How does CT fit into your overall regional expansion strategy, especially in emerging markets like India and Southeast Asia?
CT is a cornerstone of modern diagnostics. In emerging markets, it is often the modality that can scale fastest across urgent care, oncology, and cardiovascular pathways. Healthcare systems are under significant pressure to treat more patients with fewer staff, so our expansion focus is on technologies that streamline clinical decision-making and enable faster treatment decisions, helping improve efficiency and, ultimately, patient outcomes. In India and Southeast Asia specifically, expansion is tightly linked to enabling access: augmenting healthcare infrastructure with solutions that are easier to deploy and operate while maintaining strong clinical performance. In India, this also connects to our long-term footprint and local capabilities, including R&D and engineering scale as well as local manufacturing, in line with the ‘Make in India’ initiative. This helps us be closer to customers and their needs. And of course, innovation remains a growth engine: with photon-counting CT we are expanding clinical possibilities, while also working to make advanced technology accessible to more institutions over time.
How do you plan to expand in the price-sensitive Asia Pacific market with a cost optimisation approach?
First, it’s important to think about healthcare spending as an investment rather than a cost, because better diagnostics can prevent downstream testing, delays, and unnecessary procedures. From a practical perspective, our approach is to help providers optimise total cost of ownership through efficiency: reducing exam complexity, improving throughput, and supporting consistent quality even when teams are stretched. That’s why we place so much emphasis on workflow efficiency and automation, because when you can treat more patients with fewer staff, you improve both access and sustainability of care delivery. While configurations and local requirements matter, portfolio breadth lets us offer more choices depending on clinical utilisation and investment level.
What are the biggest barriers to CT adoption in Asia-Pacific?
Across Asia-Pacific, barriers are typically a combination of capacity constraints and operational realities. As demand and patient volumes rise, systems with limited access to trained professionals need technology that also delivers ease of use and workflow efficiency. Also, there is variability in infrastructure and resources between metropolitan centres and regional settings, so the question is often how to enhance imaging infrastructure sustainably rather than simply adding equipment. And third, providers are under increasing cost pressure in day-to-day operations, like energy, consumables, and utilisation, which is why operational efficiency and lifecycle thinking matter so much in deployment decisions.
How are AI-enabled CT workflows improving productivity and reducing dependency on skilled manpower?
The key point is: AI is not designed to replace clinicians; it is there to support them so they can focus on what matters most, the patient. And in regions with workforce gaps, that support can be decisive. In practice, AI helps make scanning and reading more efficient by improving scanning performance and speeding up image analysis, it can also support radiographers with patient positioning and protocol suggestions, which reduces variability and saves time on routine steps. That means more patients can be scanned, and clinical decisions can be made faster, which is crucial when capacity is limited. I often summarise this as: The key is combining the strengths of humans and AI. When you combine clinical expertise with smarter assistance, you reduce repetitive workload while improving consistency and confidence.
What according to you will be the top three growth drivers for CT in Asia-Pacific over the next 5–10 years?
First: the clinical and demographic demand. Chronic diseases and complex cases are rising, and CT remains a fast, scalable tool to answer urgent clinical questions. You can’t treat what you can’t see! Second: productivity pressure and system efficiency. Healthcare systems are under significant pressure to treat more patients with fewer staff, so technologies that streamline workflows and accelerate decision-making will see accelerating adoption. Third: technology step-changes, especially photon-counting CT and AI. Photon-counting CT has delivered a tremendous leap in image quality, dose reduction and scan times. And AI is increasingly indispensable in turning that imaging power into actionable, efficient workflows.
How are you addressing energy efficiency and sustainability in CT systems for large-scale deployments in Asia Pacific?
We treat sustainability as a healthcare priority, because global health is achievable only with a healthy planet. On CT specifically, we focus on reducing the footprint across operations and lifecycle. Newer system designs can reduce overall energy consumption compared to predecessor systems, up to 73 percent depending on the system, which becomes highly relevant in large-scale deployments where utilisation is high. And sustainability isn’t only about energy in use: it is also about responsible lifecycle management, including maintaining systems efficiently over time and using resource-preservation approaches across the product lifecycle.
Sanjiv Das
