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Biomedical Engineering and Bioengineering Commons™
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Full-Text Articles in Biomedical Engineering and Bioengineering
Multi-Beam Scan Analysis With A Clinical Linac For High Resolution Cherenkov-Excited Molecular Luminescence Imaging In Tissue., Mengyu Jeremy Jia, Peter Bruza, Lesley A. Jarvis, David J. Gladstone, Brian W. Pogue
Multi-Beam Scan Analysis With A Clinical Linac For High Resolution Cherenkov-Excited Molecular Luminescence Imaging In Tissue., Mengyu Jeremy Jia, Peter Bruza, Lesley A. Jarvis, David J. Gladstone, Brian W. Pogue
Dartmouth Scholarship
Cherenkov-excited luminescence scanned imaging (CELSI) is achieved with external beam radiotherapy to map out molecular luminescence intensity or lifetime in tissue. Just as in fluorescence microscopy, the choice of excitation geometry can affect the imaging time, spatial resolution and contrast recovered. In this study, the use of spatially patterned illumination was systematically studied comparing scan shapes, starting with line scan and block patterns and increasing from single beams to multiple parallel beams and then to clinically used treatment plans for radiation therapy. The image recovery was improved by a spatial-temporal modulation-demodulation method, which used the ability to capture simultaneous images …
Weighting Function Effects In A Direct Regularization Method For Image-Guided Near-Infrared Spectral Tomography Of Breast Cancer., Jinchao Feng, Shudong Jiang, Brian W. Pogue, Keith Paulsen
Weighting Function Effects In A Direct Regularization Method For Image-Guided Near-Infrared Spectral Tomography Of Breast Cancer., Jinchao Feng, Shudong Jiang, Brian W. Pogue, Keith Paulsen
Dartmouth Scholarship
Structural image-guided near-infrared spectral tomography (NIRST) has been developed as a way to use diffuse NIR spectroscopy within the context of image-guided quantification of tissue spectral features. A direct regularization imaging (DRI) method for NIRST has the value of not requiring any image segmentation. Here, we present a comprehensive investigational study to analyze the impact of the weighting function implied when weighting the recovery of optical coefficients in DRI based NIRST. This was done using simulations, phantom and clinical patient exam data. Simulations where the true object is known indicate that changes to this weighting function can vary the contrast …
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 …
Singular Value Decomposition Metrics Show Limitations Of Detector Design In Diffuse Fluorescence Tomography, Frederic Leblond, Kenneth M. Tichauer, Brian W. Pogue
Singular Value Decomposition Metrics Show Limitations Of Detector Design In Diffuse Fluorescence Tomography, Frederic Leblond, Kenneth M. Tichauer, Brian W. Pogue
Dartmouth Scholarship
The spatial resolution and recovered contrast of images reconstructed from diffuse fluorescence tomography data are limited by the high scattering properties of light propagation in biological tissue. As a result, the image reconstruction process can be exceedingly vulnerable to inaccurate prior knowledge of tissue optical properties and stochastic noise. In light of these limitations, the optimal source-detector geometry for a fluorescence tomography system is non-trivial, requiring analytical methods to guide design. Analysis of the singular value decomposition of the matrix to be inverted for image reconstruction is one potential approach, providing key quantitative metrics, such as singular image mode spatial …