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Current Medical Imaging

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ISSN (Print): 1573-4056
ISSN (Online): 1875-6603

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Mini-Review Article

A Review on Lossless Compression Techniques for Wireless Capsule Endoscopic Data

Author(s): Caren Babu and D. Abraham Chandy*

Volume 17, Issue 1, 2021

Published on: 23 April, 2020

Page: [27 - 38] Pages: 12

DOI: 10.2174/1573405616666200423084725

Price: $65

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Abstract

Background: The videos produced during wireless capsule endoscopy have larger data size causing difficulty in transmission with limited bandwidth. The constraint on wireless capsule endoscopy hinders the performance of the compression module.

Objectives: The objectives of this paper are as follows: (i) to conduct an extensive review of the lossless compression techniques and (ii) to find out the limitations of the existing system and the possibilities for improvement.

Methods: The literature review was conducted with a focus on the compression schemes satisfying minimum computational complexity, less power dissipation and low memory requirements for hardware implementation. A thorough study of various lossless compression techniques was conducted under two perspectives, i.e., techniques applied to Bayer CFA and RGB images. The detail of the various stages of wireless capsule endoscopy compression was investigated to have a better understanding. The suitable performance metrics for evaluating the compression techniques were listed from various literature studies.

Results: In addition to the Gastrolab database, WEO clinical endoscopy atlas and Gastrointestinal atlas were found to be better alternatives for experimentation. Pre-processing operations, especially new subsampling patterns need to be given more focus to exploit the redundancies in the images. Investigations showed that encoder module can be modified to bring more improvement towards compression. The real-time endoscopy still exists as a promising area for exploration.

Conclusion: This review presents a research update on the details of wireless capsule endoscopy compression together with the findings as an eye-opener and guidance for further research.

Keywords: Bayer CFA images, endoscopes, lossless compression algorithms, medical imaging, RGB images, WEO.

Graphical Abstract

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