AI Provides a Detailed Road Map for Interventional Lung Procedures

Precise medical imaging and analysis could enable early detection of lung cancer, help determine its exact size and location, and significantly improve diagnosis and treatment. This is usually done in a process called segmentation, which uses computers to identify the boundaries of the lung from surrounding thoracic tissue on CT images. From this process, a detailed 3-D map of the airways may be generated that can help to plan and navigate a bronchoscopy procedure to obtain biopsy samples and to perform other clinical interventions. “Until now, this process was very difficult because you need the radiologist, or even the surgeon, to spend much time to understand how to get to the specific place [where the lesion is located]. And this is sometimes prone to error,” said Ron Soferman, founder and CEO of RSIP Vision, in an interview with MD+DI. “It's very critical [to know the precise location] because, if you miss the lesion, you will take a biopsy from some random part of the lung and it will give a negative result.” RSIP Vision’s fully automated solution uses AI and deep learning technologies to provide a type of road map that can pinpoint the exact location of a suspicious lesion. The AI module uses sophisticated segmentation algorithms and computer vision to divide scanned images into clusters of pixels according to their chara...
Source: MDDI - Category: Medical Devices Authors: Tags: Imaging Source Type: news