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- Title
The Combination of Adaptive Convolutional Neural Network and Bag of Visual Words in Automatic Diagnosis of Third Molar Complications on Dental X-Ray Images.
- Authors
Ngoc, Vo Truong Nhu; Agwu, Agwu Chinedu; Son, Le Hoang; Tuan, Tran Manh; Nguyen Giap, Cu; Thanh, Mai Thi Giang; Duy, Hoang Bao; Ngan, Tran Thi
- Abstract
In dental diagnosis, recognizing tooth complications quickly from radiology (e.g., X-rays) takes highly experienced medical professionals. By using object detection models and algorithms, this work is much easier and needs less experienced medical practitioners to clear their doubts while diagnosing a medical case. In this paper, we propose a dental defect recognition model by the integration of Adaptive Convolution Neural Network and Bag of Visual Word (BoVW). In this model, BoVW is used to save the features extracted from images. After that, a designed Convolutional Neural Network (CNN) model is used to make quality prediction. To evaluate the proposed model, we collected a dataset of radiography images of 447 patients in Hanoi Medical Hospital, Vietnam, with third molar complications. The results of the model suggest accuracy of 84% ± 4%. This accuracy is comparable to that of experienced dentists and radiologists.
- Subjects
VIETNAM; CONVOLUTIONAL neural networks; THIRD molars; X-ray imaging
- Publication
Diagnostics (2075-4418), 2020, Vol 10, Issue 4, p209
- ISSN
2075-4418
- Publication type
Article
- DOI
10.3390/diagnostics10040209