Innovative, AI-supported diagnostics of the gastrointestinal tract
BioCam Sp. z o. o. and OVHcloud


More than 1.1 million medical images processed in the OVHcloud

Computational processing of experimental data accelerated from 55 to 5 days

Time required for the analysis of medical data significantly reduced thanks to AI
The background
BioCam Sp. z o. o. is a technological company developing endoscopic capsules enabling non-invasive diagnostics of the entire digestive tract. BioCam provides precise diagnostic tools that overcome the limits of traditional methods, while contributing to the well-being of patients. The examination can take place in the comfort of the patient’s home - the miniature endoscopic capsule swallowed by the patient sends images of the digestive system to a telemedicine platform in the OVHcloud cloud, where they can be analysed by specialists and proprietary artificial intelligence algorithms.
The challenge
Modern medicine struggles to cope with the ever-growing number of cases of gastrointestinal diseases, often diagnosed too late for an effective treatment to be implemented. Traditional diagnostic methods such as gastroscopy or colonoscopy require specialized equipment and trained personnel, and often are a source of stress and discomfort to the patients. As a result, many people miss regular screening tests, which leads to delayed disease detection, particularly in the cases of cancer.
BioCam faced the challenge of creating a solution which would not only increase the availability of diagnostics, but also make it more comfortable and available on a mass scale. The need to process huge amounts of image data quickly and accurately, requiring advanced technological infrastructure, was a key component. BioCam also needed a scalable infrastructure for training neural networks on large data sets, while implementing advanced AI algorithms at the same time. These processes required high computational power and flexibility of data management.
The solution
OVHcloud provides BioCam with a scalable cloud infrastructure. Advanced OVHcloud computing resources such as H100 GPUs, AI Training and AI Notebooks features enable multi-step training of AI models, including processing millions of images within one experiment. By integrating OVHcloud solutions, BioCam was also able to create a distributed computing cluster allowing many research experiments to be run in parallel and significantly reducing the time needed to develop and implement algorithms. The experimental results are of crucial importance for optimizing the diagnostic system.
The result
The cooperation with OVHcloud allowed BioCam to develop an advanced diagnostic system which redefines standards in medicine. The OVHcloud infrastructure not only provides access to advanced computing resources, but also guarantees compliance with European regulations, including GDPR, which is crucial for medical data security.
BioCam also appreciates the flexibility which OVHcloud offers by adapting its solutions to the changing needs of the company. OVHcloud specialists support the project at every stage, providing technological advice and proposing optimal solutions. This enabled BioCam to focus on developing innovative technologies with the certainty that its infrastructure needs were fully covered.
- 'One of the greatest achievements was the significant acceleration of computational processes - the experiment which would take 55 days locally was completed in no more than five days on the OVHcloud,' says Robert Hejda, Data Scientist at BioCam. - 'This allows us to perform research on multi-terabyte data sets consisting of millions of medical images.'
Thanks to the OVHcloud, we could do multiple parallel research projects at BioCam - locally, a limited number of graphics cards often allowed the company to carry out no more than two experiments at the same time, while on the OVHcloud at a certain point as many as 10 models were being trained at the same time.
Furthermore, BioCam was able to process no fewer than 1,151,600 endoscopic images efficiently and safely. By contrast, the data sets that could be processed locally consisted of only 50,000 images. Improvements in this area led to the best results in the set of publicly available capsule endoscopy data for the Kvasir-Capsule challenge.
The comprehensiveness of the OVHcloud infrastructure is also important, allowing BioCam to not only train AI models and processes images in the cloud, but also maintain other company applications, which reduces operating costs and improves the entire infrastructure.