Article Per Year (5 Year)
p-Index From 2020 - 2025
0.835
P-Index
This Author published in this journals
All Journal JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JSAI (Journal Scientific and Applied Informatics)
Iryani, Lemi
Unknown Affiliation
Computer Science & IT Engineering

Published : 5 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING

 1 
Combination of Image Enhancement and U-Net Architecture for Cervical Cell Semantic Segmentation Rudiansyah, Rudiansyah; Iryani, Lemi; Kesuma, Lucky Indra; Sari, Puspa; Alamsyah, Agung
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 7 No. 2 (2024): Vol. 7 No. 2 (2024): Issues January 2024
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v7i2.10399

Abstract

Cervical cancer is the second leading cause of death in women and ranks fourth as a disease that occurs in women worldwide. Cervical cancer is a disease that is difficult to detect and can be detected when it is in an advanced stage. This requires early prevention by carrying out a pap-smear examination. Pap-smear examination manually requires a relatively long time, so a tool is needed by segmentation. Segmentation is image processing by performing perfection between the intended object and the background. One of the CNN methods commonly used in medical image segmentation is the U-Net architecture. Segmentation in this study was carried out on the nucleus and cytoplasm of the Herlev dataset using the U-Net architecture combined with data augmentation and image enhancement. In the learning process, this research resulted in a fairly high IoU value of 78% and an RMSE close to 20%. The results of this study also yielded an accuracy value of 89%, with an average precision, recall and F1 score of 89%, 89% and 88.67%, respectively. This shows that the combination of the CNN U-Net architecture with image quality improvement and data augmentation is quite good at segmenting cervical cells for the nucleus and cytoplasm
Co-Authors Alamsyah, Agung Ayumi, Vina Dianing Asri, Sri Ghufron, Akhmad Kesuma, Lucky Indra Noprisson, Handrie Purba, Mariana Puspa Sari, Puspa Rudiansyah Rudiansyah, Rudiansyah Salamah, Umniy Umilizah , Nia