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COVID-19 Detection from Lung CT Scan Using Transfer Learning Models

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Bangabandhu and Digital Bangladesh (ICBBDB 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1550))

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Abstract

Initial prognosis of the COVID-19 is vital for pandemic avoidance. Nowadays, The lung infection driven by SARS-CoV-2 has spread throughout the world, urged the World Health Organization (WHO) to proclaim it a pandemic disease for its rapid spread. The COVID-19 infection has detrimental effects on respiration, and the severity of the infection might be discovered using particular imaging techniques and lung CT scan is one of them. So, quick and precise coronavirus disease (COVID-19) testing is a possibility utilizing computed tomography (CT) scan images with the alliance of AI. The goal of this work is to use lung CT scans to recognize COVID-19 using transfer learning models and a comparative analysis among various transfer learning models using CT scans. The research was conducted using two standard datasets containing 2792 lung CT scan images. Xception, MobileNetV2, InceptionV3, DenseNet201, and InceptionResNetV2 were utilized to tag COVID-19 as negative or positive in case of the CT scan inputs. Our used transfer learning based Xception, MobileNetV2, InceptionV3, DenseNet201, and IncpetionResNetV2 achieved the highest validation accuracy of 92.19%, 97.40%, 85.42%, 86.98%, and 95.31% accordingly.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Ahsanullah University of Science and Technology, Dhaka, Bangladesh

    Nazmus Shakib Shadin, Silvia Sanjana & Nusrat Jahan Lisa

Authors
  1. Nazmus Shakib Shadin
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  2. Silvia Sanjana
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  3. Nusrat Jahan Lisa
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Correspondence to Nazmus Shakib Shadin .

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Editors and Affiliations

  1. United International University, Dhaka, Bangladesh

    A. K. M. Muzahidul Islam

  2. Woosong University, Daejeon, Korea (Republic of)

    Jia Uddin

  3. University of Liberal Arts Bangladesh, Dhaka, Bangladesh

    Nafees Mansoor

  4. United International University, Dhaka, Bangladesh

    Shahriar Rahman

  5. University of Asia Pacific, Dhaka, Bangladesh

    Shah Murtaza Rashid Al Masud

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Shadin, N.S., Sanjana, S., Lisa, N.J. (2022). COVID-19 Detection from Lung CT Scan Using Transfer Learning Models. In: Islam, A.K.M.M., Uddin, J., Mansoor, N., Rahman, S., Al Masud, S.M.R. (eds) Bangabandhu and Digital Bangladesh. ICBBDB 2021. Communications in Computer and Information Science, vol 1550. Springer, Cham. https://doi.org/10.1007/978-3-031-17181-9_5

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  • DOI: https://doi.org/10.1007/978-3-031-17181-9_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-17180-2

  • Online ISBN: 978-3-031-17181-9

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