research-article

A Composite Image Processing Technique to Enhance Segmentation of Ultrasound Images

Authors:

Mahmood Alzubaidi,

Khaled Al-Thelaya,

Michel Makhlouf,

Khalid Alyafei,

Mowafa HousehAuthors Info & Claims

DMIP '22: Proceedings of the 2022 5th International Conference on Digital Medicine and Image Processing

Pages 1 - 7

https://doi.org/10.1145/3576938.3576939

Published: 15 March 2023 Publication History

Abstract

In ultrasound images, the speckle noise phenomenon is a typical issue that limits the accuracy of the images obtained from any quantitative measurement. Noise elimination in ultrasound images in the pre-processing stage is an important step to make the image fit for the following steps involved in image segmentation. However, various noises produce a range of significant impacts on the quality of the image and thus tend to affect the interpretation of neural networks. In this study, 35 different image processing techniques, including denoising, feature descriptor, edge detection, miscellaneous, clustering, morphological, sharpening, and composite techniques were used to determine the most optimal ultrasound image in order to improve the segmentation of ultrasound images. The performance of image processing techniques was compared using a statistical parameter, peak signal-to-noise ratio (PSNR). All techniques were examined on deep learning segmentation approach. The segmentation performance was evaluated using mean intersection over union (mIoU) and mean pixel accuracy (mPA). The results showed that the composite image technique (FancyPCA + Bilateral + Gabor) slightly enhanced the segmentation performance, with the most ideal mIoU 0.96893%, mPA 0.97831%, and average PSNR 53.034 dB.

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Cited By

Alzubaidi MShah UAgus MHouseh M(2024)FetSAM: Advanced Segmentation Techniques for Fetal Head Biometrics in Ultrasound ImageryIEEE Open Journal of Engineering in Medicine and Biology10.1109/OJEMB.2024.33824875(281-295)Online publication date: 2024
https://doi.org/10.1109/OJEMB.2024.3382487
Alzubaidi MShah UShah HHouseh M(2023)Conversion of Pixel to Millimeter in Ultrasound Images: A Methodological Approach and Dataset2023 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)10.1109/CIBCB56990.2023.10264909(1-6)Online publication date: 29-Aug-2023
https://doi.org/10.1109/CIBCB56990.2023.10264909

Index Terms

A Composite Image Processing Technique to Enhance Segmentation of Ultrasound Images
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Image segmentation
  2. Computer graphics
    1. Image manipulation
      1. Image processing

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cover image ACM Other conferences

DMIP '22: Proceedings of the 2022 5th International Conference on Digital Medicine and Image Processing

November 2022

88 pages

ISBN:9781450397643

DOI:10.1145/3576938

Copyright © 2022 ACM.

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Publication History

Published: 15 March 2023

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DMIP 2022

DMIP 2022: 2022 5th International Conference on Digital Medicine and Image Processing

November 10 - 13, 2022

Kyoto, Japan

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Cited By

Alzubaidi MShah UAgus MHouseh M(2024)FetSAM: Advanced Segmentation Techniques for Fetal Head Biometrics in Ultrasound ImageryIEEE Open Journal of Engineering in Medicine and Biology10.1109/OJEMB.2024.33824875(281-295)Online publication date: 2024
https://doi.org/10.1109/OJEMB.2024.3382487
Alzubaidi MShah UShah HHouseh M(2023)Conversion of Pixel to Millimeter in Ultrasound Images: A Methodological Approach and Dataset2023 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)10.1109/CIBCB56990.2023.10264909(1-6)Online publication date: 29-Aug-2023
https://doi.org/10.1109/CIBCB56990.2023.10264909

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