Congratulations to MIMRTL team members Sam, Weijie, and Matthew on their acceptance of their SNMMI Abstract Submissions! Chen W, McMillan AB. (2020). Single Subject Deep Learning-based Partial Volume Correction for PET using Simulated Data and Cycle Consistent Networks. Society of Nuclear Medicine and Molecular Imaging 2020 Meeting. New Orleans, Louisiana. (oral presentation) Hurley SA, McMillan …
Congratulations to MIMRTL Graduate Student, Bahar Behzadnezhad for successfully defending her PhD thesis entitled “Conformal and Flexible MRI Coils for Improved SNR.” After graduation, Dr. Behzadnezhad has obtained a position with Apple. Congrats Bahar!
Dr. McMillan participated in the Pre-Congress Symposium entitled “Advances in Image Processing Techniques” organized by the Physics + Dosimetry Committee of the European Association of Nuclear Medicine (EANM) annual meeting in Barcelona, Spain on October 12. Dr. McMillan gave a presentation entitled “Principles and Developments of Deep Learning techniques in NM Image Processing” which provided …
This position is currently filled. MIMRTL is looking for a Postdoctoral Researcher to join our team! Description: A postdoctoral researcher position is available in the Departments of Medical Physics and Radiology at the University of Wisconsin School of Medicine and Public Health. We are looking for candidates interested in molecular imaging (both MRI and PET) …
Dr. McMillan is one of the organizers and instructors of the GE Healthcare Magnetic Resonance Imaging Programming (MRI) Workshop. Going into its 6th year, this workshop is designed for beginners to learn how to use the pulse sequence and reconstruction tools available for researchers on the GE Healthcare MR platforms. Specifically, this workshop will provide hands-on …
Congrats to the team for success on Society of Nuclear Medicine and Molecular Imaging (SNMMI) abstract submissions. These abstracts will be preseted as poster or oral presentations at the 2019 SNMMI meeting in Anaheim, California. This includes Sam (2x) for his abstracts “Data-driven rigid motion correction of PET brain images using list mode reconstruction” and …
Team members Fang and Alan along with collaborators from the Department of Human Oncology recently published an article in the Journal of Applied Clinical Medical Physics entitled “MR‐based treatment planning in radiation therapy using a deep learning approach.” This work describes the development of a deep learning technique to synthesize CT images from MRI inputs, …
Team members from MIMRTL (Bahar, Jake, Sam, Bruce, Alan) recently published an article in the IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology entitled “Subject-specific, Non-invasive Helmet-restraint RF Coil for Awake, Non-human Primate MR Imaging.” This work describes the development of radiofrequency (RF) coils for magnetic resonance imaging (MRI) that are developed …
Congrats to the team for 100% success on ISMRM abstract submissions. This includes Bahar (2x) for her abstracts “Rapid Material Characterization For 3D-printed MRI Coils: A Deep Learning Approach” and “Traveling-Wave Excitation for Electron Paramagnetic Resonance Imaging”; Maribel for “Functional MRI-based Deep Learning Classification between Temporal Lobe Epilepsy Patients and Healthy Controls”; Wei-jie for “Low …
Dr. McMillan gave an educational presentation at the 2019 Society of Nuclear Medicine and Molecular Imaging (SNMMI) Mid-Winter Meeting in Palm Springs, California on January 19th 2019. The talk, entitled “What is Machine Learning? What is Deep Learning? Applications to Nuclear Medicine” provided an overview on deep learning, the specific problems it can help solve …