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 | Feb 8, 2022 | Garcia Hernandez, Nimrod Missael, Gruev, Viktor
— Technology Description
Engineers in Prof. Viktor Gruev’s laboratory have developed a compact 27-band hyperspectral imaging system for high resolution, label-free, real-time imaging. This system can distinguish spectral signatures in image guided surgery (IGS) and other applications. The tech…
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 | 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 | 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…