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1. IDCube Lite: Free Interactive Discovery Cube software for multi and hyperspectral applications

   https://doi.org/10.1255/jsi.2021.a1  

   Mishra, Deependra; Hurbon, Helena; Wang, John; Wang, Steven; Du, Tommy; Wu, Qian; Kim, David; Basir, Shiva; Cao, Qian; Zhang, Hairong; et al (May 2021, Journal of Spectral Imaging)

   null (Ed.)

   Multi- and hyperspectral imaging modalities encompass a growing number of spectral techniques that find many applications in geospatial, biomedical, machine vision and other fields. The rapidly increasing number of applications requires convenient easy-to-navigate software that can be used by new and experienced users to analyse data, and develop, apply and deploy novel algorithms. Herein, we present our platform, IDCube Lite, an Interactive Discovery Cube that performs essential operations in hyperspectral data analysis to realise the full potential of spectral imaging. The strength of the software lies in its interactive features that enable the users to optimise parameters and obtain visual input for the user in a way not previously accessible with other software packages. 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 that allow users to integrate novel computational methods. 

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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. Excitation-scan mirror array system advancements to hyperspectral imaging applications

   https://doi.org/10.1117/12.2546485  

   Parker, Marina; Browning, Craig M.; Mayes, Sam A.; Deal, Joshua; Gunn Mayes, Samantha; Rich, Thomas C.; Leavesley, Silas J.; Brown, Thomas G.; Wilson, Tony; Waller, Laura (February 2020, Proc. SPIE 11245, Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXVII)

   Hyperspectral imaging (HSI) technology has been applied in a range of fields for target detection and mixture analysis. While its original applications were in remote sensing, modern uses include agriculture, historical document authentications and medicine. HSI has shown great utility in fluorescence microscopy; however, acquisition speeds have been slow due to light losses associated with spectral filtering. We are currently developing a rapid hyperspectral imaging platform for 5-dimensional imaging (RHIP-5D), a confocal imaging system that will allow users to obtain simultaneous measurements of many fluorescent labels. We have previously reported on optical modeling performance of the system. This previous model investigated geometrical capability of designing a multifaceted mirror imaging system as an initial approach to sample light at many wavelengths. The design utilized light-emitting diodes (LEDs) and a multifaceted mirror array to combine light sources into a liquid light guide (LLG). The computational model was constructed using Monte Carlo optical ray software (TracePro, Lambda Research Corp.). Recent results presented here show transmission has increased up to 9% through parametric optimization of each component. Future work will involve system validation using a prototype engineered based on our optimized model. System requirements will be evaluated to determine if potential design changes are needed to improve the system. We will report on spectral resolution to demonstrate feasibility of the RHIP-5D as a promising solution for overcoming current HSI acquisition speed and sensitivity limitations. 

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4. 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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5. CloudRadianceHSI

   https://doi.org/10.21227/75e3-4e88  

   Russell, Randy; Kursun, Olcay (October 2025, IEEE DataPort)

   This dataset includes 30 hyperspectral cloud images captured during the Summer and Fall of 2022 at Auburn University at Montgomery, Alabama, USA (Latitude N, Longitude W) using aResonon Pika XC2 Hyperspectral Imaging Camera. Utilizing the Spectronon software, the images were recorded with integration times between 9.0-12.0 ms, a frame rate of approximately 45 Hz, and a scan rate of 0.93 degrees per second. The images are calibrated to give spectral radiance in microflicks at 462 spectral bands in the 400 – 1000 nm wavelength region with a spectral resolution of 1.9 nm. A 17 m focal length objective lens was used giving a field of view equal to 30.8 degrees and an integration field of view of 0.71 mrad. These settings enable detailed spectral analysis of both dynamic cloud formations and clear sky conditions. Funded by NSF grant 2003740, this dataset is designed to advance understanding of diffuse solar radiation as influenced by cloud coverage.  The dataset is organized into 30 folders, each containing a hyperspectral image file (.bip), a header file (.hdr) with metadata, and an RGB render for visual inspection. Additional metadata, including date, time, central pixel azimuth, and altitude, are cataloged in an accompanying MS Excel file. A custom Python program is also provided to facilitate the reading and display of the HSI files.  The images can also be read and analyzed using the free version of the Spectron software available at https://resonon.com/software. To enrich this dataset, we have added a supplementary ZIP file containing multispectral (4-channel) image versions of the original hyperspectral scenes, together with the corresponding per-pixel photon flux and spectral radiance values computed from the full spectrum. These additions extend the dataset’s utility for machine learning and data fusion research by enabling comparative analysis between reduced-band multispectral imagery and full-spectrum hyperspectral data. The ExpandAI Challenge task is to develop models capable of predicting photon flux and radiance—derived from all 462 hyperspectral bands—using only the four multispectral channels. This benchmark aims to stimulate innovation in spectral information recovery, spectral-spatial inference, and physically informed deep learning for atmospheric imaging applications. 

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