University of Wisconsin–Madison

Year: 2024

MIMRTL at the 2024 ISMRM Conference

The MIMRTL team from the University of Wisconsin School of Medicine and Public Health Department of Radiology participated in the 2024 International Society for Magnetic Resonance in Medicine (ISMRM) conference, held in Singapore from May 4-9. The team presented a series of research projects that highlighted technical advancements in magnetic resonance imaging (MRI). Contributions included: …

New Paper Using Radiomics to Study Recurrence in Metastatic Brain Tumors

In the realm of oncological treatment, stereotactic radiosurgery (SRS) is key part of treatment for patients with brain metastases. However, after SRS treatment doctors sometimes see suspicious changes in the brain. These changes can either be from the treatment itself, called radiation necrosis (RN), or from cancer coming back (tumor recurrence). Knowing the difference is …

MIMRTL Undergraduate Team Members Participate in the 2024 Undergraduate Research Symposium

On April 25, 2024, Molecular Imaging Magnetic Resonance Technology Laboratory (MIMRTL) team members Tracy He, Ndinda Kasyoka, Aditi Sunil, and Kevin You presented their work at the Undergraduate Research Symposium held at Union South at the University of Wisconsin. This annual event showcases undergraduate creativity and research across a spectrum of disciplines, from the arts …

New Prototype Traveling Wave Electron Paramagnetic Resonance Imaging System

MIMRTL team members Eric Weber and Ted Nowak, both PhD students in the Department of Electrical and Computer Engineering department, have recently completed the construction of a prototype traveling wave electron paramagnetic resonance imaging (EPRI) system. The development of a traveling wave approach for RF transmission via a waveguide can enable higher-frequency imaging with more …

New Publication on Synthetic CT for Breast PET/MRI

In the recent publication in the journal Physics in Medicine and Biology, MIMRTL team members Xue Li and Alan McMillan reported a deep learning approach to perform attenuation correction (AC) in breast PET/MR imaging. This method aims to overcome significant challenges associated with traditional PET/MR imaging, such as anatomical truncation and the absence of bone …