Open AccessMulti-atlas registration and adaptive hexahedral voxel discretization for fast bioluminescence tomography
Author(s) -
Shenghan Ren,
Hongping Hu,
Gen Li,
Xu Cao,
Shouping Zhu,
Xueli Chen,
Jimin Liang
Publication year - 2016
Publication title -
biomedical optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.362
H-Index - 86
ISSN - 2156-7085
DOI - 10.1364/boe.7.001549
Subject(s) - voxel , discretization , computer science , finite element method , tomography , image registration , segmentation , a priori and a posteriori , computer vision , iterative reconstruction , artificial intelligence , atlas (anatomy) , algorithm , physics , mathematics , optics , medicine , image (mathematics) , mathematical analysis , philosophy , epistemology , thermodynamics , anatomy
Bioluminescence tomography (BLT) has been a valuable optical molecular imaging technique to non-invasively depict the cellular and molecular processes in living animals with high sensitivity and specificity. Due to the inherent ill-posedness of BLT, a priori information of anatomical structure is usually incorporated into the reconstruction. The structural information is usually provided by computed tomography (CT) or magnetic resonance imaging (MRI). In order to obtain better quantitative results, BLT reconstruction with heterogeneous tissues needs to segment the internal organs and discretize them into meshes with the finite element method (FEM). It is time-consuming and difficult to handle the segmentation and discretization problems. In this paper, we present a fast reconstruction method for BLT based on multi-atlas registration and adaptive voxel discretization to relieve the complicated data processing procedure involved in the hybrid BLT/CT system. A multi-atlas registration method is first adopted to estimate the internal organ distribution of the imaged animal. Then, the animal volume is adaptively discretized into hexahedral voxels, which are fed into FEM for the following BLT reconstruction. The proposed method is validated in both numerical simulation and an in vivo study. The results demonstrate that the proposed method can reconstruct the bioluminescence source efficiently with satisfactory accuracy.