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An ensemble framework of deep neural networks for colorectal polyp classification

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Abstract

Colorectal cancer (CRC) is caused by malignant polyps which must be resected and examined for accurate classification. Biopsy, the manual workflow of polyp classification is time-intensive task and requires an automated solution. The objective of this study is to develop an accurate virtual biopsy tool for polyp classification. Moreover, automated assessment of polyps is a challenging task due to the similarities in their patterns, and in contrast to existing studies on binary classification, the outcome of multi-class classification requires evaluation through advanced evaluation measures. The proposed method combined the strength of individual weak learner for an accurate weighted-average ensemble deep learning classification. At first, base-classifiers were pretrained on the ImageNet database. Second, an average ensemble was built and evaluated for enhancing the performance, an appropriate combination of weights was chosen through grid search and assigned to the models. The performance evaluation of the proposed method in terms of F1-micro (0.80), F1-macro (0.81), F1-weighted (0.84) metrics, model reliability using Cohen’s Kappa Coefficient (0.60) and Mathew Correlation Co-efficient value (0.49) for binary dataset shows the superiority over existing models. The higher rates of precision and recall show potential usage of the proposed system in the development of a virtual biopsy tool.

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Acknowledgments

The authors would like to thank Basque Biobank who kindly provided us the access to their PICCOLO RGB/NBI database.

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Author notes

  1. Muhammad Usman and Wei Qi Yan contributed equally to this work.

Authors and Affiliations

  1. Auckland University of Technology, 55 Wellesley Street East, Auckland CBD, Auckland, 1010, New Zealand

    Farah Younas, Muhammad Usman & Wei Qi Yan

  2. Shaheed Zulfikar Ali Bhutto Institute of Science and Technology, Islamabad, 44000, Pakistan

    Muhammad Usman

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  1. Farah Younas
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Correspondence to Farah Younas.

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Younas, F., Usman, M. & Yan, W.Q. An ensemble framework of deep neural networks for colorectal polyp classification. Multimed Tools Appl 82, 18925–18946 (2023). https://doi.org/10.1007/s11042-022-14177-0

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