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International Work-Conference on Bioinformatics and Biomedical Engineering

IWBBIO 2020: Bioinformatics and Biomedical Engineering pp 683–694Cite as

Novel Thermal Image Classification Based on Techniques Derived from Mathematical Morphology: Case of Breast Cancer

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Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 12108))

Abstract

Image processing (IP) is a method of converting an image to digital form by performing operations on it to obtain an improved image or to extract useful information from it. It is a type of signal distribution in which the input is an image such as a video image or a photograph, and the output can be an image or associated characteristics. Besides, this system includes the processing of images in the form of two-dimensional signals, while applying signal processing methods already defined for them. One of the essential steps in IP is a combined application of erosion and dilation procedures, which is part of the mathematical morphology. This article presents a novel thermal image classification based on techniques derived from mathematical morphology. In the processing of grayscale breast cancer images, this method reveals the region of interest as the whitest area.

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References

  1. Mambou, S., Krejcar, O., Maresova, P., Selamat, A., Kuca, K.: Novel four stages classification of breast cancer using infrared thermal imaging and a deep learning model. In: Rojas, I., Valenzuela, O., Rojas, F., Ortuño, F. (eds.) IWBBIO 2019. LNCS, vol. 11466, pp. 63–74. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-17935-9_7

    Chapter  Google Scholar 

  2. Mambou, S.J., Maresova, P., Krejcar, O., Selamat, A., Kuca, K.: Breast Cancer detection using infrared thermal imaging and a deep learning model. Sensors (Basel) 18 (2018). https://doi.org/10.3390/s18092799

  3. Mambou, S., Krejcar, O., Selamat, A.: Approximate outputs of accelerated Turing machines closest to their halting point. In: Nguyen, N.T., Gaol, F.L., Hong, T.-P., Trawiński, B. (eds.) ACIIDS 2019. LNCS (LNAI), vol. 11431, pp. 702–713. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-14799-0_60

    Chapter  Google Scholar 

  4. Mambou, S., Krejcar, O., Kuca, K., Selamat, A.: Novel cross-view human action model recognition based on the powerful view-invariant features technique. Future Internet 10, 89 (2018). https://doi.org/10.3390/fi10090089

    Article  Google Scholar 

  5. Alpar, O., Krejcar, O.: A comparative study on chrominance based methods in dorsal hand recognition: single image case. In: Mouhoub, M., Sadaoui, S., Ait Mohamed, O., Ali, M. (eds.) IEA/AIE 2018. LNCS (LNAI), vol. 10868, pp. 711–721. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-92058-0_68

    Chapter  Google Scholar 

  6. Samuel, T., Assefa, D., Krejcar, O.: Framework for effective image processing to enhance tuberculosis diagnosis. In: Nguyen, N.T., Hoang, D.H., Hong, T.-P., Pham, H., Trawiński, B. (eds.) ACIIDS 2018. LNCS (LNAI), vol. 10752, pp. 376–384. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-75420-8_36

    Chapter  Google Scholar 

  7. Zhang, X., et al.: Cancer cell membrane-coated rare earth doped nanoparticles for tumor surgery navigation in NIR-II imaging window. Chem. Eng. J. 385, 123959 (2020). https://doi.org/10.1016/j.cej.2019.123959

    Article  CAS  Google Scholar 

  8. Nobel, T.B., et al.: Incidence and risk factors for isolated esophageal cancer recurrence to the brain. Ann. Thorac. Surg. 109, 329–336 (2020). https://doi.org/10.1016/j.athoracsur.2019.09.028

    Article  PubMed  Google Scholar 

  9. Bouaynaya, N., Schonfeld, D.: Theoretical foundations of spatially-variant mathematical morphology Part II: gray-level images. IEEE Trans. Pattern Anal. Mach. Intell. 30, 837–850 (2008). https://doi.org/10.1109/TPAMI.2007.70756

    Article  PubMed  Google Scholar 

  10. Devarriya, D., Gulati, C., Mansharamani, V., Sakalle, A., Bhardwaj, A.: Unbalanced breast cancer data classification using novel fitness functions in genetic programming. Expert Syst. Appl. 140, 112866 (2020). https://doi.org/10.1016/j.eswa.2019.112866

    Article  Google Scholar 

  11. Peter, S.C., et al.: Combination of an ultrafast TWIST-VIBE Dixon sequence protocol and diffusion-weighted imaging into an accurate easily applicable classification tool for masses in breast MRI. Eur. Radiol. (2020). https://doi.org/10.1007/s00330-019-06608-8

  12. Samet, H.: Applications of Spatial Data Structures: Computer Graphics, Image Processing, and GIS. Addison-Wesley Longman Publishing Co., Inc., Boston (1990)

    Google Scholar 

  13. Asem, M.M., Oveisi, I.S., Janbozorgi, M.: Blood vessel segmentation in modern wide-field retinal images in the presence of additive Gaussian noise. J. Med. Imaging 5 (2018). https://doi.org/10.1117/1.JMI.5.3.031405

  14. Alpar, O., Krejcar, O.: Virtual road condition prediction through license plates in 3D simulation. In: Nguyen, N.-T., Manolopoulos, Y., Iliadis, L., Trawiński, B. (eds.) ICCCI 2016. LNCS (LNAI), vol. 9875, pp. 269–278. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-45243-2_25

    Chapter  Google Scholar 

  15. Alpar, O., Krejcar, O.: Detection of irregular thermoregulation in hand thermography by fuzzy C-means. In: Rojas, I., Ortuño, F. (eds.) IWBBIO 2018. LNCS, vol. 10814, pp. 255–265. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-78759-6_24

    Chapter  Google Scholar 

  16. Alpar, O., Krejcar, O.: Frequency and time localization in biometrics: STFT vs. CWT. In: Mouhoub, M., Sadaoui, S., Ait Mohamed, O., Ali, M. (eds.) IEA/AIE 2018. LNCS (LNAI), vol. 10868, pp. 722–728. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-92058-0_69

    Chapter  Google Scholar 

  17. Alpar, O., Krejcar, O.: Thermal imaging for localization of anterior forearm subcutaneous veins. In: Rojas, I., Ortuño, F. (eds.) IWBBIO 2018. LNCS, vol. 10814, pp. 243–254. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-78759-6_23

    Chapter  Google Scholar 

  18. Fernandez, J.-J.: Computational methods for electron tomography. Micron 43, 1010–1030 (2012). https://doi.org/10.1016/j.micron.2012.05.003

    Article  CAS  PubMed  Google Scholar 

  19. Agulleiro, J.I., Vazquez, F., Garzon, E.M., Fernandez, J.J.: Hybrid computing: CPU+GPU co-processing and its application to tomographic reconstruction. Ultramicroscopy 115, 109–114 (2012). https://doi.org/10.1016/j.ultramic.2012.02.003

    Article  CAS  PubMed  Google Scholar 

  20. Buades, A., Coll, B., Morel, J.M.: A review of image denoising algorithms, with a new one. Multiscale Model. Simul. 4, 490–530 (2005). https://doi.org/10.1137/040616024

    Article  Google Scholar 

  21. Legaz-Aparicio, Á.-G., Verdu-Monedero, R., Angulo, J.: Adaptive morphological filters based on a multiple orientation vector field dependent on image local features. J. Comput. Appl. Math. 330, 965–981 (2018). https://doi.org/10.1016/j.cam.2017.05.001

    Article  Google Scholar 

  22. Landström, A., Thurley, M.J.: Adaptive morphology using tensor-based elliptical structuring elements. Pattern Recogn. Lett. 34, 1416–1422 (2013). https://doi.org/10.1016/j.patrec.2013.05.003

    Article  Google Scholar 

  23. Mambou, S., Krejcar, O., Maresova, P., Selamat, A., Kuca, K.: Novel hand gesture alert system. Appl. Sci. 9, 3419 (2019). https://doi.org/10.3390/app9163419

    Article  Google Scholar 

  24. Li, Y., Li, Z., Zhu, Y., Li, B., Xiong, W., Huang, Y.: Thermal infrared small ship detection in sea clutter based on morphological reconstruction and multi-feature analysis. Appl. Sci. 9, 3786 (2019). https://doi.org/10.3390/app9183786

    Article  Google Scholar 

  25. Marek, T., Krejcar, O., Selamat, A.: Possibilities for development and use of 3D applications on the android platform. In: Nguyen, N.T., Trawiński, B., Fujita, H., Hong, T.-P. (eds.) ACIIDS 2016. LNCS (LNAI), vol. 9622, pp. 519–529. Springer, Heidelberg (2016). https://doi.org/10.1007/978-3-662-49390-8_51

    Chapter  Google Scholar 

  26. de Souza, G.A.G.R., Brioschi, M.L., Vargas, J.V.C., Morais, K.C.C., Dalmaso Neto, C., Neves, E.B.: Reference breast temperature: proposal of an equation. Einstein (Sao Paulo) 13, 518–524 (2015). https://doi.org/10.1590/S1679-45082015AO3392

    Article  Google Scholar 

  27. Mesicek, J., Zdarsky, J., Dolezal, R., Krejcar, O., Kuca, K.: Simulations of light propagation and thermal response in biological tissues accelerated by graphics processing unit. In: Nguyen, N.-T., Manolopoulos, Y., Iliadis, L., Trawiński, B. (eds.) ICCCI 2016. LNCS (LNAI), vol. 9876, pp. 242–251. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-45246-3_23

    Chapter  Google Scholar 

  28. Kubicek, J., Penhaker, M., Augustynek, M., Cerny, M., Oczka, D., Maresova, P.: Detection and dynamical tracking of temperature facial distribution caused by alcohol intoxication with using of modified OTSU regional segmentation. In: Nguyen, N.T., Hoang, D.H., Hong, T.-P., Pham, H., Trawiński, B. (eds.) ACIIDS 2018. LNCS (LNAI), vol. 10752, pp. 357–366. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-75420-8_34

    Chapter  Google Scholar 

  29. Brain MRI Images for Brain Tumor Detection. https://kaggle.com/navoneel/brain-mri-images-for-brain-tumor-detection. Accessed 9 Feb 2020

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Acknowledgment

The work and the contribution were supported by the SPEV project “Smart Solutions in Ubiquitous Computing Environments”, 2019, University of Hradec Kralove, Faculty of Informatics and Management, Czech Republic.

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Authors and Affiliations

  1. Center for Basic and Applied Research, Faculty of Informatics and Management, University of Hradec Kralove, Rokitanskeho 62, 500 03, Hradec Kralove, Czech Republic

    Sebastien Mambou, Ondrej Krejcar, Ali Selamat, Michal Dobrovolny, Petra Maresova & Kamil Kuca

  2. Faculty of Computing, Universiti Teknologi Malaysia, 81310, Johor Baharu, Johor, Malaysia

    Ali Selamat

Authors
  1. Sebastien Mambou
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  2. Ondrej Krejcar
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  3. Ali Selamat
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  4. Michal Dobrovolny
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  5. Petra Maresova
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  6. Kamil Kuca
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Corresponding author

Correspondence to Ondrej Krejcar .

Editor information

Editors and Affiliations

  1. University of Granada, Granada, Spain

    Ignacio Rojas

  2. University of Granada, Granada, Spain

    Olga Valenzuela

  3. University of Granada, Granada, Spain

    Fernando Rojas

  4. University of Granada, Granada, Spain

    Luis Javier Herrera

  5. University of Chicago and Fundacion Progreso y Salud, Granada, Spain

    Francisco Ortuño

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Mambou, S., Krejcar, O., Selamat, A., Dobrovolny, M., Maresova, P., Kuca, K. (2020). Novel Thermal Image Classification Based on Techniques Derived from Mathematical Morphology: Case of Breast Cancer. In: Rojas, I., Valenzuela, O., Rojas, F., Herrera, L., Ortuño, F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2020. Lecture Notes in Computer Science(), vol 12108. Springer, Cham. https://doi.org/10.1007/978-3-030-45385-5_61

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  • DOI: https://doi.org/10.1007/978-3-030-45385-5_61

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-45384-8

  • Online ISBN: 978-3-030-45385-5

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