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Deep Convolutional Feature-Based Fluorescence-to-Color Image Registration
Conference proceeding

Deep Convolutional Feature-Based Fluorescence-to-Color Image Registration

Xingxing Liu, Tri Quang, Wenxiang Deng and Yang Liu
2021 IEEE International Symposium on Medical Measurements and Applications (MeMeA), pp.1-6
06/23/2021
DOI: 10.1109/MeMeA52024.2021.9478607

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Abstract

Fluorescence imaging has been widely utilized in various clinical applications. As a functional imaging modality, NIR fluorescence imaging often does not offer sufficient structural details. Therefore, structural imaging such as color reflectance overlaid with fluorescence imaging represents a superior approach for surgical visualization. Image registration of color reflectance and NIR fluorescence is needed for accurate overlay. In this study, we have implemented a deep convolutional algorithm for feature-based fluorescence-to-color image registration. Software-hardware codesign was conducted. Several sets of experiments were performed on biological tissues to compare the performance of our algorithm and traditional methods. We have demonstrated the feasibility of deep convolutional feature-based fluorescence-to-color image registration. To our best knowledge, this is the first demonstration of deep learning-based image registration between fluorescence and color imageries.
 Computer Vision Surgery Convolutional codes Deep learning fluorescence imaging Image color analysis Image registration Imaging intraoperative imaging multimodal imaging Reflectivity Visualization

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