After losing family members to chronic conditions, including his father, Ilker Hacihaliloglu decided something needed to be done to ensure that preventable diseases are discovered early rather than too late. His innovation, developed at Rutgers, The State University of New Jersey, became the company PONS, which seeks to give families “the precious gift of time.”
Hacihaliloglu, PhD, MSc, conceived of PONS’ technology during his tenure as a faculty member in the Department of Biomedical Engineering at Rutgers. He is currently an associate professor in the Departments of Radiology and Medicine at the University of British Columbia. The software enhances ultrasound images using advanced, physics-guided processing, improving image quality and standardizing structural representation across devices. By enabling effective data scaling and extraction of quantitative features, it provides clinicians with richer, more reliable information to support earlier disease detection and more accurate diagnostic assessment.
“Our ultimate goal was, and is, to be able to identify diseases at an earlier stage, like chronic conditions,” said Hacihaliloglu. “We believe that nobody should lose their loved ones to preventable diseases. The sooner we catch a disease, the sooner we can begin treatment, and the better the chances are of a successful outcome.”
Hacihaliloglu believes that PONS’ technology addresses three areas within healthcare that prevent earlier detection of diseases. For him, the primary reason is that many patients are not monitored frequently enough, often once a year or longer, and most of the testing takes place either at a hospital or as part of their regular checkup. He says there are three ways for patients to be scanned in a more decentralized care setting.
“Many leading research hospitals now operate hospital-at-home programs and are actively working to integrate imaging into these decentralized care models,” said Hacihaliloglu. “We’re seeing mobile mammography units traveling through cities, handheld ultrasound devices that connect to smartphones or tablets, and portable X-ray machines designed for bedside or community use. The challenge, however, is that portability often comes at the expense of image quality. Smaller hardware platforms, limited processing capacity, and constrained acquisition environments can reduce resolution and signal clarity, making subtle findings harder to detect.”
Among these portable technologies, point-of-care ultrasound (POCUS) stands out as the only widely available, non-radiation–based imaging modality suitable for repeated bedside and community use. This makes it especially attractive for hospital-at-home programs and longitudinal monitoring. According to Hacihaliloglu, however, ultrasound image quality can vary significantly depending on the device, operator experience, and acquisition conditions. Historically, ultrasound has often been used as a secondary imaging tool to confirm a diagnosis rather than to detect early-stage disease. When image quality is suboptimal, subtle structural changes associated with early pathology may be missed, limiting its potential as a frontline diagnostic tool.
The challenge becomes even more complex when artificial intelligence is introduced into clinical workflows. Effective AI models require large-scale, diverse, and high-quality datasets—often involving data from thousands or even millions of patients across different regions and healthcare systems. In practice, assembling datasets of that magnitude is costly, time-consuming, and frequently infeasible, particularly in decentralized settings where device variability further complicates data consistency.
Hacihaliloglu believes PONS addresses these interconnected challenges by enhancing image quality, harmonizing data across devices, and enabling scalable data expansion. By improving structural clarity and standardizing imaging inputs, the technology strengthens diagnostic confidence, supports earlier disease detection, and enables more reliable AI-driven analysis across diverse care environments.
“PONS’ technology features a navigation system that we have developed so that the caregiver or nurse who has to collect data outside of a hospital setting can see where to move the probe, the transfuser, to a correct location to collect clinically acceptable data,” said Hacihaliloglu.
The technology also addresses the issue of quality within the field of medical imaging by “enhancing and improving image quality and providing advanced features in Ultrasound and point-of-care ultrasound,” according to their latest publication with the MAYO clinic where they validated the technology on 62,912 breast ultrasound scans collected from 688 patients. Their study showed that AI models trained on PONS’ enhanced data achieved a 64% improvement in diagnostic accuracy.
“For example, our technology can reveal small changes in a tumor that are very difficult to see on a standard ultrasound image. By making the structure and edges of a tumor clearer, it helps radiologists better understand its size and shape, which could lead to faster and more accurate diagnoses,” said Hacihaliloglu. “We believe this is crucial because the workload of radiologists right now, in general healthcare workers, is a large issue; they are overwhelmed, and the hospitals are crowded. Any solution that makes the workload more efficient is an advantage to both medical professionals and their patients.”
PONS’ technology not only enhances the image quality, but also the data, allowing for a scale-up of data sets by up to 50, which Hacihaliloglu believes will help develop generalizable AI solutions that are not biased toward race or data collection.
“PONS is filling a gap that is missing in the healthcare ecosystem, which is improving the quality of ultrasound data and scaling the size of the data,” said Hacihaliloglu. “What’s more, our technology is a software solution that works on any ultrasound machine, so it’s not tied to a specific vendor, and we have done other studies as well that show PONS’ technology enhances other imaging modalities such as X-Ray or Mammography.”
PONS was named after the region of the brain that connects the midbrain to the spinal cord—reflecting the company’s original focus on traumatic brain injury. In Latin, pons means “bridge,” a name that, Hacihaliloglu says, also captures the company’s broader mission to bring high-quality ultrasound imaging to communities and decentralized care settings. The company was founded by Hacihaliloglu and his twin brother, Soner, who serves as CEO. PONS is based in Newark and currently employs a team of eight.
“The technology developed by Dr. Hacihaliloglu has the potential to help make preventable diseases even more so,” said Deborah Perez Fernandez, PhD, MBA, executive director of the Technology Transfer unit within the Office for Research, which negotiated the license with PONS. “Our team has supported Dr. Hacihaliloglu through the patenting and licensing of his technology, and we are excited to see the positive impact it will make on the medical profession.”
“PONS is a fantastic company, based on technology that was developed here at Rutgers and has the potential to have a major impact on the world,” said Vince Smeraglia, JD, executive director of New Ventures, the team within the Office for Research that supports companies that arise from innovations developed at Rutgers. “We were proud to award Dr. Hacihaliloglu with a TechAdvance® grant in 2019, and we continue to work with Dr. Hacihaliloglu and his brother Soner to help the company grow and expand.”
“In the United States, there are a lot of regions which we call healthcare deserts, where the nearest hospital is two or three hours away,” said Hacihaliloglu. “Our technology is suitable for providing high-quality imaging to people in those areas, underserved minority groups and underrepresented groups. Because our technology is portable, it lends itself to a more decentralized care system, and we are very proud of that.”
PONS is currently advancing its technology through an NIH-funded SBIR Phase I study aimed at improving diagnostic accuracy for early-stage liver disease. The project is being conducted in close collaboration with clinicians and researchers at Rutgers Robert Wood Johnson University Hospital and the Rutgers Cancer Institute, with Professor David Foran serving as the lead Rutgers site Principal Investigator.
