LONDON, UK: The Royal Marsden NHS Foundation Trust, a world-leading specialist cancer center, has today announced a pioneering partnership with NTT DATA, a global leader in digital business and technology services, and CARPL.ai, a leading enterprise imaging artificial intelligence (AI) and machine learning operations (MLOps) platform. Together, they have designed and built an advanced AI-powered radiology analysis service for the development and evaluation of AI in medical imaging, designed to transform cancer research and, ultimately, improve patient outcomes.

AI’s potential to enhance the speed and accuracy of identifying imaging biomarkers has long been recognized. Funded by a three-year grant from the UK’s National Institute for Health and Care Research (NIHR), the service will be used for research at The Royal Marsden and the Institute of Cancer Research (ICR), including projects in collaboration with other research teams. This research initiative will focus on developing and evaluating AI algorithms to improve the accuracy of cancer evaluation, including sarcoma, lung, breast, brain, and prostate cancers. This will lead to faster response times, more accurate diagnoses, and better-targeted treatments.

The service runs on an MLOps clinical imaging platform, built and operated by NTT DATA. To enable this, NTT DATA developed a bespoke AI computing solution leveraging high-performance Dell servers and utilizing the latest GPU processing capacity orchestrated by the CARPL.ai platform, which helps test and manage AI algorithms and includes a large collection of radiology AI models.

NTT DATA is also providing specialist imaging AI consulting services, helping researchers at The Royal Marsden test and evaluate emerging AI tools in real clinical settings, while extracting maximum insight and value from both in-house and commercial algorithms.

“AI has immense potential to support clinicians in diagnosing and treating cancer earlier and more precisely,” said Professor Dow-Mu Koh, Professor in Functional Cancer Imaging and Consultant Radiologist in Functional Imaging at The Royal Marsden. “By working with NTT DATA and CARPL.ai, we’ve created a scalable research environment that allows us to explore the full potential of AI safely and in a way that could one day transform cancer diagnosis and treatment across the NHS.”

Minister of State for Health, Karin Smyth, said: “Our 10-Year Health Plan will modernize the NHS, replacing outdated systems with cutting-edge digital solutions. While this trial is in its early stages, it represents exactly the kind of collaboration between the NHS, industry, and academia that will help build a health service fit for the future. Early detection saves lives, and innovations like AI will transform how cancer is diagnosed and treated – helping patients receive faster and more effective care.”

Professor Mike Lewis, NIHR Scientific Director for Innovation, said: “Cancer is one of the biggest killers in the UK. That must change. This three-year grant will help researchers push the boundaries of AI-driven technology for cancer detection and diagnosis.

This AI-powered service represents the cutting edge of cancer research, and it is going to transform treatment, better support NHS staff, and ultimately change patients’ lives. It is another great example of how NIHR-funded and supported research will ensure the best care is there when patients need it.”

Tom Winstanley, Chief Technology Officer at NTT DATA UK & Ireland, commented: “This service is a great example of responsible innovation in practice, showing the ethical, secure use of AI in healthcare. We are very proud to support The Royal Marsden in pushing the boundaries of cancer research.”

Once the service is live, research teams at The Royal Marsden will be able to evaluate a range of AI models across several cancer types. These studies will generate critical insights into how AI can support clinical decision-making and shape future approaches to diagnosis and treatment. Through CARPL.ai’s centralized interface and built-in monitoring tools, the research teams will also be able to track model performance over time, enabling faster feedback loops between development and deployment – a crucial step towards clinical translation. NTT DATA will continue to work closely with The Royal Marsden to support this next phase of research, which will ultimately improve cancer care and patient outcomes.

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Augmented Reality (AR) is rapidly evolving from a niche technology to a mainstream tool that is reshaping how we interact with the world. What started with simple smartphone-based experiences has advanced to complex, immersive systems that blend digital and physical environments. With applications ranging from gaming to medical surgeries, AR is increasingly becoming a transformative technology across various industries. In this article, we will explore the latest advancements in AR technology, its architectural components, and how its applications are pushing the boundaries of what’s possible.

1. The Evolution of AR Technologies

AR is not a new concept, but recent advancements have unlocked new possibilities for interaction and immersion. The key drivers of this evolution can be broken down into several technological improvements:

a. Software and Algorithmic Advancements

Software innovations are just as critical to AR development. The integration of computer vision, machine learning, and AI is transforming AR from passive visualization to dynamic, interactive experiences.

• Simultaneous Localization and Mapping (SLAM): SLAM algorithms allow AR devices to map and understand the environment in real time while also tracking their position within that environment. This technology is essential for placing virtual objects in real-world contexts with high accuracy, even in dynamic or unstructured environments.
• Spatial Anchoring: The ability to persistently anchor digital objects within a physical space is a game-changer for AR. Technologies such as Apple’s ARKit’s “World Tracking” and Google’s ARCore’s “Cloud Anchors” enable persistent, multi-user AR experiences where digital objects can be seen and interacted with by multiple people in real time.
• Deep Learning and Computer Vision: AI-driven computer vision systems allow AR applications to recognize and understand objects, faces, and gestures. These capabilities can be used for applications ranging from virtual try-ons in fashion to facial recognition in security systems.

b. Cloud Integration and Edge Computing

The move to cloud and edge computing plays a crucial role in overcoming the limitations of local hardware processing. Cloud-based AR platforms can offload complex computations to high-performance servers, enabling more sophisticated AR experiences. Edge computing, on the other hand, allows data processing to occur closer to the source of data (the device itself), which reduces latency and enhances real-time interactivity.

2. Applications of Advanced AR

AR’s potential extends across a variety of sectors, with advanced technologies allowing for new levels of realism, interactivity, and utility. Some of the most significant applications include:

a. Healthcare and Surgery

AR is revolutionizing healthcare by providing real-time visual overlays during medical procedures. Surgeons can use AR to superimpose critical data, such as patient anatomy or imaging scans, directly onto the patient during surgery, improving precision and reducing the risk of errors. The use of AR also facilitates remote assistance, where specialists can guide on-site teams through complex procedures using live AR feeds.

• Enhanced Diagnostics: With the integration of machine learning, AR systems can help healthcare professionals visualize complex diagnostic data, such as MRI or CT scans, in 3D, aiding in better decision-making.
• Training and Education: AR is being used to create immersive medical simulations, providing medical students with the opportunity to practice surgical techniques or diagnose conditions in a controlled virtual environment.

b. Retail and E-Commerce

The retail industry has embraced AR for creating immersive shopping experiences, enhancing both in-store and online engagement. Virtual try-ons, where customers can see how clothes, accessories, or even makeup will look on them, are one of the most popular applications.

• Product Visualization: AR allows customers to visualize products in their own home environments before making a purchase. For instance, Ikea’s app allows customers to place virtual furniture in their living rooms to determine fit and style.
• In-store Navigation and Assistance: AR systems can provide in-store navigation, guiding customers to products and offering personalized promotions or product information when they point their device at items.

c. Automotive Industry

The automotive industry is leveraging AR to enhance both driver experience and vehicle design. From heads-up displays (HUDs) that project navigation instructions onto the windshield to AR-based maintenance guides, AR is improving safety and functionality in modern vehicles.

• Augmented Navigation: By overlaying real-time navigation data directly onto a driver’s view of the road, AR can reduce distraction and enhance situational awareness, especially when navigating complex environments or cities.
• Vehicle Design and Manufacturing: AR is aiding in the design and manufacturing process by enabling engineers to visualize complex components in 3D, ensuring more precise assembly and minimizing errors.

d. Military and Defence

The military sector has long been a key adopter of AR technology, utilizing it to improve training, situational awareness, and battlefield management. Soldiers equipped with AR glasses can access critical information in real-time, such as enemy location, terrain mapping, and tactical data.

• Combat Training: AR simulators provide immersive, realistic training scenarios for soldiers, helping them to rehearse missions and combat tactics in a virtual yet lifelike environment.
• Tactical Decision Support: In the battlefield, AR can project maps, mission-critical data, and other environmental details, enabling faster, better-informed decision-making during operations.

e. Entertainment and Gaming

While AR gaming has been around for a while, recent advancements are making these experiences more interactive and realistic. The success of games like Pokémon Go highlighted the immense potential of AR in entertainment, but the future promises even more immersive experiences.

• Mixed-Reality Gaming: The integration of physical and virtual spaces can create highly engaging experiences. With the combination of AR and VR (Virtual Reality), next-gen games may allow users to seamlessly transition between the real world and virtual worlds with minimal latency and complete immersion.
• Live Events and Experiences: Concerts, sports events, and theater performances are increasingly using AR to engage audiences. Virtual performers or interactive holograms are augmenting live experiences, providing novel ways to interact with the content.

3. Challenges and Future Directions

Despite its rapid growth, AR still faces several challenges, particularly in areas related to usability, privacy, and scalability.

a. User Experience

Ensuring an intuitive and comfortable user experience is one of the biggest hurdles for AR developers. Current AR devices often struggle with issues like small field-of-view, limited battery life, and difficulties in tracking fast-moving objects or people. Furthermore, the complexity of interacting with AR interfaces, especially in mobile environments, may overwhelm users.

b. Privacy and Security Concerns

With AR systems collecting vast amounts of data about the physical world, such as location, object recognition, and even personal habits, privacy and security concerns are significant. Developers will need to prioritize data protection to avoid potential breaches or misuse.

c. Content Creation and Standardization

As AR technologies continue to evolve, the creation of high-quality AR content requires specialized skills. Content developers need to integrate 3D modeling, spatial design, and AI, making it a resource-intensive process. Moreover, there is no universal standard for AR content, which creates interoperability issues between devices and platforms.

d. Scalability

For large-scale AR experiences, such as those in smart cities or industrial applications, challenges related to the real-time synchronization of massive datasets and devices come into play. Ensuring low-latency communication, cloud management, and efficient rendering will be essential as AR applications scale to support more users.

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