Abstract
Optical-CT dual-modality imaging requires the mapping between 2D fluorescence images and 3D body surface light flux. In this paper, we proposed an optical-CT dual-modality image mapping algorithm based on the Digitally Reconstructed Radiography (DRR) registration. In the process of registration, a series of DRR images were computed from CT data using the ray casting algorithm. Then, the improved HMNI similarity strategy based on Hausdorff distance was used to complete the registration of the white-light optical images and DRR virtual images. According to the corresponding relationship obtained by the image registration and the Lambert’s cosine law based on the pin-hole imaging model, the 3D light intensity distribution on the surface of the object could be solved. The feasibility and effectiveness of the mapping algorithm are verified by the irregular phantom and mouse experiments.
Highlights
Fluorescence Molecular Tomography (FMT) has been used frequently for the noninvasive study of cancer biological behavior [1,2,3]
We propose an optical-computerized tomography (CT) dual-modality image mapping algorithm based on Digitally Reconstructed Radiograph (DRR) registration
The white-light image and the Digitally Reconstructed Radiography (DRR) virtual image computed from CT are aligned iteratively until an optimal matching is achieved by adjusting the optimal transformation parameters and similarity measure
Summary
Fluorescence Molecular Tomography (FMT) has been used frequently for the noninvasive study of cancer biological behavior [1,2,3]. When FMT/CT dual-modality imaging technology is used to calculate internal bioluminescent source’s size and location, it is necessary to establish a mapping between two-dimensional (2D) optical images and three-dimensional (3D) CT data in order to reconstruct 3D energy distribution on surface of the imaging object [6,7]. 3D image can be projected into 2D image to achieve the registration between two modal 2D images. Fluorescent image is used along with CT to map functional information on tissue structures due to its high sensitivity. We propose an optical-CT dual-modality image mapping algorithm based on Digitally Reconstructed Radiograph (DRR) registration. The algorithm can directly map the 2D optical image onto the surface of the 3D CT data to obtain the 3D light intensity distribution on the tissue surface
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