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Computer-aided system for bleeding detection in WCE images based on CNN-GRU network

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Abstract

Wireless capsule endoscopy (WCE) is a non-invasive video technique used to investigate gastrointestinal diseases such as hemorrhage, ulcer, and polyp. Automatic detection systems that primarily use features derived from WCE images are being developed in order to bypass a difficult and time-consuming manual evaluation procedure. Bleeding is one the most prevalent anomalies in WCE images, This anomaly can be identified by its color features. In this paper, a computer-aided approach for detecting bleeding frames is proposed. The suggested system consists of three major phases: preprocessing, feature extraction using optimized convolutional neural network (CNN), and classification based on gated recurrent unit (GRU). We investigate our proposed CNN-GRU based methodology using a publicly available dataset called MICCAI 2017, and the results of the experiments demonstrate that our strategy is both efficient and robust, achieving high accuracy of 99.39% with considerable performance gains over the state-of-the-art.

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Data Availability

The dataset analysed during the current study is available in the [Red Lesion Endoscopy Dataset] repository, [https://rdm.inesctec.pt/dataset/nis-2018-003].

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Acknowledgements

This work was partially supported by the Ministry of National Education, Vocational Training, Higher Education and Scientific Research, The Ministry of Industry, Trade and Green and Digital Economy, Digital Development Agency (ADD) and National Center for Scientific and Technical Research (CNRST). Project nmber: ALKHAWARIZMI/2020/20.

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

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Authors and Affiliations

  1. LabSIV, Department of Computer Science, Faculty of Sciences, Ibnou Zohr University, BP 8106, 80000, Agadir, Morocco

    Samira Lafraxo, Mohamed El Ansari & Lahcen Koutti

  2. Informatics and Applications Laboratory Department of Computer Science Faculty of Sciences, Moulay Ismail University, Meknès, Morocco

    Mohamed El Ansari

Authors
  1. Samira Lafraxo
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  2. Mohamed El Ansari
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Contributions

Methodology and Funding Acquisition, (S. LAFRAXO & M. EL ANSARI); Project Administration, (M. EL ANSARI & L. KOUTTI); Writing: Original Draft Preparation, (S. LAFRAXO); Writing: Review and Editing (M. EL ANSARI); All authors read and approved the final manuscript.

Corresponding author

Correspondence to Samira Lafraxo.

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Lafraxo, S., El Ansari, M. & Koutti, L. Computer-aided system for bleeding detection in WCE images based on CNN-GRU network. Multimed Tools Appl 83, 21081–21106 (2024). https://doi.org/10.1007/s11042-023-16305-w

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