Pemisahan Objek Sel Tumpang Tindih pada Citra Pap Smear dengan Metode Deep Learning dan Watershed
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Keywords:
Object Separation, Cervical Cancer, Pap Smear Image, Overlapping Cells, Segmentation
AbstractThe object observed in the Pap Smear image is Cervical Cancer which forms overlapping cells. This cancer must be observed early because it is a disease that causes the death of thousands of women worldwide every year. The death rate from this disease is the fourth highest among women. One way to be aware of this disease is to do an early check on the Pap Smear test image. This cell separation process uses the image segmentation method. This method is one of the important steps to be able to identify existing cell objects. This study proposes a segmentation method to separate 2 overlapping cells in the RepomedUNM dataset. The dataset is engineered in the manufacture of synthetic Pap Smear images. The segmentation method proposed is a Deep Learning-based method so that it can identify 2 overlapping cells in one area. The level of accuracy of the test with an average score of Intersection over Union (IoU) is 0.9003. 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Published
2022-11-30
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How to Cite
Jamil, M., & Riana, D. (2022). Pemisahan Objek Sel Tumpang Tindih pada Citra Pap Smear dengan Metode Deep Learning dan Watershed. Jurnal Informasi Dan Teknologi, 4(4), 253-259. https://doi.org/10.37034/jidt.v4i4.243
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