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

MIMRTL team member Jinnian Zhang successfully defended his PhD thesis in the Department of Electrical and Computer Engineering entitled “Towards Efficient Deep Learning Models for Image Recognition.” Jinnian conducted state of the art research towards studying efficient and robust deep learning models applied to medical imaging. Thanks to the committee members for their advice and …

MIMRTL team members presented at the 2022 Conference on Machine Intelligence in Medical Imaging (CMIMI) from the Society for Imaging Informatics in Medicine (SIIM). Presentations included: (poster) – Torres-Velázquez M, Joshi T, McMillan A. (2022). Radiomics for Intractable vs not Intractable Epilepsy Classification using Magnetic Resonance Imaging Data. (oral presentation) – Zhang J, Joshi T, …

Congratulations to our MIMRTL team members and collaborators who presented their research at the 2022 Society for Nuclear Medicine and Molecular Imaging (SNMMI) in Vancouver, British Columbia from June 11th-14th. There are many great contributions using novel radiotracers and novel technical developments! Oral Presentations Staging Liver Fibrosis by Fibroblast Activation Protein Inhibitor Positron Emission Tomography …

MIMRTL team member Maribel Torres-Velázquez succesfully defended her PhD thesis in the Department of Biomedical Engineering entitled “Deep Learning and Radiomics Applied to Magnetic Resonance Images of the Brain and Muscles to Better Detect Disease.” In her thesis, Maribel conducted interesting and state of the art analyses using a combination of machine learning and deep …