Artificial intelligence (AI) company qure.ai is testing its application for chest X-Rays to detect tuberculosis (TB) with mobile TB screening programs in several developing countries. However, one issue the company encountered was the lack of PACS systems to run the software or the lack of internet connections in rural areas. This black box is a mini-server/computer the company provides to allow remote clinics a platform to run the AI and house the digital images.

Radiology artificial intelligence (AI) was again the hottest topic at the 2019 Radiological Society of North America (RSNA) annual meeting in December. AI was a primary theme in the larger booths in the north and south expo floors, as well as on the new third expo floor dedicated AI showcase. The separate AI show floor did not make many AI vendors happy. Many wanted the artificial intelligence showcase on the same level as the other expo halls to reduce the shuttling between the floors for meetings. RSNA organizers pointed out to one startup that due to the sheer number of AI exhibitors, they had to give the showcase its own space.

AI in medical imaging entered the consciousness of radiologists just a few years ago, notably peaking in 2016 when Geoffrey Hinton declared radiologists' time was up, swiftly followed by the first AI startups booking exhibiting booths at RSNA. Three years on, the sheer number and scale of AI-focussed offerings has gathered significant pace, so much so that this year a decision was made by the RSNA organising committee to move the ever-growing AI showcase to a new space located in the lower level of the North Hall. In some ways it made sense to offer a larger, dedicated show hall to this expanding field, and in others, not so much. With so many startups, wiggle room for booths was always going to be an issue, however integration of AI into the workflow was supposed to be a key theme this year, made distinctly futile by this purposeful and needless segregation. By moving the location, the show hall for AI startups was made more difficult to find, with many vendors verbalising how their natural booth footfall was not as substantial as last year when AI was upstairs next to the big-boy OEM players. One witty critic quipped that the only way to find it was to'follow the smell of burning VC money, down to the basement'.

Learning to perform and interpret radiographs is "hard". Learning to perform and interpret barium studies is "hard". Learning to perform and interpret sonograms is "hard". Learning to perform and interpret pneumoencephalograms was "hard". Learning to perform and interpret angiograms is "hard".

The Radiological Society of North America (RSNA) is an international society of radiologists, medical physicists, and other medical professionals. The annual RSNA meeting with approximately 50,000 attendees in Chicago is a place for scientific exchange and clinical training. This year radiologists are invited to experience the hands-on cutting-edge technology of artificial intelligence, 3D printing, and virtual reality. The Fraunhofer MEVIS team will be pleased to welcome you at their booth, located at the "AI Showcase". Our experts are looking forward to providing you with a range of latest developments in deep learning and artificial intelligence, e.g., our free software MEVIS draw.

Fujifilm Medical Systems U.S.A. is showcasing REiLI, the company's global medical imaging and informatics artificial intelligence (AI) technology initiative at the 2019 Radiological Society of North America's (RSNA) annual meeting. "At RSNA 2019, we look forward to sharing the AI insights and advances we've made by working closely with clinical and research partners for several years," said Takuya Shimomura, chief technology officer and executive director, Fujifilm. "Ultimately, the long-term goal of our AI initiative is to help providers make better decisions that improve patient lives." Under the REiLI brand, Fujifilm is developing AI technologies that strongly support diagnostic imaging workflow, leveraging the combination of its deep learning innovations and distinct image processing heritage. Applications currently in development include, but are not limited to: Region Recognition, an AI technology that helps to accurately recognize and consistently extract organ regions, regardless of deviations in shape, presence or absence of disease, and imaging conditions; Computer Aided Detection, an AI technology to reduce the time of image interpretation and support radiologists' clinical decision making; Workflow Support, using AI technology to realize optimal study prioritization, alert communications of AI findings, and report population automation.

November 30, 2019 -- Fujifilm Medical Systems U.S.A. is showcasing REiLI, the company's global medical imaging and informatics artificial …

Embedded systems: This segment hasn't received as much attention, but it could eventually become the area where AI has the biggest impact, covering the incorporation of AI into modality scanners to perform tasks such as reconstruction of image data. In MRI, for example, AI could be used to analyze data more effectively and shorten scan times or enhance image quality -- or both. In CT, embedded AI could lead to major advances in dose reduction. But Harris sees ultrasound as the modality where embedded AI could make the biggest difference. Ultrasound is prone to operator variability and has a steep learning curve.

PACS/RIS developer PaxeraHealth will highlight its updated PaxeraUltima360 artificial intelligence (AI)-based enterprise imaging software at RSNA 2019 in Chicago. PaxeraUltima360 is designed to use machine-learning technologies to decrease clinician workload by performing basic tasks and improving access to and coordination of patient data and care, the company said. The platform features an AI chatbot called Erabot that facilitates user interaction with the platform, thus speeding up access to relevant patient information. In addition, PaxeraUltima360 can adjust to the preferences of users by monitoring their behavior patterns for certain tasks and providing clinical decision support backed by augmented reading aids, PaxeraHealth said.

The vast number of CT presentations at RSNA 2019 is a testament to the modality's resilience and its value to the medical imaging community. Of the numerous factors that have contributed to CT's long-standing relevance, its adaptability certainly ranks high among them. This year's RSNA meeting looks to serve as a reminder of just how adaptable CT continues to be: Presentations will reaffirm the utility of tried-and-true imaging techniques and also feature relatively new technologies that have already begun reshaping the approach radiologists take to common clinical applications. Perhaps one of the best examples of this theme lies in the diagnostic evaluation of heart disease. Researchers will discuss the benefits of traditional coronary CT angiography (CCTA), one of the most reliable noninvasive methods for examining patients suspected of having coronary artery disease.