Free Space Fluorescence Molecular Imaging For Small Animals

Fluorescence molecular imaging has become an important imaging method of biomedical research at molecular and cellular level. Combine fluorescence reflectance imaging with spectral analysis, fluorescence signal from multiple fluorophores can be acquired simultaneously, which is useful to understanding the interaction between molecules or proteins. Fluorescence molecular tomography can provide the three dimensional and quantitative information of fluorophore. More information is acquired with dual-modal FMT-CT imaging than stand-alone FMT system.Multispectral fluorescence reflectance imaging system is designed and constructed in this thesis, and the corresponding data processing algorithms are developed. This system is capable of recording the fluorescence signal of fluorophore deep in biological tissue, reducing the effects of noise and autofluorescence, imaging and unmixing the signals from multiple fluorophores. A method to extract typical spectrum in vivo is proposed, which divide pixels in fluorescence image into different classifications according to their spectral properties.A slab geometry fluorescence molecular tomography system was developed. A748nm continuous wave diode laser was employed as excitation source. High sensitivity cooled CCD camera with excitation and emission filters was used to acquire the excitation and fluorescence images. The laser beam can perform a fast raster scanning with a dual-axis galvanometric scanner. The accuracy of the laser spot position at the source window was within±200μm. The phantom experiments demonstrated that the spatial resolution was less than1.7mm and the relative quantitation error was about10%. In vivo imaging of nude mouse bearing tumor marked by near-infrared dye demonstrated the feasibility of the system.Combined system of fluorescence molecular tomography and micro-computed tomography can provide molecular and anatomical information of small animals in a single study with intrinsically co-registered images. A co-calibration method for the combined system is proposed. First, linear models are adopted to describe the galvano mirrors and the charge-coupled device (CCD) camera in the FMT subsystem. Second, the position and orientation of the galvano mirrors are determined with the input voltages and the markers, whose positions are predetermined. The position, orientation and normalized pixel size of the CCD camera are obtained by analysing the projections of a point-like marker at different positions. Finally, the orientation and position of sources and the corresponding relationship between the detectors and their projections on the image plane are predicted. Because the positions of the markers are acquired with CT, the registration of the FMT and CT could be realized by direct image fusion. The accuracy and consistency of this method in the presence of noise is evaluated by computer simulation. Next, a practical implementation for an experimental FMT-CT system is carried out and validated. The maximum prediction error of the source positions on the surface of a cylindrical phantom is within0.375mm and that of the projections of a point-like marker is within0.629pixel. Finally, imaging experiments of the fluorophore distribution in a cylindrical phantom and a phantom with a complex shape demonstrate the feasibility of the proposed method.To take advantages of the combined system, a data preprocessing method is proposed to extract the valid data for FMT reconstruction algorithms using a priori information provided by CT. The boundary information of the animal and animal holder is extracted from reconstructed CT volume data. A ray tracing method is used to trace the path of the excitation beam, calculate the locations and orientations of the optional sources and determine whether the optional sources are valid. To accurately calculate the projections of the detectors on optical images and judge their validity, a combination of perspective projection and inverse ray tracing method are adopted to offer optimal performance. The imaging performance of the combined system with the presented method is validated through experimental rat imaging.