Novel registration for microcomputed tomography and bioluminescence imaging based on iterated optimal projection

Abstract

Abstract. As a high-sensitivity imaging modality, bioluminescence tomography can reconstruct the three-dimensional (3-D) location of an internal luminescent source based on the 3-D surface light distribution. However, we can only get the multi-orientation two-dimensional (2-D) bioluminescence distribution in the experiments. Therefore, developing an accurate universal registration method is essential for following bioluminescent source reconstruction. We can then map the multi-orientation 2-D bioluminescence distribution to the 3-D surface derived from anatomical information with it. We propose a 2-D -to-3-D registration method based on iterated optimal projection and applied it in a registration and reconstruction study of three transgenic mice. Compared with traditional registration methods based on the fixed points, our method was independent of the markers and the registration accuracy of the three experiments was improved by 0.3, 0.5, and 0.4 pixels, respectively. In addition, based on the above two registration results using the two registration methods, we reconstructed the 3-D location of the inner bioluminescent source in the three transgenic mice. The reconstruction results showed that the average error distance between the center of the reconstructed element and the center of the real element were reduced by 0.32, 0.48, and 0.39 mm, respectively.

An Artificial Intelligent Signal Amplification System for in vivo Detection of miRNA

“…When a fluorescence signal is generated inside the body, we cannot directly detect the fluorescence intensity; we can only detect the distribution and intensity of fluorescence that passes through the tissue and reaches the body surface. The transmission of fluorescence in vivo obeys a certain rule, which can be expressed by the following equation describing the propagation of light (Ma et al, 2013; Xue et al, 2013; Qin et al, 2014; Ye et al, 2014; Zhang et al, 2018b):…”

“…ημ af ( r ) is the fluorophore distribution to be reconstructed, where η is the quantum yield and q denotes the optical reflective index. In the process of fluorescence tomography reconstruction, we used Robin boundary conditions to calculate the position of fluorescence source in vivo (Ma et al, 2013). For nearly 10 years, our research group has been working on 3D reconstruction of internal fluorescence and developed series of algorithms.…”

Recent Advances in Optical Molecular Imaging and its Applications in Targeted Drug Delivery

“…Nevertheless, BLI and FMI cannot distinguish drug distributions in different organs at different depths. As sensitive in vivo imaging modalities are concerned, many bioluminescence reconstruction and fluorescence reconstruction algorithms have been proposed in order to detect the inner information of tumor location and drug efficacy [9][10][11]. However, due to the accuracy constraints, these two-dimensional imaging modalities were rarely used in drug delivery research such as the research of three-dimensional drug distribution in the body.…”