By: Jamal Hamama
To many radiologists, researchers, and the general public alike, the idea that artificial intelligence can support cancer detection still feels futuristic, but for Dr. Juhi Raj, Ph.D., it is already part of her daily work. Dr. Raj grew up in India, where she witnessed firsthand the critical need for fast and accurate cancer detection, especially in densely populated, high-throughput healthcare settings common in developing countries, and recognized how delayed diagnoses can potentially cost lives. After earning bachelor’s and master’s degrees in physics at Christ University, Bangalore, India, she pursued a doctorate at Jagiellonian University in Poland, and today Dr. Raj is a postdoctoral researcher at the University of Pennsylvania.
Her work focuses on using artificial intelligence to generate high-quality diagnostic images that are generally as quantitatively reliable as those produced by traditional PET reconstruction methods, while considerably reducing processing time.
“I vividly remember the first time I saw a PET scan image reconstructed using AI. The clarity and speed of it felt like a step towards the future of medical imaging,” says Dr. Raj. “For years, PET (Positron Emission Tomography) has been a leading method for detecting diseases such as cancer, neurological disorders, and cardiovascular conditions. However, traditional PET imaging pipelines face challenges like long scan times, noise, and high radiation exposure. Now, it’s encouraging to see how many studies are using AI to address these issues.”
Transforming Imaging Pipelines with AI
Dr. Juhi Raj’s AI-driven PET imaging frameworks can significantly reduce scan time while preserving diagnostic accuracy, making it highly valuable not only for advanced hospitals but also for under-resourced healthcare systems. In developing countries, where imaging equipment and trained specialists are scarce, such AI tools could substantially expand access by enabling faster, low-dose scans and automating interpretation. Raj’s work exemplifies how thoughtful integration of AI can help alleviate global imaging gaps and bring high-quality diagnostics to communities that need them most. Her efforts reflect a deep commitment to equitable healthcare and the belief that innovation should serve many, rather than just a few.
By collaborating with clinicians and industry partners, validating these tools in real-world settings, she ensures their reliability and clinical impact. These AI solutions might increase patient throughput, optimize use of radiotracers, and help reduce delays in diagnosis. As global health leaders aim to reduce preventable deaths through improved imaging access, frameworks like Raj’s offer a scalable path forward. Her work sits at the intersection of advanced technology and global health equity, improving how care is delivered across resource settings. “AI-driven imaging is more than speed,” Raj explains. “It provides clinicians the clarity and reliability they need to make confident patient decisions.”
Bridging Imaging Gaps with Scalable AI Solutions
Dr. Juhi Raj’s current research is grounded in a clear goal: reducing global disparities in access to medical imaging. She emphasizes that barriers to imaging aren’t just about equipment; they’re about trained personnel, infrastructure, and affordability. These gaps continue to significantly affect low-resource settings, where even basic diagnostic tools are unavailable. Motivated by these challenges, Raj focuses on developing AI models that enable low-dose, high-quality imaging for oncology and other clinical domains. Her frameworks are designed to reduce radiation exposure, especially in pediatric care and high-throughput environments, while also being lightweight and scalable across hospital networks with varying infrastructure strength.
By combining technical innovation with a deep awareness of healthcare inequities, Raj ensures her work not only advances technology but also expands access. “Introducing new technology into healthcare means understanding who depends on it, and building for them,” she says.
Educating, Advocating, and Expanding Impact
Outside the lab, Dr. Juhi Raj is a passionate advocate for the role of medical imaging in early detection and preventive health. She actively communicates the value of imaging in women’s health, cancer screening, and global health through writing, public speaking, and outreach. Her efforts aim to bridge the gap between research and public understanding, fostering greater awareness of medical imaging’s real-world impact.
In parallel, Raj shares her research at leading scientific conferences and serves as a peer reviewer for prominent imaging journals. She mentors young researchers and promotes collaboration across engineering, clinical, and computational disciplines, nurturing the next generation of innovators.
Raj also works closely with academic institutions and industry partners to facilitate the testing, validation, and integration of her tools into clinical practice. By combining research, mentorship, and translational collaboration, she ensures that her work contributes meaningfully to patient care and health equity.
Helping Shape the Future of Cancer Imaging
Dr. Juhi Raj is a researcher, advancing the use of AI in clinical imaging, with a focus on improving cancer diagnostics. Her expertise in algorithm development drives the creation of intelligent imaging tools that enhance both speed and accuracy, making them valuable in busy hospitals and under-resourced clinics alike.
“My goal is to ensure that advancements in AI extend beyond high-tech institutions to support hospitals and clinics that need it most,” she says. “That is the real measure of impactful science.”
By combining machine learning with translational research, Raj is helping scale PET imaging technologies for broader access. Her work sits at the intersection of innovation and equity, ensuring that high-quality diagnostics can become a global standard of care.
