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A theoretical‐experimental methodology for assessing the sensitivity of biomedical spectral imaging platforms,assays, and analysis methods
Authors:Silas J Leavesley  Brenner Sweat  Caitlyn Abbott  Peter Favreau  Thomas C Rich
Affiliation:1. Department of Chemical and Biomolecular Engineering, University of South Alabama, 150 Jaguar Dr., SH 4129, Mobile, AL 36688, USA;2. Department of Pharmacology, University of South Alabama, USA;3. Center for Lung Biology, University of South Alabama, USA;4. IT Security & Governance, AM/NS Calvert, USA;5. Basic Medical Sciences, University of South Alabama, USA;6. Morgridge Institute for Research, University of Wisconsin - Madison, USA;7. College of Engineering, University of South Alabama, USA
Abstract:Spectral imaging technologies have been used for many years by the remote sensing community. More recently, these approaches have been applied to biomedical problems, where they have shown great promise. However, biomedical spectral imaging has been complicated by the high variance of biological data and the reduced ability to construct test scenarios with fixed ground truths. Hence, it has been difficult to objectively assess and compare biomedical spectral imaging assays and technologies. Here, we present a standardized methodology that allows assessment of the performance of biomedical spectral imaging equipment, assays, and analysis algorithms. This methodology incorporates real experimental data and a theoretical sensitivity analysis, preserving the variability present in biomedical image data. We demonstrate that this approach can be applied in several ways: to compare the effectiveness of spectral analysis algorithms, to compare the response of different imaging platforms, and to assess the level of target signature required to achieve a desired performance. Results indicate that it is possible to compare even very different hardware platforms using this methodology. Future applications could include a range of optimization tasks, such as maximizing detection sensitivity or acquisition speed, providing high utility for investigators ranging from design engineers to biomedical scientists.

Keywords:spectral  spectroscopy  microscopy  linear unmixing  spectral angle mapper  constrained energy minimization  matched filter
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