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Annual Conference on Medical Image Understanding and Analysis

MIUA 2019: Medical Image Understanding and Analysis pp 377–388Cite as

Polyp Segmentation with Fully Convolutional Deep Dilation Neural Network

Evaluation Study

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1065))

Abstract

Analyses of polyp images play an important role in an early detection of colorectal cancer. An automated polyp segmentation is seen as one of the methods that could improve the accuracy of the colonoscopic examination. The paper describes evaluation study of a segmentation method developed for the Endoscopic Vision Gastrointestinal Image ANAlysis – (GIANA) polyp segmentation sub-challenges. The proposed polyp segmentation algorithm is based on a fully convolutional network (FCN) model. The paper describes cross-validation results on the training GIANA dataset. Various tests have been evaluated, including network configuration, effects of data augmentation, and performance of the method as a function of polyp characteristics. The proposed method delivers state-of-the-art results. It secured the first place for the image segmentation tasks at the 2017 GIANA challenge and the second place for the SD images at the 2018 GIANA challenge.

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Notes

  1. 1.

    It is envisaged that supplementary results of the ongoing research on polyp segmentation will be gradually made available at: https://github.com/ybguo1/Polyp-Segmentation.

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Acknowledgements

The authors would like to acknowledge the organizers of the Gastrointestinal Image ANAlysis – (GIANA) challenges for providing video colonoscopy polyp images.

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Authors and Affiliations

  1. Computer Vision and Machine Learning (CVML) Research Group, School of Engineering, University of Central Lancashire, Preston, UK

    Yunbo Guo & Bogdan J. Matuszewski

Authors
  1. Yunbo Guo
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  2. Bogdan J. Matuszewski
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Correspondence to Yunbo Guo .

Editor information

Editors and Affiliations

  1. University of Liverpool, Liverpool, UK

    Yalin Zheng

  2. University of Liverpool, Liverpool, UK

    Bryan M. Williams

  3. University of Liverpool, Liverpool, UK

    Ke Chen

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Guo, Y., Matuszewski, B.J. (2020). Polyp Segmentation with Fully Convolutional Deep Dilation Neural Network. In: Zheng, Y., Williams, B., Chen, K. (eds) Medical Image Understanding and Analysis. MIUA 2019. Communications in Computer and Information Science, vol 1065. Springer, Cham. https://doi.org/10.1007/978-3-030-39343-4_32

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  • DOI: https://doi.org/10.1007/978-3-030-39343-4_32

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  • Online ISBN: 978-3-030-39343-4

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