AI

Philips highlights AI integrated diagnostic approach at ECR 2023

Fully interoperable smart imaging systems and informatics solutions connect teams in radiology, oncology, cardiology and pathology to enhance clinical confidence and advance precision in diagnosis and treatment

Royal Philips (NYSE: PHG, AEX: PHIA), a global leader in health technology, today announced its radiology portfolio of smart connected imaging systems and vendor-neutral integrated radiology workflow solutions featured at the European Congress of Radiology (ECR) international meeting (March 1-5, Vienna, Austria). Visitors to Philips @The Blue Level at ECR, the largest exposition space at the Congress, will experience how Philips’ AI-powered technology turns data into actionable insights to increase diagnostic confidence and improve clinical outcomes, enhancing patient and staff experience, driving operational efficiency, and helping lower the cost of care.

“At this year’s ECR, together with our customer partners, Philips will demonstrate how our latest AI-powered integrated smart diagnostic systems and informatics solutions can help reduce clinical complexity and drive operational efficiency to address workforce shortages and staff burnout, all while optimizing the right care pathway for patients,” said Bert van Meurs, Chief Business Leader of Image Guided Therapy and Precision Diagnosis at Philips. “With our AI-enabled technology, we can automate and accelerate routine tasks to generate patient-centric insights from large volumes of data to help improve productivity and enhance patient outcomes. Underpinning each of our innovations at ECR is Philips’ commitment to delivering sustainable, resilient diagnostic solutions that help hospitals receive ongoing value from their investments.”

Smart connected imaging systems powered by leading clinical and AI technology
Philips will showcase its latest innovations connecting radiology, cardiology, pathology and oncology across MR, CT, diagnostic X-ray and ultrasound, including MR SmartSpeed, the next-generation imaging technology that leverages Philips’ state-of-the-art speed engine and an award-winning Artificial Intelligence (AI) [1] reconstruction technology that boosts speed and image quality. In partnership with Leiden University Medical Center (Leiden, The Netherlands) Philips is innovating with AI to further speed up and improve MR examinations, with the aim to reduce scan times to less than five minutes and to reconstruct detailed MR images despite patient or internal organ movement. The approach is already showing promising results in leading hospitals worldwide.

“In systematic research studies, we have seen strong evidence of the ability of SmartSpeed to significantly accelerate acquisition times for knee and spine examinations without compromising image quality, with scan times that can be reduced up to 64% for certain sequences,” said Dr. Andra-Iza Iuga, Department of Radiology at the University Hospital of Cologne, Germany.  “Since musculoskeletal (MSK) exams make up a large part of all MR procedures, these acceleration benefits have the potential to result in significant operational cost reductions and we are currently successfully implementing the results of our research studies into our clinical routine.”

Integrated radiology workflow solutions driving operational efficiency
Optimizing clinical workflows can help eliminate waste and allow hospitals to use their resources more efficiently, which translates into improved patient flow and delivery of higher quality care to patients. At ECR, Philips will spotlight its advanced technology to simplify and connect workflows to help reduce variability and staff workload, drive operational efficiency, and enhance the patient experience.

For more information on Philips’ fully integrated radiology portfolio of imaging and informatics solutions being featured at ECR, visit the Philips ECR Press BackgrounderRead more about Philips’ partnerships with public and private customers, peers, and industry-leading global organizations to help reduce the environmental impact of radiology.

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