IBM has announced that Watson will gain the ability to “see” by bringing together Watson’s advanced image analytics and cognitive capabilities with data and images obtained from Merge Healthcare Incorporated’s medical imaging management platform.  

IBM plans to acquire Merge, a leading provider of medical image handling and processing, interoperability and clinical systems designed to advance healthcare quality and efficiency, in an effort to unlock the value of medical images to help physicians make better patient care decisions

Merge’s technology platforms are used at more than 7,500 U.S. healthcare sites, as well as most of the world’s leading clinical research institutes and pharmaceutical firms to manage a growing body of medical images.  The vision is that these organizations could use the Watson Health Cloud to surface new insights from a consolidated, patient-centric view of current and historical images, electronic health records, data from wearable devices and other related medical data, in a HIPAA-enabled environment.

Under terms of the transaction, Merge shareholders would receive $7.13 per share in cash, for a total transaction value of $US1 billion.  The closing of the transaction is subject to regulatory review, Merge shareholder approval, and other customary closing conditions, and is anticipated to occur later this year.  It is IBM’s third major health-related acquisition – and the largest – since launching its Watson Health unit in April, following Phytel (population health) and Explorys (cloud based healthcare intelligence).

“As a proven leader in delivering healthcare solutions for over 20 years, Merge is a tremendous addition to the Watson Health platform.  Healthcare will be one of IBM’s biggest growth areas over the next 10 years, which is why  we are making a major investment to drive industry transformation and to facilitate a higher quality of care,” said John Kelly, senior vice president, IBM Research and Solutions Portfolio.

Medical images are by far the largest and fastest-growing data source in the healthcare industry and perhaps the world – IBM researchers estimate that they account for at least 90% of all medical data today – but they also present challenges that need to be addressed:

The volume of medical images can be overwhelming to even the most sophisticated specialists – radiologists in some hospital emergency rooms are presented with as many as 100,000 images a day.

Tools to help clinicians extract insights from medical images remain very limited, requiring most analysis to be done manually.

At a time when the most powerful insights come at the intersection of diverse data sets (medical records, lab tests, genomics, etc.), medical images remain largely disconnected from mainstream health information.   

IBM plans to leverage the Watson Health Cloud to analyse and cross-reference medical images against a deep trove of lab results, electronic health records, genomic tests, clinical studies and other health-related data sources, already representing 315 billion data points and 90 million unique records.  Merge’s clients could compare new medical images with a patient’s image history as well as populations of similar patients to detect changes and anomalies. Insights generated by Watson could then help healthcare providers in fields including radiology, cardiology, orthopaedics and ophthalmology to pursue more personalized approaches to diagnosis, treatment and monitoring of patients.

Cutting-edge image analytics projects underway in IBM Research’s global labs suggest additional areas where progress can be made.  They include teaching Watson to filter clinical and diagnostic imaging information to help clinicians identify anomalies and form recommendations, which could help reduce physician viewing loads and increase physician effectiveness.

“As Watson evolves, we are tackling more complex and meaningful problems by constantly evaluating bigger and more challenging data sets,” Kelly said. “Medical images are some of the most complicated data sets imaginable, and there is perhaps no more important area in which researchers can apply machine learning and cognitive computing.  That’s the real promise of cognitive computing and its artificial intelligence components – helping to make us healthier and to improve the quality of our lives.”