19 March 2015 Development of color micro optical-CT: evaluation using phantom and biological samples
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Micro-optical computed tomography (MOCT) is a method for performing image reconstruction using microscopic images to obtain tomographic images of small samples. Compared with conventional observation methods, it offers the possibility to obtain tomograpic images without distortion, and create three-dimensional images. However, MOCT system which developed previously outputs monochrome images, while useful color information could not be obtained from the analysis of the sample. Therefore, we focused on the features that simplify the wavelength measurement of visible light, and developed a color MOCT system that can obtain color tomographic images. In this study, we acquired tomographic images of phantom and biological samples, and evaluated its usefulness. In this system, a digital single-lens reflex camera was used as a detector that was connected to a stereoscopic microscope, and projection images were obtained by rotating the sample. The sample was fixed in the test tube by carrageenan. The projection images were obtained from various projection angles followed by decomposing the R, G and B components. Subsequently, we performed image reconstruction for each component using filtered back projection. Finally, color tomographic image was obtained by combining the three-color component images. In the experiments, we scanned a color phantom and biological samples and evaluated the color and shape reproducibility. As a result, it was found that the color and shape of the tomographic images were similar to those of the samples. These results indicate that the proposed system may be useful to obtain the three-dimensional color structure of biological samples.
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C. Murata, C. Murata, A. Teramoto, A. Teramoto, C. Kaneko, C. Kaneko, H. Fujita, H. Fujita, "Development of color micro optical-CT: evaluation using phantom and biological samples", Proc. SPIE 9417, Medical Imaging 2015: Biomedical Applications in Molecular, Structural, and Functional Imaging, 941722 (19 March 2015); doi: 10.1117/12.2081681; https://doi.org/10.1117/12.2081681

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