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Dimensional & Spatial Analysis of Ultrasound Imaging Through Image Processing: A Review

In: New Trends in Computational Vision and Bio-inspired Computing

Author

Listed:
  • Kajal Rana

    (GJUS&T, Department of BME)

  • Anju Gupta

    (GJUS&T, Department of BME)

  • Anil Khatak

    (GJUS&T, Department of BME)

Abstract

Ultrasound imaging is one of the most generally & frequently used techniques in the medical field due to its low cost, portability and non-invasive nature. Kidney stones & tumors are the two form of the disorder that are accurately & correctly detectable by employing ultrasound imaging. This article provides an understanding of automation which could be embedded with the ultrasound system resulting in spatial as well as dimensional analysis of various kidneys disorders in ultrasound images through image processing. Usually, human visual perception is utilized for detecting the exact position & spatial dimension of these artifacts. The advent of new image processing era has enabled the new ways for detecting these kidney related artifacts accurately. With these new image processing techniques, the beginners/experience radiologists, doctors’ paramedics, etc. are able to draw correct conclusion regarding the presence of artifacts through these techniques and hence opt for a correct course of treatment for the removal of the identified disorder. A fast and accurate way of diagnosis can be achieved which leads to better therapy and confidence in patients. The aim of this review paper is to understand & review the various techniques of image processing which are frequently employed in the detection of disorders in ultrasound images. A brief comparison of these image processing techniques is also conducted where the comparing parameter is complexities & accuracy.

Suggested Citation

  • Kajal Rana & Anju Gupta & Anil Khatak, 2020. "Dimensional & Spatial Analysis of Ultrasound Imaging Through Image Processing: A Review," Springer Books, in: S. Smys & Abdullah M. Iliyasu & Robert Bestak & Fuqian Shi (ed.), New Trends in Computational Vision and Bio-inspired Computing, pages 763-771, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-41862-5_76
    DOI: 10.1007/978-3-030-41862-5_76
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