Edouard Naegelen (VP of Sales & Customer Success, SmartOne) and Hadrien Jacomino (Key Account Manager, SmartOne) gave this talk at the Computer Vision Summit in London in 2023.
SmartOne is a data labeling company and has been working for the biggest tech players around the globe for over ten years.
We’ll be talking about why data is the only thing you should have if you want to create, scale, and industrialize an AI solution. We're going to explore that with a concrete use case of one of our customers.
- SURGAR: Enhancing surgical precision with augmented reality
- The data dilemma
- Creating and preparing data sets for an AI model
- The best way to do data labeling at scale
- The three Ps of successful data annotations
- 4 key successes in the surgical AI project
- A quality assurance process is critical
- Data labeling is the bottleneck of any AI project
SURGAR: Enhancing surgical precision with augmented reality
Here’s what our customer, SURGAR, is doing and why data is very important to them:
Every year, more than 15 million surgeries are performed worldwide using laparoscopy. This minimally invasive surgical technique is used for abdominal procedures and offers various advantages for the patient.
However, it also presents serious challenges for the surgeons, such as the loss of eye and hand coordination, and the loss of tactile feedback. This explains why laparoscopy is only used for 30% of abdominal surgeries.
At SURGAR, we want to bring laparoscopic surgery to the next level, thanks to visualization software overlaying the real-time surgical video with 3D augmented reality images, showing the organs' internal structures.
Before surgery, using SURGAR plan software, a first phase of image segmentation is carried out using MRI or preoperative scanner images to create a 3D model of the organ and its inner structures.
During surgery, a digital twin of the organ is created. Algorithms using a deep neural network allow for automatic detection of the organ limits and the segmentation.
Developed with surgeons' ease of use in mind, SURGAR is simple to operate and doesn't require any additional viewing headset.
Our preclinical studies have proven that we increase surgical accuracy by a factor of 20 and decrease complications by twofold using SURGAR software.
No more classical mental mapping approach for the surgeon with the associated mental burden of rebuilding 2D info into a 3D format; SURGAR will create a new segment market of laparoscopy, assisted by augmented reality.
Through this example, let’s understand why clean data is the bottleneck of every AI project, and why building an AI model is almost all about data and also some volumes.