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Floor of log: a novel intelligent algorithm for 3D lung segmentation in computer tomography images

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Abstract

This work presents a high-performance approach for 3D lung segmentation tasks in computer tomography images using a new intelligent machine learning algorithm called Floor of Log(FoL). The Support Vector Machine was used to learn the better parameter of the FoL algorithm using the parenchyma and its border as labels. Sensitivity, Matthews Correlation Coefficient (MCC), Hausdorff Distance (HD), Dice, Accuracy (ACC), and Jaccard were used to evaluate the proposed algorithm. The FoL was compared with recent 3D region growing, 3D Adaptive Crisp Active Contour, 3D OsiriX toolbox, and Level-set algorithm based on the coherent propagation method algorithms. The FoL algorithm achieves good results with approximately 19 s in the most significant result in an exam with 430 slices and presents similarity indexes achieving HD 3.5, DICE 83.63, and Jaccard 99.73 and qualitative indexes achieving Sensitivity 83.87, MCC 83.08, and ACC 99.62. The proposed approach of this work showed a simple and powerful algorithm to segment lung in computer tomography images of the chest region by combining similar textures, highlighting the lung structure. The FoL was presented as a new supervised clustering algorithm which can be trained to achieve better results and attached to other approaches as Convolutional Deep Neural Networks applications.

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Acknowledgements

The authors are grateful to King Saud University, Riyadh, Saudi Arabia for funding this work through Researchers Supporting Project number RSP-2020/18. This study was also supported in part by the CAPES - Finance Code 001, and by the CNPq via Grants Nos. 311973/2018-3 and 430274/2018-1.

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Authors and Affiliations

  1. Laboratório de Processamento Digital de Imagens, Sinais e Computação Aplicada, Instituto Federal de Federal de Educação, Ciência e Tecnologia do Ceará (IFCE), Ceará, Brazil

    Solon Alves Peixoto, Aldísio G. Medeiros & Pedro P. Rebouças Filho

  2. Information Systems Department, College of Computer and Information Sciences, King Saud University, Riyadh, 11543, Saudi Arabia

    Mohammad Mehedi Hassan

  3. School of Computing and Information Systems, Faculty of Science and Technology, Athabasca University, Edmonton, Canada

    M. Ali Akber Dewan

  4. Programa de Pós-Graduação em Informática Aplicada, Laboratório de Bioinformática, Universidade de Fortaleza, Fortaleza-CE, Brazil

    Victor Hugo C. de Albuquerque

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  1. Solon Alves Peixoto
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  2. Aldísio G. Medeiros
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  3. Mohammad Mehedi Hassan
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  6. Pedro P. Rebouças Filho
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Correspondence to Mohammad Mehedi Hassan.

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Peixoto, S.A., Medeiros, A.G., Hassan, M.M. et al. Floor of log: a novel intelligent algorithm for 3D lung segmentation in computer tomography images. Multimedia Systems 28, 1151–1163 (2022). https://doi.org/10.1007/s00530-020-00698-x

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