Principle component analysis in bioimaging.

• 主要作者: Poh, Corina Qian Yi.
• 其他作者: Lee Kijoon
• 格式: Final Year Project
• 語言: English
• 出版: 2009
• 主題: DRNTU::Engineering::Bioengineering
• 在線閱讀: http://hdl.handle.net/10356/16539

Although the use of non-invasive in vivo optical imaging that makes use of Optical Tomography with secondary imaging modalities (X-ray combined with micro computed Tomography) can generate high resolution images, they are expensive, complex and cannot exactly outline the true anatomical structure of animals’ organs. Dynamic fluorescence imaging (DFI) with a minute amount of chemically inert fluorescent dye, ICG (Indocyanine Green) and the use of statistical tool Principle Component Analysis (PCA), could be used instead to delineate the organs in mice. In this report, the author studied the difference in retention and metabolism of ICG dye for each organ by taking images over a fixed time interval. Images were being captured using a CCD camera, detecting the dynamics of ICG fluorescence shortly after its intravenous injection into mice upon excitation by a diverged laser source. Post processing and its analysis were done in Matlab. It made use of PCA to contribute to improving the resolution of imaging data by being able to handle the bulk of data through image compression and highlighting hidden trends among images collected. To show the achievement of PCA in Bio-imaging positively, the author has also simulated the perfusion rate of ICG and applied PCA to the images to portray the success delineation of organs. Therefore, the use of PCA with DFI indeed promises better bio-imaging capability with the ability to attain accurate structure within mice, without the need for secondary imaging methods.