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Quaternion-Valued Convolutional Neural Network Applied for Acute Lymphoblastic Leukemia Diagnosis

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Intelligent Systems (BRACIS 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13074))

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Abstract

The field of neural networks has seen significant advances in recent years with the development of deep and convolutional neural networks. Although many of the current works address real-valued models, recent studies reveal that neural networks with hypercomplex-valued parameters can better capture, generalize, and represent the complexity of multidimensional data. This paper explores the quaternion-valued convolutional neural network application for a pattern recognition task from medicine, namely, the diagnosis of acute lymphoblastic leukemia. Precisely, we compare the performance of real-valued and quaternion-valued convolutional neural networks to classify lymphoblasts from the peripheral blood smear microscopic images. The quaternion-valued convolutional neural network achieved better or similar performance than its corresponding real-valued network but using only 34% of its parameters. This result confirms that quaternion algebra allows capturing and extracting information from a color image with fewer parameters.

This work was supported in part by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001.

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Author information

Authors and Affiliations

  1. Instituto Federal de Educação, Ciência e Tecnologia de São Paulo, São Paulo, Brazil

    Marco Aurélio Granero

  2. Escuela Superior Politécnica del Litoral, Guayaquil, Ecuador

    Cristhian Xavier Hernández

  3. Universidade Estadual de Campinas, Campinas, Brazil

    Marcos Eduardo Valle

Authors
  1. Marco Aurélio Granero
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  2. Cristhian Xavier Hernández
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  3. Marcos Eduardo Valle
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Correspondence to Marcos Eduardo Valle .

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Editors and Affiliations

  1. Universidade Federal de Sergipe, São Cristóvão, Brazil

    André Britto

  2. Universidade de São Paulo, São Paulo, Brazil

    Karina Valdivia Delgado

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Granero, M.A., Hernández, C.X., Valle, M.E. (2021). Quaternion-Valued Convolutional Neural Network Applied for Acute Lymphoblastic Leukemia Diagnosis. In: Britto, A., Valdivia Delgado, K. (eds) Intelligent Systems. BRACIS 2021. Lecture Notes in Computer Science(), vol 13074. Springer, Cham. https://doi.org/10.1007/978-3-030-91699-2_20

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  • DOI: https://doi.org/10.1007/978-3-030-91699-2_20

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