@inproceedings{e73a2d4ff61846a384404c6efe3289e5,
title = "Cephalometric Landmark Detection on Cephalograms using Regression CNN",
abstract = "Cephalograms are an imaging process used by orthodontics to determine the position of cephalometric landmarks. These cephalometric landmarks are essentials to be found before any treatment to the patient can be performed. In this research, a CNN architecture to detect 31 cephalometric landmarks was proposed. The results shows that Mean Absolute Percentage Error (MAPE) of our proposed method achieves a value of 1.856%. Better than detectron2 with 2.443%.",
keywords = "CNN, Cephalograms, Cephalometric Landmarks, Detectron2",
author = "Aziz Fajar and Gusti Pangestu and Riyanarto Sarno and Ardani, {I. Gusti Aju Wahju}",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 5th International Conference on Information and Communications Technology, ICOIACT 2022 ; Conference date: 24-08-2022 Through 25-08-2022",
year = "2022",
doi = "10.1109/ICOIACT55506.2022.9972144",
language = "English",
series = "ICOIACT 2022 - 5th International Conference on Information and Communications Technology: A New Way to Make AI Useful for Everyone in the New Normal Era, Proceeding",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "150--154",
booktitle = "ICOIACT 2022 - 5th International Conference on Information and Communications Technology",
address = "United States",
}