Advanced Medical Imaging
Our work in medical imaging involves leveraging the power of magnetic resonance imaging (MRI) and machine learning to enhance detection and assessment of disorders and diseases. To improve the diagnostic capabilities of MRI imaging, we are developing innovative pulse sequences and design tools aimed at enabling rapid image acquisition and identifying in vivo microstructural changes that are currently undetectable with standard clinical protocols. Our research is focused on applying these advancements to detect structural changes following traumatic brain injury and to monitor lesion formation in multiple sclerosis.
Additionally, the acquisition of medical images relies on specialized detection systems that are regularly tested to ensure quality. Partial failures in acquisition hardware can lead to a subtle degradation of image contrast—issues that may not be obvious during routine visual inspection. Current quality control protocols are too time-consuming to integrate into each scan. To address this, we are integrating machine learning to facilitate real-time quality control during the medical image process, ensuring optimal image quality with minimal disruption to workflow.
Our work in MRI imaging and machine learning will significantly help propel the detection of subtle structural changes and lesion development, advancing the diagnosis and monitoring of traumatic brain injury and multiple sclerosis.
Reconstructed PINS-UTE Dual Echo Images. Sagittal anatomical images acquired in-vivo with the PINS-UTE sequence using the modified PINS prepulse and CAIPI gradient. Echo 1 with TE1 = 0.23 ms is shown.
