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    •   BracU IR
    • School of Data and Sciences (SDS)
    • Department of Computer Science and Engineering (CSE)
    • Thesis & Report, BSc (Computer Science and Engineering)
    • View Item
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    Cervical Cancer Detection from Cervix Image Using Pap smear Imaging through CNN

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    15201035, 15201038, 15201034, 15201044_CSE.pdf (4.144Mb)
    Date
    2020-04
    Publisher
    Brac University
    Author
    Bhuiyan, Mazedul Haque
    Tabassum, Fariba
    Bushra, Umme
    Shwon, Md.Mahbub Rahman
    Metadata
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    URI
    http://hdl.handle.net/10361/14464
    Abstract
    Uterine cervical cancer is the second most regular gynecological harm around the world. The appraisal of the degree of sickness is fundamental for arranging ideal treatment. Imaging procedures are progressively utilized in the pre-treatment workup of cervical malignancy[22]. Presently, MRI for the neighborhood degree of sickness assessment and PET-check for removed ailment appraisal is considered as firstline procedures. In any case, over the most recent couple of years, ultrasound has picked up consideration as an imaging system for assessing ladies with cervical cancer.In this paper, we will take a shot at the advancement of a profound conviction system to order ultrasound pictures of the cervical cells to recognize cervical malignant growth. This postulation talks about the depiction of examples of single pap-smear cells from a current database set up at Herlev University Hospital. Wellbeing, the apparatus ought to be utilized before disease improvement to distinguish pre-dangerous cells in the uterine cervix[16]. For the separation among ordinary and unusual cells, open cell qualities, for example, area, position, and splendor of the core and cytoplasm are utilized. The exhibition of the classifier is determined on the rate total blunder but on the other hand is tried on the recurrence of bogus negative and bogus positive mistakes. The point is to support the all out mistake instead of the outcomes acquired already. A detailed overview of Herlev University Hospital’s latest pap- data prepares a new comparison platform Papsmear for publishing on Twitter. The papsmear collection consists of 917 experiments on 7 separate types of normal and irregular cells spread unequally. Every sample is represented by 20 characteristics. The average performance of the tested classifiers indicates no substantial change in earlier tests, but similar results are obtained using very basic methods.
    Keywords
    Cervical Cancer; Deep Learning; Cervix; Prediction; PCA; t-SNE; AUC-ROC Curve; XGBooster; SVM; CNN
     
    Description
    This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2020.
     
    Cataloged from PDF version of thesis.
     
    Includes bibliographical references (pages 37-39).
    Department
    Department of Computer Science and Engineering, Brac University
    Collections
    • Thesis & Report, BSc (Computer Science and Engineering)

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