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  • br Conflict of interest br The authors

    2022-06-21


    Conflict of interest
    The authors declared that there is no ‘Conflict of interest’.
    Acknowledgments
    The authors would like to acknowledge the Department of Elec-trical and Information Engineering, Universitas Gadjah Mada and Directorate General of Higher Education, Ministry of Research, Technology and Higher Education, Republic of Indonesia for fund-ing this Cyclophosphamide research work through the ‘‘Penelitian Tim Pasca Sarjana” Research Grant. The authors would also like to thank colleagues of Intelligent System research group in our Department for inspiring discussion and anonymous reviewers for encouraging reviews and recommendations.
    References
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    Please cite this article as: R. Nurfauzi, H. A. Nugroho, I. Ardiyanto et al., Autocorrection of lung boundary on 3D CT lung cancer imagesq, Journal of King Saud University – Computer and Information Sciences, https://doi.org/10.1016/j.jksuci.2019.02.009
    10 R. Nurfauzi et al. / Journal of King Saud University – Computer and Information Sciences xxx (xxxx) xxx
    ‘‘LIDC-IDRI - The Cancer Imaging Archive (TCIA) Public Access - Cancer Imaging Archive Wiki.” [Online]. Available: https://wiki.cancerimagingarchive.net/ display/Public/LIDC-IDRI (accessed: 21-Feb-2017).
    M.R.S., 2016. Automatic 3D pulmonary nodule detection in CT Images: a survey.
    Zhou, S., Cheng, Y., Tamura, S., 2014. Biomedical signal processing and control automated lung segmentation and smoothing techniques for inclusion of juxtapleural nodules and pulmonary vessels on chest CT images. Biomed. Signal Process. Control 13, 62–70.
    Contents lists available at ScienceDirect
    Expert Systems With Applications
    journal homepage: www.elsevier.com/locate/eswa
    Automatic reconstruction of overlapped cells in breast cancer FISH images
    T. Les a, T. Markiewicz a,c, S. Osowski b,∗, M. Jesiotr c a Faculty of Electrical Engineering, Warsaw University of Technology, Koszykowa 75, Warsaw, Poland
    b Faculty of Electronics, Military University of Technology, Kaliskiego 2, 00-908 Warsaw, Poland c Military Institute of Medicine, Warsaw, Poland
    Article history:
    Keywords:
    Cell reconstruction
    Image segmentation
    PatchMatch
    Pattern recognition 
    This paper presents a new image processing and analysis technique for the quality evaluation of cell nu-clei to support medical diagnostics in breast cancer. The technique allows cell nuclei that are deformed or overlapped by biological material to be reconstructed. The paper proposes a sensitivity and similarity approach, enriching the PatchMatch correspondence algorithm in accurate cell reconstruction. Its appli-cation in reconstruction processes enables accelerated computations and an increased probability of ob-taining appropriate segmentation results. The numerical results demonstrate that the developed system allows for automatic and effective cell nuclei reconstruction with an acceptable average area accuracy level above 85% compared with manual human results (assuming manual segmentation as a true value). The reconstruction system allows for the recovery of the proper shape of the analyzed distorted cells very rapidly and in a repeatable manner. An additional advantage of the procedure is that the nuclei area overlapped by artifacts or other cells can be determined. The experimental results prove the high utility of the method in final HER2 gene amplification assessment in breast cancer images.