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Cancerous object detection using morphological region-based active contour in ultrasound images

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  • معلومة اضافية
    • Contributors:
      Department of Electrical & Information Engineering; Universitas Gadjah Mada; Department of Electrical Engineering; Universitas Negeri Semarang (UNNES); Département Procédés de Mise en oeuvre des Milieux Granulaires (PMMG-ENSMSE); Centre Sciences des Processus Industriels et Naturels (SPIN-ENSMSE); École des Mines de Saint-Étienne (Mines Saint-Étienne MSE); Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT)-École des Mines de Saint-Étienne (Mines Saint-Étienne MSE); Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT); Laboratoire Georges Friedel (LGF-ENSMSE); Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT)-Université de Lyon-Centre National de la Recherche Scientifique (CNRS); Universitas Negeri Semarang
    • بيانات النشر:
      HAL CCSD
      IOP Publishing
    • الموضوع:
      2019
    • Collection:
      Mines de Saint-Etienne: Archives Ouvertes / Open Archive (HAL)
    • الموضوع:
    • نبذة مختصرة :
      International audience ; Ultrasound is widely utilized in radiological screening to achieve early cancer investigations. Alongside this utilization, the need of object detection and segmentation techniques highly increases as crucial procedure of computer aided diagnosis tool. In addition, the industrial revolution 4.0 also demands automation and digitization in every technological development including computer aided diagnosis systems. This paper presents a morphological region-based active contour called MoRbAC to automatically detect the cancerous objects. Global level set active contour is initially employed to quick segment all objects in the whole image. Inhomogeneity in ultrasound images will lead to erroneous segmentation result. Hence,several morphology operations are taken to enhance it. The cancerous objects are then specifically detected by comparative calculation of area similarity. The proposed MoRbAC was tested in the real ultrasound images of breast and thyroid which validated by manual ground truth localization. Measurements of overlapping and disagreement regions are applied as quantitative indexes to demonstrate its performance. Average values of each validation has achieved i.e accuracy 98.58±0.89%, sensitivity 89.58±7.69%, specificity 99.58±0.11%, precision 95.58±2.77%, similarity 92.36±4.67%. In conclusion, the high performance of MoRbAC indicates its potential for practical applications in ultrasound computer aided diagnosis.
    • Relation:
      emse-02472462; https://hal-emse.ccsd.cnrs.fr/emse-02472462; https://hal-emse.ccsd.cnrs.fr/emse-02472462/document; https://hal-emse.ccsd.cnrs.fr/emse-02472462/file/A%20Nugroho_J%20Debayle%20Jour%20Phy%202020.pdf
    • الرقم المعرف:
      10.1088/1742-6596/1444/1/012011
    • الدخول الالكتروني :
      https://hal-emse.ccsd.cnrs.fr/emse-02472462
      https://hal-emse.ccsd.cnrs.fr/emse-02472462/document
      https://hal-emse.ccsd.cnrs.fr/emse-02472462/file/A%20Nugroho_J%20Debayle%20Jour%20Phy%202020.pdf
      https://doi.org/10.1088/1742-6596/1444/1/012011
    • Rights:
      http://creativecommons.org/licenses/by/ ; info:eu-repo/semantics/OpenAccess
    • الرقم المعرف:
      edsbas.67D0F2B3