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International Conference on Pattern Recognition and Artificial Intelligence

ICPRAI 2020: Pattern Recognition and Artificial Intelligence pp 725–738Cite as

A Survey on Peripheral Blood Smear Analysis Using Deep Learning

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12068))

Abstract

Peripheral Blood Smear (PBS) analysis is a routine test carried out in specialized medical laboratories by specialists to assess some aspects of health status that are measured and assessed through blood. PBS analysis is prone to human errors and the usage of computer-based analysis can greatly enhance this process in terms of accuracy and cost. Despite the challenges, Deep Learning neural networks have shown impressive performance in this context. In this study the recent contributions are summarized along with the main challenges and future directions in this context.

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Acknowledgment

We thank Dr. Mohammad Al-Qudah from the pathology department at Jordan University of Science and Technology for his help in the medical background and for useful discussions about the possible future directions in PBS analysis.

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Authors and Affiliations

  1. Concordia University, Montreal, QC, H3G 1M8, Canada

    Rabiah Al-qudah & Ching Y. Suen

Authors
  1. Rabiah Al-qudah
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  2. Ching Y. Suen
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Corresponding author

Correspondence to Rabiah Al-qudah .

Editor information

Editors and Affiliations

  1. East China Normal University, Shanghai, China

    Yue Lu

  2. Paris Descartes University, Paris, France

    Nicole Vincent

  3. Hong Kong Baptist University, Kowloon, Hong Kong

    Pong Chi Yuen

  4. Sun Yat-sen University, Guangzhou, China

    Wei-Shi Zheng

  5. Polytechnique Montréal, Montreal, QC, Canada

    Farida Cheriet

  6. Concordia University, Montreal, QC, Canada

    Ching Y. Suen

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Al-qudah, R., Suen, C.Y. (2020). A Survey on Peripheral Blood Smear Analysis Using Deep Learning. In: Lu, Y., Vincent, N., Yuen, P.C., Zheng, WS., Cheriet, F., Suen, C.Y. (eds) Pattern Recognition and Artificial Intelligence. ICPRAI 2020. Lecture Notes in Computer Science(), vol 12068. Springer, Cham. https://doi.org/10.1007/978-3-030-59830-3_63

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  • DOI: https://doi.org/10.1007/978-3-030-59830-3_63

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-59829-7

  • Online ISBN: 978-3-030-59830-3

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