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Vol.12, No.2, May 2023. ISSN: 2217-8309 eISSN: 2217-8333
TEM Journal
TECHNOLOGY, EDUCATION, MANAGEMENT, INFORMATICS Association for Information Communication Technology Education and Science |
Model of Watershed Segmentation in Deep Learning Method to Improve Identification of Cervical Cancer at Overlay Cells
Dwiza Riana, Muh Jamil, Sri Hadianti, Jufriadif Na’am, Hadi Sutanto, Ronald Sukwadi
© 2023 Dwiza Riana, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)
Citation Information: TEM Journal. Volume 12, Issue 2, Pages 813-819, ISSN 2217-8309, DOI: 10.18421/TEM122-26, May 2023.
Received: 28 November 2022. Revised: 16 March 2023.
Abstract:
Cervical cancer is a disease that is very scary for women because it is the cause of death among women. To be aware of this disease is to do an early examination through the Pap Smear (PS) test. In terms identifying overlapping cancer cells, it still has low accuracy. Therefore, this research was carried out with the aim of getting the level of cell separation with high accuracy. This study uses a model to develop the Watershed segmentation technique in the Deep Learning Method. The data tested in this study comes from the RepomedUNM dataset. The amount of data tested is 420 overlapping images with the formulation of 1,260 test images. The results of this study can very well separate each overlapping cell with an average Intersection over Union (IoU) score of 0.9061. Each result can be divided fully by the whole of its area, so the final results of overlapping cells were successfully separated with an average score of 0.945. Therefore, this research can be used as a reference in identifying cervical cancer cells.
Keywords –cervical cancer, Pap Smear, segmentation, deep learning, overlay cell. |
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