by | Feb 21, 2022 | Curcuru, Austen, Gach, H. Michael, Kim, Taeho, Villa, Umberto
— Technology Description
Researchers at Washington University in St. Louis have developed a method to improve image quality during MR imaging guided radiation therapy (MR-IGRT) by correcting for B0 fluctuation in real-time. The corrections reduce electromagnetic interference (EMI) between the MRI sc…
by | Jan 21, 2022 | Wang, Qing, Wang, Yong
— Technology Description
Researchers at Washington University in St. Louis have developed MRI post-processing software capable of imaging cellular components. The software matches specific patterns with a dictionary of signals corresponding to cellular components. While the researchers have previous…
by | Apr 26, 2021 | Chapman Jr., William "Will Jr", Leng, Xiandong, Mutch, Matthew, Uddin, Shihab, Zhu, Quing
— Technology Description:
Researchers led by Quing Zhu at Washington University have developed a method for imaging rectal tumors using photoacoustic microscopy and ultrasound with a machine learning component. This method is better able to differentiate residual cancer from healthy tissue following…
by | Apr 26, 2021 | Hawasli, Ammar, Jayasekera, Dinal, Lamichhane, Bidhan, Leuthardt, Eric, Ray, Wilson
— Technology Description:
Researchers at Washington University, led by Eric Leuthardt, have developed software that can identify specific brain regions involved in chronic low back pain from neuroimaging data. This software, powered by machine learning, relies on differences in cortical thickness an…
by | Feb 9, 2021 | An, Hongyu, Eldeniz, Cihat
— Technology Description
Researchers in Prof. Hongyu An’s laboratory have developed a new image processing system for faster acquisition of motion-corrected MR or PET/MR images. This technology could be expanded to multiple sampling schema to correct both respiratory and cardiac motion.
Liv…