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Medical Diagnosis Using Image-Based Deep Learning and Supervised Hashing Approach

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Applications of Artificial Intelligence and Machine Learning

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 925))

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Abstract

Due to the high use of digital images in hospitals and clinics, there is an increase in the size of medical images’ databases. It makes it difficult to manage and to retrieve similar images for the localization of disease and differentiate between the diseases from the databases which forces the use of features-based systems. This study presents a novel CNN architecture for the Highlight Based Recovery framework for retrieving medical images quickly and efficiently for identifying Covid-19. For the purpose of training the network, multimodal datasets are utilized and split into two types. The lungs invaded by Covid-19 are in one class, while the reduced lung images are in another. To decrease the search space, the compensated CNN’s learnt components are obtained with the hash method’s quick processing feature. With class-based expectations, the best retrieval outcomes are attained with 94.5% average prediction performance and 0.87 average mean precision for this retrieval challenge.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, USICT, GGSIPU, New Delhi, India

    Aman Dureja

  2. Department of Information Technology, BPIT, Rohini, New Delhi, India

    Aman Dureja

  3. Department of Computer Science and Engineering, BPIT, Rohini, New Delhi, India

    Payal Pahwa

Authors
  1. Aman Dureja
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  2. Payal Pahwa
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Corresponding author

Correspondence to Aman Dureja .

Editor information

Editors and Affiliations

  1. University of South Florida Sarasota–Manatee, Sarasota, FL, USA

    Bhuvan Unhelker

  2. Bournemouth University, Poole, UK

    Hari Mohan Pandey

  3. School of Engineering and Technology, Sharda University, Greater Noida, India

    Gaurav Raj

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Dureja, A., Pahwa, P. (2022). Medical Diagnosis Using Image-Based Deep Learning and Supervised Hashing Approach. In: Unhelker, B., Pandey, H.M., Raj, G. (eds) Applications of Artificial Intelligence and Machine Learning. Lecture Notes in Electrical Engineering, vol 925. Springer, Singapore. https://doi.org/10.1007/978-981-19-4831-2_30

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  • DOI: https://doi.org/10.1007/978-981-19-4831-2_30

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-4830-5

  • Online ISBN: 978-981-19-4831-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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