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International Symposium on Visual Computing

ISVC 2020: Advances in Visual Computing pp 224–235Cite as

Real-Time Contrast Enhancement for 3D Medical Images Using Histogram Equalization

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12509))

Abstract

Medical professionals rely on medical imaging to help diagnose and treat patients. It is therefore important for them to be able to see all the details captured in the images. Often the use of contrast enhancement or noise reduction techniques are used to help improve the image quality. This paper introduces a real-time implementation of 3D Contrast Limited Adaptive Histogram Equalization (CLAHE) to enhance 3D medical image stacks, or volumes. This algorithm can be used interactively by medical doctors to help visualize the 3D medical volumes and prepare for surgery. It also introduces two novel extensions to the algorithm to allow a user to interactively decide on what region to focus the enhancement: Focused CLAHE and Masked CLAHE. Focused CLAHE applies the 3D CLAHE algorithm to a specified block of the entire medical volume and Masked CLAHE applies the algorithm to a selected organ or organs. These three contributions can be used, to not only help improve the visualization of 3D medical image stacks, but also to provide that contrast enhancement in real-time.

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Acknowledgements

This research was funded in part by a grant from The Leona M. and Harry B. Helmsley Charitable Trust. We thank Trevor Hedstrom for his help with the implementation of the shader version of the algorithm.

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Authors and Affiliations

  1. University of California San Diego, La Jolla, CA, USA

    Karen Lucknavalai & Jürgen P. Schulze

Authors
  1. Karen Lucknavalai
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  2. Jürgen P. Schulze
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Corresponding author

Correspondence to Jürgen P. Schulze .

Editor information

Editors and Affiliations

  1. University of Nevada Reno, Reno, NV, USA

    George Bebis

  2. Stony Brook University, Stony Brook, NY, USA

    Zhaozheng Yin

  3. Drexel University, Philadelphia, PA, USA

    Edward Kim

  4. RWTH Aachen University, Aachen, Germany

    Jan Bender

  5. University of Edinburgh, Edinburgh, UK

    Kartic Subr

  6. IBM Research – Cambridge, Cambridge, MA, USA

    Bum Chul Kwon

  7. University of Waterloo, Waterloo, ON, Canada

    Jian Zhao

  8. Graz University of Technology, Graz, Austria

    Denis Kalkofen

  9. The Hong Kong Polytechnic University, Hong Kong, Hong Kong

    George Baciu

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Lucknavalai, K., Schulze, J.P. (2020). Real-Time Contrast Enhancement for 3D Medical Images Using Histogram Equalization. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2020. Lecture Notes in Computer Science(), vol 12509. Springer, Cham. https://doi.org/10.1007/978-3-030-64556-4_18

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  • DOI: https://doi.org/10.1007/978-3-030-64556-4_18

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-64555-7

  • Online ISBN: 978-3-030-64556-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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