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A Brief Review of Kidney Stone Detection and Prediction Techniques

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Proceedings of International Conference on Communication and Computational Technologies (ICCCT 2023)

Part of the book series: Algorithms for Intelligent Systems ((AIS))

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Abstract

When it comes to the treatment of kidney stones, imaging is a crucial diagnostic tool, and the very first step in determining which therapeutic choices to utilize is vitally significant. Non-contrast CT of the abdominal area routinely delivers the best precise test but also exposes patients to ionizing radiation as a result of the procedure. Ultrasonography has traditionally had lesser sensitivity and accuracy than computed tomography (CT), but it does not involve radiation use. These imaging modalities, on the other hand, were shown to have equal diagnostic accuracy when compared to a randomized controlled experiment, which was conducted in an emergency department. Both modes of transportation have their pros as well as downsides. In patients with established stone illness, plain film radiography of the kidney, ureter, as well as bladder (KUB) is the most appropriate imaging technique for assessing interval stone development. It is less beneficial in the context of acute stones, however. Although magnetic resonance imaging (MRI) allows for 3D imaging without the use of radiation, it is both expensive and hard to see stones at this time. The examination of kidney disease is thus a critical aspect of the research into nephrolithiasis to better comprehend the function of trace components in the production of kidney stones as well as to develop future methods for management and prophylaxis of stone formation as well as recurrence. The purpose of this study is to examine methods and procedures that are routinely utilized in the evaluation of urinary calculi. And along with this, a cheap and non-radiation technology can be developed by improving the techniques, methods, and algorithms being used so far.

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Authors and Affiliations

  1. Computer Science and Engineering, Arya College of Engineering and I.T., Jaipur, 302028, India

    Sharwan Buri & Vishal Shrivastava

Authors
  1. Sharwan Buri
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  2. Vishal Shrivastava
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Correspondence to Vishal Shrivastava .

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Editors and Affiliations

  1. Christ ((Deemed to be University), Bengaluru, Karnataka, India

    Sandeep Kumar

  2. Rajasthan Institute of Engineering and Technology, Jaipur, India

    Saroj Hiranwal

  3. Rajasthan Technical University, Kota, India

    S.D. Purohit

  4. University of Technology Sydney, Ultimo, NSW, Australia

    Mukesh Prasad

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Buri, S., Shrivastava, V. (2023). A Brief Review of Kidney Stone Detection and Prediction Techniques. In: Kumar, S., Hiranwal, S., Purohit, S., Prasad, M. (eds) Proceedings of International Conference on Communication and Computational Technologies. ICCCT 2023. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-99-3485-0_42

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