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Effective deep learning based segmentation and classification in wireless capsule endoscopy images

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Abstract

Wireless capsule endoscopy is a noninvasive wireless imaging method that has grown in popularity over the last several years. One of the efficient and effective ways for examining the gastrointestinal system is using WCE. It sends a huge number of images in a single examination cycle, making abnormality analysis and diagnosis extremely difficult and time-consuming. As a result, in this research, we provide the Expectation maximum (EM) algorithm, a revolutionary deep-learning-based segmentation approach for GI tract recognition in WCE images. DeepLap v3+ can extract a variety of features including colour, shape, and geometry, as well as SURF (speed-up robust features). Thus the Lenet 5 based classification can be made in the extracted images. The effectiveness of the performances is carried out on a publicly available Kvasir-V2 dataset, on which our proposed approach achieves 99.12% accuracy 98.79% of precision, 99.05% of recall and 98.49% of F1- score when compared to existing approaches. Effectiveness benefits are demonstrated over multiple current state-of-the-art competing techniques on all performance variables we evaluated, especially mean of Intersection Over Union (IoU), IoU for background, and IoU for the entire class.

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Acknowledgements

We declare that this manuscript is original, has not been published before, and is not currently being considered for publication elsewhere.

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Authors and Affiliations

  1. School of Computer Science Engineering, Vellore Institute of Technology, VIT-AP University, Amaravathi, Andhra Pradesh, India

    Panguluri Padmavathi & Jonnadula Harikiran

  2. International Institute of Information Technology, Naya Raipur, Chhattisgarh, India

    J. Vijaya

Authors
  1. Panguluri Padmavathi
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  2. Jonnadula Harikiran
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  3. J. Vijaya
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The author confirms sole responsibility for the following: study conception and design, data collection, analysis and interpretation of results, and manuscript preparation.

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Correspondence to Jonnadula Harikiran or J. Vijaya.

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Padmavathi, P., Harikiran, J. & Vijaya, J. Effective deep learning based segmentation and classification in wireless capsule endoscopy images. Multimed Tools Appl 82, 47109–47133 (2023). https://doi.org/10.1007/s11042-023-14621-9

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  • DOI: https://doi.org/10.1007/s11042-023-14621-9

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