UA Little Rock’s Basu completes first phase of cardiac visualization project
September 15-21, 2025
By Angelita Faller
A professor at the University of Arkansas at Little Rock has developed a new way for heart surgeons to visualize arteries in 3D using gaming technology. The project promises to give doctors a clearer, more interactive view of the heart before performing complex procedures.
Dr. Arya Basu, an assistant professor of computer science, has completed the first phase of the project, “Robust 2D to 3D Cardiac Arterial Mapping and Visualization for Surgical Preplanning.” He has successfully developed a pipeline that converts traditional 2D angiographic images into interactive 3D models of the heart’s arterial network.
Using computer modeling techniques often found in video games, Basu’s team turned 2D X-ray-like images of the heart’s arteries into detailed 3D models. The system lets doctors virtually “peek around corners,” offering perspectives that flat images can’t provide. The work promises to enhance surgical precision, reduce medical errors, and open the door for remote surgical collaboration and physician training.
“This project is deeply personal to me,” Basu said. “After losing a family member and watching my mother undergo open heart surgery due to complications from gestational diabetes, I felt compelled to help doctors gain clearer views of cardiac anatomy.”
During phase one, the research team generated 3D arterial tree models designed to simulate various types of arterial anatomy. They then applied the Marching Cubes algorithm to translate those data sets into interactive 3D surface reconstructions using Unity, a real-time 3D rendering engine. The result is a user-friendly platform that allows clinicians to dynamically explore coronary anatomy by viewing arterial paths from hard-to-see angles and assessing regions of interest that are often obscured in standard 2D angiographic imaging.
“We’re taking something inherently flat and turning it into something surgeons can manipulate, explore, and better understand,” Basu said. “This isn’t about replacing expertise. It’s about augmenting it.”
The research team includes Brandon “Alex” Norman, a graduate student in computer science who is using the project for his thesis, and Dr. Jan Springer, professor of computer science, and Dr. Ahmed AbuHalimeh, interim chair of the Department of Computer Science, who both provided technical consultation.
The second phase of research will focus on integrating real, de-identified patient angiograms and validating the efficacy of the 3D models through post-surgical data. This will allow researchers to measure how well their system can support clinical outcomes and provide real-world feedback to improve the tool. This phase will involve working with anonymized patient data under strict ethical and privacy protocols.
“This methodology holds the potential to reduce the need for invasive post-surgical assessments, such as repeat catheterization or other invasive imaging, by providing surgeons with a more accurate preoperative understanding of coronary anatomy and flow-limiting lesions,” Basu said. “Our goal is to build a platform that is highly customizable, scalable, and, most importantly, useful to surgeons and their teams. We’re not just visualizing the heart. We’re reimagining how we understand it.”
Long-term plans include partnerships with medical institutions to apply the system using real patient data, with full adherence to privacy standards. The technology also holds promise for training medical students and assisting with global telemedicine efforts, where specialists can collaboratively prepare for complex surgeries across continents.
“This is a dream come true in a way,” Basu said. “I’ve been thinking about this for years, and now we’re seeing it take shape. It’s not an easy task, especially when you’re working with human health, but we are pushing the limits of what’s possible.”
The team’s efforts are already online through a newly launched project website, which offers demos, technical insights, and a roadmap for future research phases. This project is funded through the National Science Foundation’s EPSCoR DART (Data Analytics that are Robust and Trusted) initiative and marks Basu’s first major grant-funded research effort at UA Little Rock.
Photo Caption:
Dr. Arya Basu (Photo provided)
