New medical image segmentation tool uses AI to reduce errors
A new AI-driven medical imaging tool has launched with the capacity to segment and measure areas of interest to help with surgical decisions and diagnosis.
RSIP Vision, a medical imaging company specialising in AI and computer vision solutions have created the tool to detect objects of interest and their boundaries quickly and automatically, with the aim of helping to make surgical and diagnostic measurements easier and more accurate.
The tool has been designed to minimise the amount of work required from the clinician, avoiding human factors like fatigue and misreads that can lead to mistakes.
The AI-based software uses a series of algorithms to detect and focus on a specific area, delivering an accurate 3D visualization and analysis of the patient's anatomy. The segmentation creates boundaries around the image for better viewing and performs automatic measurements. Physicians and researchers can receive consistent, repeatable measurements on the dimensions and characteristics of a specific area.
The software can be used for X-rays, CT scans, MRI scans, surgical robotics, and pathology; additionally it can be integrated in medical device software to be used by multiple applications, without the need to collect and train different machine learning models.
“Distinguishing and measuring organs, lesions, and other areas of interest in biopsy and pre-surgical planning can be tedious work, which is generally assigned to a specific employee or technician, or even a physician” Ron Soferman, Founder & CEO at RSIP Vision explained.
“Our new segmentation tool makes it easier to pinpoint specific points and boundaries in images, which in turn leads to greater accuracy during surgeries without being dependent on the capability and experience of a specific individual."
