Journal of Spectral Imaging,   Volume 10   Article ID a1   (2021)

Peer reviewed Paper

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

  • Deependra Mishra
  • Helena Hurbon
  • John Wang
  • Steven T. Wang
  • Tommy Du
  • Qian Wu
  • David Kim
  • Shiva Basir
  • Qian Cao
  • Hairong Zhang
  • Kathleen Xu
  • Andy Yu
  • Yifan Zhang
  • Yunshen Huang
  • Roman Garnett
  • Maria Gerasimchuk-Djordjevic
  • Mikhail Y. Berezin  
Department of Radiology, Washington University School of Medicine, 4515 McKinley Ave, St Louis, MO 63110, USA
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 https://orcid.org/0000-0003-1578-8526
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Department of Radiology, Washington University School of Medicine, 4515 McKinley Ave, St Louis, MO 63110, USA
[email protected]
 https://orcid.org/0000-0003-3181-6566
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Department of Radiology, Washington University School of Medicine, 4515 McKinley Ave, St Louis, MO 63110, USA and HSpeQ LLC, 4340 Duncan Ave, St Louis, MO 63110, USA
[email protected]
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Department of Radiology, Washington University School of Medicine, 4515 McKinley Ave, St Louis, MO 63110, USA and HSpeQ LLC, 4340 Duncan Ave, St Louis, MO 63110, USA
[email protected]
 https://orcid.org/0000-0002-5630-9010
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Department of Radiology, Washington University School of Medicine, 4515 McKinley Ave, St Louis, MO 63110, USA
[email protected]
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Department of Radiology, Washington University School of Medicine, 4515 McKinley Ave, St Louis, MO 63110, USA
[email protected]
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Department of Radiology, Washington University School of Medicine, 4515 McKinley Ave, St Louis, MO 63110, USA
[email protected]
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Department of Radiology, Washington University School of Medicine, 4515 McKinley Ave, St Louis, MO 63110, USA
[email protected]
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Department of Radiology, Washington University School of Medicine, 4515 McKinley Ave, St Louis, MO 63110, USA
[email protected]
 https://orcid.org/0000-0002-3900-0433
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Department of Radiology, Washington University School of Medicine, 4515 McKinley Ave, St Louis, MO 63110, USA
[email protected]
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Department of Radiology, Washington University School of Medicine, 4515 McKinley Ave, St Louis, MO 63110, USA
[email protected]
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Department of Radiology, Washington University School of Medicine, 4515 McKinley Ave, St Louis, MO 63110, USA
[email protected]
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Department of Radiology, Washington University School of Medicine, 4515 McKinley Ave, St Louis, MO 63110, USA
[email protected]
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Department of Radiology, Washington University School of Medicine, 4515 McKinley Ave, St Louis, MO 63110, USA
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Department of Computer Science and Engineering, Washington University, 1 Brookings Hall, St Louis, MO 63110, USA
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 https://orcid.org/0000-0002-0152-5453
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Art and Design Department, Missouri State University, 901 S. National Ave, Springfield, MO 65897, USA
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 Corresponding Author
Department of Radiology, Washington University School of Medicine, 4515 McKinley Ave, St Louis, MO 63110, USA and HSpeQ LLC, 4340 Duncan Ave, St Louis, MO 63110, USA
[email protected]
 https://orcid.org/0000-0002-2670-2487
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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.

Keywords: hyperspectral, multispectral, spectral imaging, IDCube, segmentation, geospatial, biomedical

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