When most people think of IBM’s famed cognitive computing system Watson, they’ll likely recall the time that it competed on the game show Jeopardy and took first place over its two human competitors. But, Watson’s sweet spot is something far more practical than trivia questions — it’s healthcare.

IBM has been targeting healthcare with its cognitive computing system, Watson, for years. The system has been used to help with lung cancer treatment at Memorial Sloan-Kettering Cancer Center and has been used in the Cleveland Clinic. Then, in April, 2015, IBM launched a health unit specifically for Watson.

On August 6, 2015, IBM broadened its healthcare capabilities for Watson by announcing a planned $1 billion acquisition of medical imaging company Merge Healthcare. Previously, IBM acquired Phytel and Explorys for the health unit as well.

Merge Healthcare was founded in 1987 and was publicly traded as MRGE on the NASDAQ when it was acquired. The company’s platform is used in medical specialities such as radiology, cardiology, orthopedics, and others.

“By bringing Merge into Watson Health, medical professionals will have the opportunity to tap Watson for help analyzing X-rays, MRIs, angiograms, electro-cardiograms and other images to spot anomalies and provide evidence to support how they determine treatment decisions.” an IBM spokesperson said.

Dr. Orest Boyko, director of advanced imaging research at Huntington Medical Research Institutes, said that the combination of Merge’s extensive client network and body of images with Watson’s technological abilities “will allow for revolutionary innovations in patient centric clinical decisions.”

An IBM spokesperson said that the Watson system will apply image analytics to medical images taken by Merge.

Gartner research vice president Tom Austin said that IBM has been doing image processing and analysis through Watson for years and they recently added more capabilities through their acquisition of AlchemyAPI.

“This provides a foundation for DNN based (deep neural network) image analysis, feature detection, novel pattern identification and so on,” Austin said.

The added imaging tools and features that come with the Merge acquisition could be a boost in the future of Watson in the enterprise, as it would better enable other entities to build healthcare applications on top of the Watson platform, Austin said.

As has been highlighted by other writers, healthcare applications seem to be critical to the commercial success of IBM. Watson. However, an IBM spokesperson called healthcare a “moonshot,” even within the context of Watson Health.

But, it can sometimes be difficult to predict how a specific deal, such as this one, will really play out in practice.

Eric J. Topol, director of the Scripps Translational Science Institute, said that one of the ways that the Watson system could make use of,= and improve the medical imaging technology of Merge is by integrating medical scan findings with the remaining patient information. He calls this the “Google medical map,” and said it could help improve diagnostics by leveraging the artificial intelligence (AI) and contextual computing of Watson.

Furthermore, when the experience of radiologists is combined with Ai and deep learning, it could improve the accuracy of scan interpretations at the onset, Topol said.

It makes sense for IBM to target the healthcare market with Watson. Not only did the global healthcare market surpass $3 trillion back in 2012, it is a good fit for their existing technology to make and impact.

Dr. Kenneth Weiss, a professor at University of Miami Miller School of Medicine, said that the volume of imaging data is continually growing and it will continue to require more advanced analytics to make it truly useful.

Weiss also said that he foresees the growth of imaging to set the stage for the advancement of other medical technologies and a stronger commitment to the field by major tech companies such as Google.

“Most importantly,” Weiss said, “patient care will improve and cost savings will finally start to be realized.