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Bioimaging and Biomedical Optics Commons™
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Full-Text Articles in Bioimaging and Biomedical Optics
Review Of Fluorescence Guided Surgery Visualization And Overlay Techniques, Jonathan T. Elliott, Alisha V. Dsouza, Scott C. Davis, Jonathan D. Olson, Keith Paulsen, David Roberts, Brian Pogue
Review Of Fluorescence Guided Surgery Visualization And Overlay Techniques, Jonathan T. Elliott, Alisha V. Dsouza, Scott C. Davis, Jonathan D. Olson, Keith Paulsen, David Roberts, Brian Pogue
Dartmouth Scholarship
In fluorescence guided surgery, data visualization represents a critical step between signal capture and display needed for clinical decisions informed by that signal. The diversity of methods for displaying surgical images are reviewed, and a particular focus is placed on electronically detected and visualized signals, as required for near-infrared or low concentration tracers. Factors driving the choices such as human perception, the need for rapid decision making in a surgical environment, and biases induced by display choices are outlined. Five practical suggestions are outlined for optimal display orientation, color map, transparency/alpha function, dynamic range compression, and color perception check.
Direct Regularization From Co-Registered Anatomical Images For Mri-Guided Near-Infrared Spectral Tomographic Image Reconstruction, Limin Zhang, Yan Zhao, Shudong Jiang, Brian W. Pogue, Keith Paulsen
Direct Regularization From Co-Registered Anatomical Images For Mri-Guided Near-Infrared Spectral Tomographic Image Reconstruction, Limin Zhang, Yan Zhao, Shudong Jiang, Brian W. Pogue, Keith Paulsen
Dartmouth Scholarship
Combining anatomical information from high resolution imaging modalities to guide near-infrared spectral tomography (NIRST) is an efficient strategy for improving the quality of the reconstructed spectral images. A new approach for incorporating image information directly into the inversion matrix regularization was examined using Direct Regularization from Images (DRI), which encodes the gray-scale data into the NIRST image reconstruction problem. This process has the benefit of eliminating user intervention such as image segmentation of distinct regions. Specifically, the Dynamic Contrast Enhanced Magnetic Resonance (DCE-MR) image intensity value differences within the anatomical image were used to implement an exponentially-weighted regularization function between …