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11 July 2019 Simulation of fluorescence molecular tomography using a registered digital mouse atlas
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Abstract
Fluorescence Molecular Tomography (FMT) constitutes a functional and molecular imaging tool complementing well-established anatomical imaging modalities such as magnetic resonance imaging (MRI) and X-ray computer tomography (CT). Preclinical applications of FMT in the fields of tumor imaging, breast imaging, proteomic research, and drug discovery have been reported. We have developed the Smart ToolkIt for Fluorescence Tomography (STIFT) software platform for simulating, reconstructing and optimizing FMT. However, accurate reconstruction of FMT data for inhomogeneous objects of complex shape, e.g. a live mouse, requires prior information about the anatomy. This work addresses this issue by incorporating a digital mouse atlas into STIFT. The Digimouse consists of high-resolution and well-registered multimodal volumetric images of a post-mortem 28g male C57Bl/6 mouse. Techniques including cropping, translation, and de-noising were performed on the Digimouse atlas (DA), the Digimouse CT volume (DCT), and our MR datasets. To decrease the discrepancy between the DCT and the DA, the skull regions of these two volumes were enhanced and the DA was deformed using the transformation matrix. Followed, was another automated registration, between an experimental MRI dataset and the newly coupled DCT-DA dataset by fixing the former. Finally, the registered DA was used for meshing and FMT simulations. The quality of registration was quantified and shown to have increased organ volume overlap using the Dice similarity coefficient as metric. The reconstructed fluorophore distribution matches well with the preset ground truth, demonstrating that the meshed atlas is compatible with STIFT.
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Mavi Nunn Polatoglu, Yan Liu, Ruiqing Ni, Jorge Ripoll, Markus Rudin, Martin Wolf, and Wuwei Ren "Simulation of fluorescence molecular tomography using a registered digital mouse atlas", Proc. SPIE 11074, Diffuse Optical Spectroscopy and Imaging VII, 110740C (11 July 2019); https://doi.org/10.1117/12.2525366
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