A theoretical‐experimental methodology for assessing the sensitivity of biomedical spectral imaging platforms, assays, and analysis methods. Issue 1 (9th May 2017)

• Record Type: Journal Article
• Authors: Leavesley, Silas J.; Sweat, Brenner; Abbott, Caitlyn; Favreau, Peter; Rich, Thomas C.
• Is Part Of: Journal of biophotonics. Volume 11:Issue 1(2018)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2017-05-09
• Subjects: spectral -- spectroscopy -- microscopy -- linear unmixing -- spectral angle mapper -- constrained energy minimization -- matched filter; Photonics -- Periodicals; Optical materials -- Periodicals; Optics -- Periodicals; Medical instruments and apparatus -- Periodicals; 621.3605
• DOI: 10.1002/jbio.201600227
• Languages: English
• ISSNs: 1864-063X

Abstract

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. Abstract : Spectral imaging has many applications in biology and medicine. Unfortunately, assessing the sensitivity of spectral imaging experiments is often not feasible, due to the need for exhaustive experimental controls and the inability to generate biological samples with a fixed ground truth. Here, we present a solution for assessing spectral imaging performance sensitivity that requires only a small set of experimental controls combined with theoretical modeling.Picture : A theoretical experimental methodology for assessing the sensitivity of biomedical spectral imaging platforms, assays, and analysis methods.