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XAI hybrid multi-staged algorithm for routine & quantum boosted oncological medical imaging

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Abstract

Medical imaging is the process of visualizing the diseased part, inside the patient’s body, with the aid of images. The field of medical imaging depends on several disciplines of science and technology, including physics, biological sciences, engineering, artificial intelligence and mathematics. These disciplines contribute in designing the imaging devices, installation of the devices and the collection and analysis of the images for better understanding and future forecasting of the disease prognosis and prevention. In this manuscript, medical images are analyzed with the aid of the a new hybrid machine learning approach, where the breast cancer images are studied in a novel manner with the help of a newly devised algorithm that is conceptually more sound as compared to already existing algorithms. Step by step stages are followed by the algorithm to process, filter, segment, statistically analyze and to classify the medical images. The results from different classification tools are compared in a novel manner, inspired from the explainable artificial intelligence tools for classification. The algorithm devised during this research can serve as a useful tool, in the evolving field of particle - physics -imaging.

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Acknowledgements

The source of medical images is: https://www.repository.cam.ac.uk/handle/1810/250394 under the license: https://creativecommons.org/licenses/by/2.0/uk/ The authors would like to thank the Deanship of Scientific Research at Umm Al-Qura University for supporting this work by Grant Code: (22UQU4340548DSR05), (Author: Mohamed Abdelsabour Fahmy; Email: maselim@uqu.edu.sa).

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Authors and Affiliations

  1. Department of Mathematics, Comsats University Islamabad, Lahore, 54000, Pakistan

    Ayesha Sohail & Usama Ahmad Khan

  2. Department of Mathematics, Jamoum University College, Umm Al-Qura University, Alshohdaa, Jamoum, 25371, Makkah, Saudi Arabia

    Mohamed Abdelsabour Fahmy

  3. Faculty of Computers and Informatics, Suez Canal University, New Campus, Ismailia, 41522, Egypt

    Mohamed Abdelsabour Fahmy

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  1. Ayesha Sohail
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  2. Mohamed Abdelsabour Fahmy
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  3. Usama Ahmad Khan
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Correspondence to Ayesha Sohail.

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Sohail, A., Fahmy, M.A. & Khan, U.A. XAI hybrid multi-staged algorithm for routine & quantum boosted oncological medical imaging. Comp. Part. Mech. 10, 209–219 (2023). https://doi.org/10.1007/s40571-022-00490-w

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  • DOI: https://doi.org/10.1007/s40571-022-00490-w

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