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1. Idcube Lite – A Free Interactive Discovery Cube Software for Multi And Hyperspectral Applications

   Mishra, D; Hurbon, H; Wang, J; Wang, T; Du, T; Wu, Q; Kim, D; Cao, Q; Basir, S; Zhang, H; et al (July 2021, Workshop on Hyperspectral Image and Signal Processing Evolution in Remote Sensing)

   null (Ed.)

   Multi- and hyperspectral imaging modalities encompass a growing number of spectral techniques that find many applications in geospatial, biomedical and machine vision fields. The rapidly increasing number of applications requires a convenient easy-to-navigate software that can be used by new and experienced users to analyze data, develop, apply, and deploy novel algorithms. Herein, we present our platform, IDCube that performs essential operations in hyperspectral data analysis to realize the full potential of spectral imaging. The strength of the software lies in its interactive features that enable the users to optimize parameters and obtain visual input for the user. The entire software can be operated without any prior programming skills allowing interactive sessions of raw and processed data. IDCube Lite, a free version of the software described in the paper, has many benefits compared to existing packages and offers structural flexibility to discover new hidden features. 

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2. Colorectal cancer detection by hyperspectral imaging using fluorescence excitation scanning

   https://doi.org/10.1117/12.2290696  

   Leavesley, Silas J.; Deal, Joshua; Martin, Will A.; Lall, Malvika; Lopez, Carmen; Rich, Thomas C.; Boudreaux, Carole W.; Rider, Paul F.; Hill, Shante (February 2018, Proc. SPIE 10489, Optical Biopsy XVI: Toward Real- Time Spectroscopic Imaging and Diagnosis, 104890K)

   Hyperspectral imaging technologies have shown great promise for biomedical applications. These techniques have been especially useful for detection of molecular events and characterization of cell, tissue, and biomaterial composition. Unfortunately, hyperspectral imaging technologies have been slow to translate to clinical devices – likely due to increased cost and complexity of the technology as well as long acquisition times often required to sample a spectral image. We have demonstrated that hyperspectral imaging approaches which scan the fluorescence excitation spectrum can provide increased signal strength and faster imaging, compared to traditional emission-scanning approaches. We have also demonstrated that excitation-scanning approaches may be able to detect spectral differences between colonic adenomas and adenocarcinomas and normal mucosa in flash-frozen tissues. Here, we report feasibility results from using excitation-scanning hyperspectral imaging to screen pairs of fresh tumoral and nontumoral colorectal tissues. Tissues were imaged using a novel hyperspectral imaging fluorescence excitation scanning microscope, sampling a wavelength range of 360-550 nm, at 5 nm increments. Image data were corrected to achieve a NIST-traceable flat spectral response. Image data were then analyzed using a range of supervised and unsupervised classification approaches within ENVI software (Harris Geospatial Solutions). Supervised classification resulted in >99% accuracy for single-patient image data, but only 64% accuracy for multi-patient classification (n=9 to date), with the drop in accuracy due to increased false-positive detection rates. Hence, initial data indicate that this approach may be a viable detection approach, but that larger patient sample sizes need to be evaluated and the effects of inter-patient variability studied. 

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3. Applications and assessment of an excitation-scanning hyperspectral imaging system

   https://doi.org/10.1117/12.2290120  

   Mayes, Sam A.; Leavesley, Silas J.; Rich, Tom C.; Klomkaew, Phiwat; Moore, Kaysie; Browning, Craig (February 2018, Proc. SPIE 10497, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues XVI)

   The majority of microscopic and endoscopic technologies utilize white light illumination. For a number of applications, hyper-spectral imaging can be shown to have significant improvements over standard white-light imaging techniques. This is true for both microscopy and in vivo imaging. However, hyperspectral imaging methods have suffered from slow application times. Often, minutes are required to gather a full imaging stack. Here we will describe and evaluate a novel excitation-scanning hyperspectral imaging system and discuss some applications. We have developed and are optimizing a novel approach called excitation-scanning hyperspectral imaging that provides an order of magnitude increased signal strength. This excitation scanning technique has enabled us to produce a microscopy system capable of high speed hyperspectral imaging with the potential for live video acquisition. The excitation-scanning hyperspectral imaging technology we developed may impact a range of applications. The current design uses digital strobing to illuminate at 16 wavelengths with millisecond image acquisition time. Analog intensity control enables a fully customizable excitation profile. A significant advantage of excitation-scanning hyperspectral imaging is can identify multiple targets simultaneously in real time. Finally, we are exploring utilizing this technology for a variety of applications ranging from measuring cAMP distribution in three dimensions within a cell to electrophysiology. 

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4. Deriving a usage-independent software quality metric

   https://doi.org/10.1007/s10664-019-09791-w  

   Dey, T; Mockus, A (May 2020, Empirical software engineering)

   Context The extent of post-release use of software affects the number of faults, thus biasing quality metrics and adversely affecting associated decisions. The proprietary nature of usage data limited deeper exploration of this subject in the past. Objective To determine how software faults and software use are related and how, based on that, an accurate quality measure can be designed. Method Via Google Analytics we measure new users, usage intensity, usage frequency, exceptions, and release date and duration for complex proprietary mobile applications for Android and iOS. We utilize Bayesian Network and Random Forest models to explain the interrelationships and to derive the usage independent release quality measure. To increase external validity, we also investigate the interrelationship among various code complexity measures, usage (downloads), and number of issues for 520 NPM packages. We derived a usage-independent quality measure from these analyses, and applied it on 4430 popular NPM packages to construct timelines for comparing the perceived quality (number of issues) and our derived measure of quality during the lifetime of these packages. Results We found the number of new users to be the primary factor determining the number of exceptions, and found no direct link between the intensity and frequency of software usage and software faults. Crashes increased with the power of 1.02-1.04 of new user for the Android app and power of 1.6 for the iOS app. Release quality expressed as crashes per user was independent of other usage-related predictors, thus serving as a usage independent measure of software quality. Usage also affected quality in NPM, where downloads were strongly associated with numbers of issues, even after taking the other code complexity measures into consideration. Unlike in mobile case where exceptions per user decrease over time, for 45.8% of the NPM packages the number of issues per download increase. Conclusions We expect our result and our proposed quality measure will help gauge release quality of a software more accurately and inspire further research in this area. 

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5. Optimization of light transmission through an excitation-scan hyperspectral mirror array system

   https://doi.org/10.1117/12.2510555  

   Parker, Marina; Browning, Craig; Rich, Thomas C.; Leavesley, Silas J.; Farkas, Daniel L.; Leary, James F.; Tarnok, Attila (March 2019, Proc. SPIE 10881, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues XVII, 108810O)

   Hyperspectral imaging has numerous applications in a range of fields for target detection. While its original applications were in remote sensing, new uses include analyzing food quality, agriculture and medicine, Hyperspectral imaging has shown utility in fluorescence microscopy for detecting signatures from many fluorescent molecules, but acquisition speeds have been slow due to the need to acquire many spectral bands and the light losses associated with spectral filtering. Therefore, a novel confocal microscope, the 5- Dimensional Rapid Hyperspectral Imaging Platform (RHIP-5D) was designed and is undergoing testing to overcome acquisition speed and sensitivity limitations. The current design utilizes light-emitting diodes (LEDs) and a multifaceted mirror array to combine light sources into a liquid light guide. Initial tests demonstrated feasibility and we are now working on determining the ideal location of the liquid light guide, LEDs, lenses and mirror array to optimize optical transmission. A computational model was constructed using Monte Carlo optical ray tracing in TracePro software (Lambda Research Corp.). LED sources were simulated by importing irradiance properties from the manufacturers’ specifications. Optical properties of lenses were modeled using lens files available from the manufacturer. Analysis of the model includes geometry and parametric optimization, assessing lens power, mirror angles and location of optical elements. Initial results show an increase of transmission is possible by up to 20%. Future work will involve evaluating the position of the liquid light guide as well as analyzing lens configurations to further increase optical transmission. 

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