Lawrence N. Tanenbaum MD FACR

The topic of artificial intelligence (AI) is prominent throughout the healthcare enterprise, particularly in diagnostic imaging services. At present, it appears AI is less a competitive force than a mechanism for elevation, augmentation, and expansion of the radiologist’s capabilities. Improved algorithms based on AI and machine learning (ML) will make computer-assisted diagnosis, detection and study triage (CADx, CADe, CADt) more intelligent and effective, improving lesion detection and classification. The enhanced pattern recognition in ML-based tools promises to assist in identifying cancers before they are evident to the radiologist. Natural language processing (NLP) is already being used to leverage information in a patient’s electronic medical record to facilitate billing appropriateness and a more patient-focused diagnostic process.

This explosion in AI and ML products is being fueled by the availability of enhanced computing and gaming processes that can handle huge amounts of data. Having curated, high-quality data and validation via ground truth remains critical. Data access is problematic, as concerns exist oversharing and patient privacy. AI companies are tackling these challenges by forming alliances with radiology partners around the globe. Curemetrix has partners in the US and Mexico working with their ML CAD mammography solution. Enlitic, perhaps the most established company in the imaging AI space, is already working with partners in Canada, Australia, and the U.S. to measure improvements in time-to-diagnosis and error reduction in emergency rooms, where speed and accuracy matter most.  AIDoc is already building market share (and revenue) with its CAD triage tool for intracranial hemorrhage and recruiting research partners for its whole body WIP applications, some of which are already CE marked.

Additional tools in or approaching the market are Arterys’ first application, Cardio AI, which assists in segmenting advanced 4D cardiac and vascular MR studies. Arterys’ latest approved Lung AI and Liver AI tools segment and register longitudinal oncological advanced imaging data sets. MaxQ-AI’s AccipioIx software is approved by the FDA to prioritize reading of studies in patients with a high likelihood of brain hemorrhage. Viz AI’s FDA-approved Contact software detects evidence of stroke on head CT and automatically notifies neurovascular team members to review the studies with a radiologist. Brainomix (collateral vascularity quantification) and Ischemaview (ASPECT scoring) have already been approved for use in stroke in Europe.  

Next entry will focus on AI applications in image reconstruction. Back soon.

This article is an excerpt of “Demystifying AI: An imaging tool ready to explode” written by the author for Applied Radiology. More guest posts can be read on

Author Bio

Dr. Lawrence N. Tanenbaum is the Chief Technology Officer, Director of Advanced Imaging, Vice President and Medical Director Eastern Region, RadNet Inc.