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A De-Speckling Framework for Optical Coherence Tomography Images

  • 2022
  • OriginalPaper
  • Chapter
Published in:
Authors
Pradeep K. Gupta
Farooq Husain
Published in
Proceedings of Trends in Electronics and Health Informatics
Publisher
Springer Nature Singapore

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Abstract

The chapter introduces a novel de-speckling framework for Optical Coherence Tomography (OCT) images, addressing the challenge of speckle noise inherent in these images. The framework employs a hybrid approach consisting of three steps: preprocessing with SRAD filtering, de-noising using curvelet transform, and post-processing with Huber variant of TV regularization. This method aims to enhance OCT image quality for accurate retinal disease diagnosis, outperforming existing filters in terms of PSNR, CNR, and SSIM. The chapter provides a comprehensive review of speckle noise modeling and compares the proposed framework with state-of-the-art filters, demonstrating its superior performance in both visual and numerical results.
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previous chapter Digitalization of Healthcare System in India—A Perspective and PESTLE Analysis
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Title
A De-Speckling Framework for Optical Coherence Tomography Images
Authors
Pradeep K. Gupta
Farooq Husain
Copyright Year
2022
Publisher
Springer Nature Singapore
Book
Proceedings of Trends in Electronics and Health Informatics

Print ISBN: 978-981-16-8825-6

Electronic ISBN: 978-981-16-8826-3

Copyright Year: 2022

DOI
https://doi.org/10.1007/978-981-16-8826-3_18
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