Case Study - AI-Generated Dental Simulation
Problem
Our client, Tasty Tech, was an organically growing start-up with a first-generation product in the dental space, and their product-market fit was validated. However, the existing product required too much manual tuning on the user side. They wanted to develop a second-generation product with higher quality and more automated functionality. It was also necessary to meet specific touchpoints so manual editing remains possible.
Solution
Our client, Tasty Tech, was an organically growing start-up with a first-generation product in the dental space; hence, their product-market fit was validated. However, the existing product required too much manual tuning on the user side. They wanted to develop a second-generation product with higher quality and more automated functionality. It was also necessary to meet specific touchpoints so manual editing remains possible.
TechnoLynx has started working based on one of the state-of-the-art models in agreement with the customer, and at first, we only made cautious modifications to meet functional requirements for synthesis. After having satisfactory results relatively early on in the project, the scope has been expanded to cover the entire end-to-end image processing pipeline, including segmentation, classification, and structural deformation, not just synthesis alone. Once the initial functionality was implemented for all parts, we executed a series of experiments, some based on ideas of other state-of-the-art models, and some were genuinely new ideas previously not used in this context. This was the foundation of an iterative improvement model that we could use to manage the project, enabling us to deliver gradual improvements to parts of the pipeline on an on-demand basis. We used PyTorch for this project, and we still believe it is a good starting point, especially if a great deal of research is expected will be involved. However, it must be pointed out that using PyTorch during delivery probably posed more challenges than a reasonably optimised delivery with TensorFlow.
Result
A functionally complete end-to-end pipeline, a clear yet flexible roadmap, and a constant flux of improvement ideas based on novel research ideas have been delivered to this dental simulation project.
Additionally, to successfully deliver the required functionality and quality, TechnoLynx has assisted the client with its attempt to protect the novel IP created as part of this R&D project.
Dentrino On-Demand has recently graduated from beta and is released for dental practitioners to utilise. The AI-generated smile makeover simulation is now available on Dentrino’s official website.
