AI for GastroIntestinal

Artificial Intelligence is more and more used for detection, diagnosis and treatment of gastrointestinal diseases. Image analysis techniques are very helpful to power classical endoscopic tools and to helps classify all kind of items, including lesions, colorectal polyps, tumors, bleedings, occlusions and more. Today's most modern AI for GI software powers surgical robots developed to effectively intervene in the most dire gastroenterology procedures and cases.

AI in Diagnostic ERCP

Recent developments in the field of medical image analysis and artificial intelligence (AI) are used to improve the procedural outcomes of ERCP (Endoscopic retrograde cholangiopancreatography). Here is how RSIP Vision develops AI for diagnostic ERCP. Read what we do for enabling 3D Image Reconstruction and Image Registration/Fusion. Learn how strictures detection and classification can provide the physicians with classification scoring and, sometimes, help them avoid unnecessary biopsies during ERCP. Read more...

ERCP Gallstones and Strictures Treatment with AI

When performing ERCP for stone removal and stricture treatment, the gastroenterologist must overcome several challenges, namely navigation in the region of interest and the choice of the most fitting treatment that must be selected and implemented. AI enables to reconstructing a 3D image from multi-angle X-ray images or ultrasound slices. It is also trained to accurately classify the type of blockage that necessitated the ERCP procedure in the first place, resulting in quicker and more efficient ERCP procedures. Read more...

ERCP Tumor Assessment with AI

ERCP involves both endoscopy and fluoroscopy on a region with limited access. Accordingly, it poses several challenges for the gastroenterologist performing the procedure: imaging and artificial intelligence are key technologies to solve these challenges. They are used to reconstruct multiangle 2D X-ray images into a 3D image that will help the gastroenterologists in real-time navigation, reducing any complications involved in the navigation process. AI can be trained to accurately classify each tumor found by ERCP and check whether it is cancerous or not. Read more...

AI for Gastric Cancer Detection

Upper gastrointestinal cancers, including esophageal cancer and gastric cancer, are among the most common cancers worldwide. However, a lack of endoscopists with colonoscopy skills has been identified and solutions are critically needed. The development of a real-time robust detection system for colorectal neoplasms is needed to significantly reduce the risk of missed lesions during colonoscopy. Read More...

GI Lesion Detection with AI

Endoscopic examination is performed to disclose the lesion’s biophysical properties and assess its severity according to its physical appearance. Computer vision and machine learning put a large arsenal of techniques at our disposal. Clever utilization of these techniques enables to do just that, that is, translating expert knowledge into a fine-tuned algorithm, specifically designed for the task of GI lesion detection. The highest level of robustness, accuracy, and reproducibility is required, hence automatic methods can perform as a proper alert system for lesion detection. Read more...