Machine Learning-Enabled Algorithm Helps Reduce Scan Time

QT Imaging Holdings Inc. has released a machine learning-enabled image interpolation algorithm designed to significantly reduce scan times by approximately 50%. This advancement is expected to enhance patient comfort by decreasing time spent on the scanner and improve operational efficiency by increasing the number of patients scanned within a given timeframe.

The advanced machine learning algorithm enables sophisticated image interpolation, allowing the system to skip every other scan level while accurately preserving high image quality. The technology reduces overall scan time by nearly half without sacrificing diagnostic accuracy, showcasing the ability of the innovation to streamline imaging processes, optimize diagnostic workflows, and deliver superior patient outcomes.

“Our commitment to advancing QTI’s technology and revolutionizing medical imaging is exemplified by this development,” QT Imaging Chief Science Officer Dr. Bilal Malik said. “By integrating machine learning into our imaging systems, we ensure its application is to create meaningful improvements in patient experience by reducing discomfort and scan times, while simultaneously streamlining workflows to enhance efficiency for healthcare providers “

The algorithm aligns with QTI’s strategy to improve health outcomes by making medical imaging safe, affordable, accessible, and centered on patient experience. The company has expanded its clinical and research and development efforts through collaborations with such institutions as the National Institutes of Health (NIH), Sunnybrook Health Sciences Centre, and the Stephenson Cancer Center at the University of Oklahoma.

QT Imaging Holdings Inc. is a public medical device company engaged in the research, development, and commercialization of body imaging systems using low frequency sound waves. QT Imaging Holdings strives to improve global health outcomes.