مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Verion

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

video

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

sound

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Version

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

View:

260
مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Download:

0
مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Cites:

Information Journal Paper

Title

Diagnosis of Cervical Cancer Using Texture and Morphological Features in Pap Smear Images

Pages

  489-493

Abstract

 Background: Cervical cancer is one of the most common cancers among women worldwide, which can be diagnosed more quickly via using digital systems. The purpose of this study was to classify the cells in Pap smear test images into two types of normal and abnormal by using image processing to diagnose Cervical cancers. Methods: We used Herlev public database, which contained 917 cells. 35 geometric and 263 histologic features such as Gray Level Co-Occurrence Matrix (GLCM), Local Binary Pattern (LBP), and rotational gradient histogram were extracted from cell images. T test filter method was applied on the data set after extraction of geometrical and textural features. We used different Classification methods such as support vector machine (SVM), decision tree (DT), k nearest neighbor (KNN) and ensemble classifiers. Findings: The best results were for SVM classifier as 97. 5% accuracy in two-class Classification with 20 features. Conclusion: Feature selection and feature extraction methods are very important for classify normal and abnormal cervical cell images. By optimizing and choosing the right methods, we can optimizing accuracy, and speed and error (2-3 percent).

Cites

  • No record.
  • References

  • No record.
  • Cite

    APA: Copy

    Hosseinabadi, Hamid, MEHRI DEHNAVI, ALIREZA, TALEBI, ARDESHIR, Momenzadeh, Mohammadreza, & VARD, ALIREZA. (2020). Diagnosis of Cervical Cancer Using Texture and Morphological Features in Pap Smear Images. JOURNAL OF ISFAHAN MEDICAL SCHOOL (I.U.M.S), 38(583 ), 489-493. SID. https://sid.ir/paper/954645/en

    Vancouver: Copy

    Hosseinabadi Hamid, MEHRI DEHNAVI ALIREZA, TALEBI ARDESHIR, Momenzadeh Mohammadreza, VARD ALIREZA. Diagnosis of Cervical Cancer Using Texture and Morphological Features in Pap Smear Images. JOURNAL OF ISFAHAN MEDICAL SCHOOL (I.U.M.S)[Internet]. 2020;38(583 ):489-493. Available from: https://sid.ir/paper/954645/en

    IEEE: Copy

    Hamid Hosseinabadi, ALIREZA MEHRI DEHNAVI, ARDESHIR TALEBI, Mohammadreza Momenzadeh, and ALIREZA VARD, “Diagnosis of Cervical Cancer Using Texture and Morphological Features in Pap Smear Images,” JOURNAL OF ISFAHAN MEDICAL SCHOOL (I.U.M.S), vol. 38, no. 583 , pp. 489–493, 2020, [Online]. Available: https://sid.ir/paper/954645/en

    Related Journal Papers

  • No record.
  • Related Seminar Papers

  • No record.
  • Related Plans

  • No record.
  • Recommended Workshops






    Move to top
    telegram sharing button
    whatsapp sharing button
    linkedin sharing button
    twitter sharing button
    email sharing button
    email sharing button
    email sharing button
    sharethis sharing button