Congratulations to MIMRTL graduate students Sabeeka Khan (LinkedIn: https://www.linkedin.com/in/sabeeka-khan/) and Nikhil Nagam (LinkedIn: https://www.linkedin.com/in/nikhil-nigam-31131b12a/). Both recently graduated with Masters’ degrees in the Department of Electrical and Computer Engineering. We look forward to seeing the great things that you accomplish. Congrats to Sabeeka and Nikhil!
Congratulations to Weijie Chen on a successful preliminary examination! Weijie’s PhD thesis work in the MIMRTL group will develop efficient ensemble methods applied to medical imaging. His hypothesis is that such models will yield not only better performance for segmentation and synthesis applications, but also enable assessment of model uncertainty. The ability to assess a …
MIMRTL researchers and collaborators, led by S. Iman Zare Estakhraji, PhD recently published a paper that explored the use of unsupervised and supervised training methods to generate synthetic computed tomography (sCT) images from magnetic resonance (MR) images. The study employed a cycleGAN method with unpaired data sets for unsupervised training and several supervised models that …
MIMRTL Undergraduate Student Researchers Divya Durgavarjhula, Tracy He, Mahathi Karthikeyan, Kevin Yuan presented their research at the 2023 Undergraduate Symposium (https://ugradsymposium.wisc.edu/). Divya, Tracy, Mahathi, and Kevin participated in research using machine learning and artificial intelligence applied to medical imaging during the 2022-2023 academic year via the Undergraduate Research Scholars program (https://urs.ls.wisc.edu/). Congrats to our team …
Dr. McMillan, MIMRTL Principal Investigator, was recently selected as a Data Science Institute Affiliate. The Data Science Institute (DSI) at the University of Wisconsin collaborates with campus researchers to address data science challenges, such as integrating data from various sources and developing new research directions. This cooperation enhances the depth of research, allowing the exploration …
MIMRTL research was featured in a video produced with support from the National Library of Medicine. This video features Dr. McMillan as well as MIMRTL collaborators John Garrett, PhD and Richard Bruce, MD discussing our research efforts in support of improved robustness for artificial intelligence methods applied to medical imaging. Check out the video here: …
Please see this related story from the Department of Medical Physics regarding the upgraded 4.7T MR Scanner: Animal imaging gets a boost with updated 4.7T MRI