Paper Info
Title
OralViewer: 3D Demonstration of Dental Surgeries for Patient Education with Oral Cavity Reconstruction from a 2D Panoramic X-ray
Abstract
ABSTRACT Patient’s understanding on forthcoming dental surgeries is required by patient-centered care and helps reduce anxiety. Due to the complexity of dental surgeries and the patient-dentist expertise gap, conventional techniques of patient education are usually not effective for explaining surgical steps. In this paper, we present OralViewer—the first interactive application that enables dentist’s demonstration of dental surgeries in 3D to promote patients’ understanding. OralViewer takes a single 2D panoramic dental X-ray to reconstruct patient-specific 3D teeth structures, which are then assembled with registered gum and jaw bone models for complete oral cavity modeling. During the demonstration, OralViewer enables dentists to show surgery steps with virtual dental instruments that can animate effects on a 3D model in real-time. A technical evaluation shows that our deep learning model achieves a mean Intersection over Union (IoU) of 0.771 for 3D teeth reconstruction. A patient study with 12 participants shows OralViewer can improve patients’ understanding of surgeries. A preliminary expert study with 3 board-certified dentists further verifies the clinical validity of our system.
Year
DOI
Venue
2021
10.1145/3397481.3450695
IUI
Keywords
DocType
Citations 
deep learning, 3D visualization, patient education
Conference
0
PageRank 
References 
Authors
0.34
0
11
Name
Order
Citations
PageRank
Yuan Liang113.40
Liang Qiu202.37
Tiancheng Lu300.34
Zhujun Fang400.34
Dezhan Tu500.34
Jiawei Yang692.72
Tiandong Zhao7142.18
Yiting Shao800.68
Kun Wang942556.96
Xiang 'Anthony' Chen1024.08
Lei He11167.77