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Artificial Intelligence in Medical Image Processing for Airway Diseases

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Connected e-Health

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1021))

Abstract

Artificial intelligence is the most contentious issue in diagnostic and therapeutic medical imaging research today. Numerous artificial intelligence (AI)-based architectures have been created to accomplish a high-precision diagnosis. To expedite therapy, artificial intelligence software analyses X-rays, CT scans, MRIs, and other pictures for opacities as well as assists physicians in diagnosing and managing airway issues in the clinical context. Airway illnesses are the third most significant cause of mortality worldwide, affecting roughly 65 million people and claiming 3 million lives each year. Thus, this chapter examined how artificial intelligence can comprehend medical images of various respiratory illnesses, including cystic fibrosis, emphysema, pneumoconiosis, pulmonary edema and embolism, asthma, and TB. The first section of this chapter focused on ways to enhance care for patients who have respiratory problems. In the next part, we looked at how artificial intelligence may identify and diagnose various airway diseases. Another section of the chapter discussed a recently released study examining researchers’ efforts to analyze airway diseases using multiple machines and deep learning models. Finally, the chapter contained a comparative study based on the kind of airway disease diagnosed, the data set utilized, and performance variables. Additionally, we addressed the evaluation and discussion of our results to convey any new information or insights gleaned from our chapter’s conclusion.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Punjabi University, Patiala, India

    Apeksha Koul

  2. Department of Computer Science, Punjabi University, Patiala, India

    Rajesh K. Bawa

  3. Department of Computer Science and Engineering, Indus Institute of Technology & Engineering, Indus University, Ahmedabad, India

    Yogesh Kumar

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  1. Apeksha Koul
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  2. Rajesh K. Bawa
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  3. Yogesh Kumar
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Editors and Affiliations

  1. School of Computer Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar, Odisha, India

    Sushruta Mishra

  2. Grupo de Investigación BISITE, Departamento de Informática y Automática, Facultad de Ciencias, University of Salamanca, Instituto de Investigación Biomédica de Salamanca, Salamanca, Spain

    Alfonso González-Briones

  3. KIET Group of Institutions, Ghaziabad, Delhi-NCR, India

    Akash Kumar Bhoi

  4. School of Computer Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar, Odisha, India

    Pradeep Kumar Mallick

  5. Grupo de Investigación BISITE, Departamento de Informática y Automática, Facultad de Ciencias, University of Salamanca, Instituto de Investigación Biomédica de Salamanca, Salamanca, Spain

    Juan M. Corchado

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Koul, A., Bawa, R.K., Kumar, Y. (2022). Artificial Intelligence in Medical Image Processing for Airway Diseases. In: Mishra, S., González-Briones, A., Bhoi, A.K., Mallick, P.K., Corchado, J.M. (eds) Connected e-Health. Studies in Computational Intelligence, vol 1021. Springer, Cham. https://doi.org/10.1007/978-3-030-97929-4_10

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