by noting that variation in tissue optical properties can be loosely associated with the tissue's anatomical structure, providing an opportunity to incorporate anatomical information from highly resolved conventional imaging systems in the recovery of images of optically relevant molecules. In practice, standard magnetic resonance ͑MR͒ images have been used to guide diffusionbased image reconstruction of endogenous tissue chromophores [19][20][21] and recently of fluorescent molecules.…”

Tumor detection using Bayesian conjugate prior in diffuse optical tomography

“…More detailed development is given in our previous work [1]. Using the perturbation approach and Rytov approximation [4], [5], we show that the image can be reconstructed with a single noisy observation. For the inverse problem, we assume a Gaussian conjugate prior on the absorption coefficient.…”

“…The inverse problem is to reconstruct the spatially varying absorption and scattering coefficients of human tissues. This problem is typically illposed because of the large number of unknown parameters involved [2], [3], [5]. Solutions to the inverse problem have been extensively studied [4], [11].…”

Application and data fusion of different sensor modalities in tomographic imaging

“…The measurements are usually acquired using optical fibres and photo diodes. Diffuse Optical Tomography (DOT) aims at reconstructing the scattering and absorption coefficients and has been investigated for imaging tissue in the medical field (Guven et al, 2005). It can only be applied to optically transparent materials and optically accessible pipes and containers.…”