Deep Learning Segmentation in Neuro-Oncologic Imaging
Monday, March 11
![Deep Learning Segmentation Neuro Oncologic Imaging, March 11, 3-4 pm 2024](/sites/intelligentimaging.ucsf.edu/files/2024-03/EVNT-Deep-Learning-Segmentation-Neuro-Oncologic-Imaging-WEB.jpg)
![Jeff Rudie](/sites/intelligentimaging.ucsf.edu/files/2024-02/Jeff-Rudie.jpg)
Jeff Rudie, MD, PhD, a Neuroradiologist at Scripps Health and Adjunct Assistant Professor at UCSD has completed a Medical Scientist Training Program at UCLA with a PhD in neuroscience in 2012. He went to the Hospital of the University in Pennsylvania for a research track radiology residency and informatics fellowship, followed by a two-year Neuroradiology fellowship at UCSF, completed in 2021. He is currently a neuroradiologist at Scripps Clinic Medical Group in San Diego as well as an Adjunct Assistant Professor of Radiology at University of California, San Diego. He is actively involved in research at UCSD, through radiology societies (RSNA and ASNR), and industry. His research is focused on developing and translating artificial intelligence into clinical practice in order to improve the accuracy and efficiency of neuroradiology. In particular, his research used deep-learning based segmentation methods for the longitudinal assessment in neuro-oncology, including diffuse gliomas and intracranial metastases. He is the lead organizer of the 2024 International Brain Tumor Segmentation Challenge (BraTS) on post-treatment gliomas.