Mobile Dental Image Analysis for Automated Orthodontic Evaluation
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Solution Overview
Problem
Current methods for evaluating dental situations, especially orthodontic conditions, are costly and require frequent visits to dental professionals, leading to low patient participation and insufficiently detailed or unsatisfactory evaluations by centralized computers.
Innovation Solution
A method using a mobile telephone to acquire images of dental arches, analyze them using a neural network, and compose personalized responses based on dental attributes, which are then transmitted to patients and professionals for evaluation and education on hygiene practices, improving patient participation and providing detailed feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If a centralized computer processes requests remotely using conventional methods, then dental evaluation can be performed without frequent professional visits, but the evaluation detail and usefulness is insufficient for dental professionals
Solution Approach 1:
The evaluation process is segmented into multiple components: automated image analysis for initial assessment, neural network-based detection of specific dental conditions, and structured composition of detailed reports covering different aspects (orthodontic devices, tooth position, hygiene). This segmentation enables both reduced visit frequency and comprehensive evaluation details.
Solution Approach 2:
A mobile application serves as an intermediary between the patient and the dental professional, capturing images and transmitting them to a centralized computer for analysis. The system then generates composed responses with detailed evaluations that are transmitted back through the mobile application, eliminating the need for frequent in-person visits while providing comprehensive information.
2Measurement precision
If conventional dental checkups are performed by professionals alone with appropriate equipment, then accurate dental evaluation is achieved, but the cost increases and visits become stressful for patients
Solution Approach 1:
The patient performs the image capture themselves using their mobile telephone, eliminating the need for professional equipment and in-person visits. The centralized computer then automatically analyzes the images and generates detailed evaluations, maintaining accuracy while significantly improving convenience and reducing stress for patients.
Solution Approach 2:
The mechanical system of in-person professional examinations is replaced with a digital system where patients capture images using mobile telephones and centralized computers perform automated analysis using neural networks and image processing algorithms, achieving both accuracy and convenience.
3Loss of time
If patients use mobile telephones to send updated images for evaluation, then the number of professional visits is reduced, but patient participation decreases after a few weeks
Solution Approach 1:
The system implements a feedback mechanism where composed responses are automatically transmitted back to patients through their mobile applications. These responses include detailed evaluations, detected conditions, and recommendations, providing patients with actionable information that encourages continued participation and regular image submission.
Solution Approach 2:
The system enables periodic automated evaluations at intervals determined by the treatment plan, with the composed responses providing regular feedback to patients. This periodic structure maintains patient engagement by creating a routine that does not require continuous professional intervention while ensuring consistent monitoring.
4Loss of information
If artificial intelligence algorithms are used to evaluate dental situations from updated images, then patient participation increases and detailed feedback is provided, but the complexity of the system increases
Solution Approach 1:
The centralized computer system performs multiple functions: receiving images from mobile applications, analyzing them using neural networks, detecting various dental conditions, composing detailed responses with recommendations, and transmitting results back to patients. This multi-functionality consolidates complexity into a single system while providing comprehensive evaluations.
Data Source
AI summary
Method for preparing a composed response from a value for at least one dental attribute relating to the dental situation of a patient. The method includes: (d) selection by a composition computer of at least one relevant standard response from a base or standard responses and as a function of the value of the at least one dental attribute; (e) composition of a composed response by the composition computer on the basis of the at least one relevant standard response; (f) optionally, validation and/or modification of the composed response by a controller; (g) presentation of the optionally validated and/or modified composed response. The selection in (d) and the composition in (e) are determined according to composition rules of a composition protocol. Before (e), the composition protocol is selected in a protocol models base and/or is created by selecting a protocol model in a protocol models base and then modifying.