TY - JOUR
T1 - Automatic for Generating Landmark Mandibular Panoramic Radiography Image
AU - Nafi’iyah, Nur
AU - Fatichah, Chastine
AU - Herumurti, Darlis
AU - Astuti, Eha Renwi
AU - Putra, Ramadhan Hardani
AU - Akbar, Agus Subhan
N1 - Publisher Copyright:
© (2024), (Intelligent Network and Systems Society). All Rights Reserved.
PY - 2024
Y1 - 2024
N2 - Forensic gender identification based on teeth is needed to identify incomplete victims, only bones and teeth. Previous studies identified gender by manually or semi-automatically measuring mandibular parameters based on landmark points. Gender identification, especially for victims of mass disasters, requires accuracy, so it takes longer, especially if there are many parameters to be measured. In addition, the observer's manual or semi-automatic measurements may give different results. This study proposes a new automatic approach to generate ten mandibular landmark points from panoramic radiographic images for gender identification. We propose a step, namely determining the centroid point of the mandibular image and using linear regression to predict ten mandibular landmark points such as the two condyle, two gonion, four ramus, and two body of the mandible. This study obtained panoramic radiographic images from the Academic Dental Hospital, Universitas Airlangga. We calculated the distance between expert mandibular landmark points and the predicted results to evaluate performance. The prediction of the landmark with the smallest average distance is the lower point of the mandibular body 1 pixel. In comparison, the predicted landmark with the most extended average length is a gonion of 10 pixels.
AB - Forensic gender identification based on teeth is needed to identify incomplete victims, only bones and teeth. Previous studies identified gender by manually or semi-automatically measuring mandibular parameters based on landmark points. Gender identification, especially for victims of mass disasters, requires accuracy, so it takes longer, especially if there are many parameters to be measured. In addition, the observer's manual or semi-automatic measurements may give different results. This study proposes a new automatic approach to generate ten mandibular landmark points from panoramic radiographic images for gender identification. We propose a step, namely determining the centroid point of the mandibular image and using linear regression to predict ten mandibular landmark points such as the two condyle, two gonion, four ramus, and two body of the mandible. This study obtained panoramic radiographic images from the Academic Dental Hospital, Universitas Airlangga. We calculated the distance between expert mandibular landmark points and the predicted results to evaluate performance. The prediction of the landmark with the smallest average distance is the lower point of the mandibular body 1 pixel. In comparison, the predicted landmark with the most extended average length is a gonion of 10 pixels.
KW - Automatic
KW - Dental panoramic radiography
KW - Gender identification
KW - Linear regression
KW - Mandibular landmark generate
UR - http://www.scopus.com/inward/record.url?scp=85184184155&partnerID=8YFLogxK
U2 - 10.22266/ijies2024.0229.49
DO - 10.22266/ijies2024.0229.49
M3 - Article
AN - SCOPUS:85184184155
SN - 2185-310X
VL - 17
SP - 584
EP - 595
JO - International Journal of Intelligent Engineering and Systems
JF - International Journal of Intelligent Engineering and Systems
IS - 1
ER -