Madhur Srivastava, an Assistant Research Professor in the Department, has been awarded the NSF Partnership for Innovation grant for the proposal titled “Enabling More Scans per Machine through Magnetic Resonance Imaging using Data Processing”. Srivastava’s research group, Signal Science Lab, focuses on developing data processing methods for early disease diagnosis.
Magnetic Resonance Imaging (MRI) is widely used as a clinical diagnostic tool. Over 30 million MRI scans are conducted each year in the United States. However, patients in need of MRI scans often face long wait-times as a result of imaging facility backlogs. The per-patient scan-time is a fundamental bottleneck that limits daily throughput and is one of the root causes of backlogs and long wait-times. Srivastava proposes the development of a signal-processing based software approach for reducing MRI scan-times. The technology is focused on the novel application of denoising raw MRI data in real-time prior to construction of the MRI image and can be integrated with existing instrumentation without requiring any hardware modifications.
The potential to reduce MRI scan-times and improve patient throughput will be beneficial for patients as well as healthcare providers. Shorter scan-times will improve patient comfort, especially for patients that are young, elderly, or claustrophobic. Improved throughput will increase accessibility, allow patients to receive MRI scans in a timely manner with less wait-time, and contribute to better healthcare outcomes. For healthcare providers and imaging facilities, shorter scans and better throughput will increase operational efficiency, revenue potential, as well as patient satisfaction.
Click here to read the full award announcement.
Follow this link to find out more about the research in the Srivastava Group (Signal Science Lab).
