Artificial Neural Networks Can be Used as Alternative Method to Estimate Loss Tooth Root Sizes for Prediction of Dental Implants

Year 2017, Volume: 38 Issue: 2, 385 - 395, 25.04.2017

Oğuzhan Görler , Serkan Akkoyun

https://doi.org/10.17776/cumuscij.304902

Cited By: 3

Abstract

The aim of this study was to investigate the
feasibility of estimation of canine root length and cervical width by an
artificial neural network method with an appropriate setting. We randomly
obtained 120 representative samples of routine panoramic radiographs by
computer tomography (CT). Of 120 samples, 96 (80%) were used in training phase
and 24 (20%) were used in test phase after a randomized selection. The intertuberal length (IL) of maxilla and canine root length (RL) and
canine root cervical width (CW) of the right canine tooth was measured and was
entered to a datum file. According to the results, the method is
convenient with this purpose. The mean square error values are lied between 2% and 4.4% for the estimations. This shows
that ANN is an alternative method for the prediction of canine root length and
cervical width. Since an ANN software, as a cost-effective tool that can be
purchased and after a training procedure that can be easily performed by an
experienced person, the ANN system can have a place in implant surgery after
further studies and optimization of software setting. An ANN software can be adapted to the dental implant surgery after
proper setting and training procedures that can be easily performed by an
experienced person and it can have a place in implant surgery after further
expanded studies and optimization of software setting.

Keywords

Neural Network, Dental Implant, Canine, Dentistry

Dental İmplantlara Alternatif Değerlendirme Metodu Olarak Kayıp Dişlerin Boyutlarının Yapay Sinir Ağı Yöntemiyle Tahmini

Abstract

Bu çalışmanın amacı, kanin diş kökü uzunluğu ve
servikal genişliğinin yapay bir sinir ağı yöntemi (ANN) ile tahmin edilmesinin
fizibilitesini araştırmaktır. Bilgisayarlı tomografilerin (BT) panoramic
görüntüleri ile rasgele 120 hasta değerlendirildi. 120 örnekten 96'sı (% 80)
eğitim fazında, 24'ü (% 20) randomize bir seçimden sonra test aşamasında
kullanıldı. Sağ maksiller kanin kök uzunluğu (RL), servikal genişliği (CW) ve intertuberal
uzunluk (IL) ölçülerek bir veri dosyasına oluşturuldu. Sonuçlara göre, yöntem
bu amaca uygun bulundu. Tahminler için ortalama karesel hata değerleri %2 ile
%4.4 arasında bulundu. Bu ANN yönteminin kanin kök boyu ve servikal genişliği
için alternatif bir yöntem olduğunu göstermektedir. Satın alınabilecek uygun
maliyetli bir araç olan ANN yazılımı ve sistemi, daha ileri çalışmalar ve
yazılım ayarlarının optimizasyonundan sonra dental implant ameliyatına adapte
edilebilir, implant ameliyatlarında implantların boy ve genişlikleri için
öngörü imkanı verebilir. 

Keywords

Yapay Sinir Ağı Yöntemi, Dental İmplant, Kanin, Diş Hekimliği

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