Jessica Scholey, PhD, MSc

Assistant Professor

LinkedIn: https://www.linkedin.com/in/jess-scholey-phd-508678a0/

Radiation Oncology Profile: https://radonc.ucsf.edu/about/our-team/jessica-e-scholey-phd/

Dr. Jess Scholey is an Assistant Professor, Physics Director of the MRI Simulation Program, and Physics Lead of the Proton Ocular Program in the Department of Radiation Oncology at the University of California, San Francisco. She received her BA in Physics from UC Berkeley and went on to receive her MSc and clinical residency training in medical physics from The University of Pennsylvania. Upon completion of her clinical training and ABR certification, she received her PhD from the Joint UC Berkeley-UCSF Bioengineering Program. She joined the faculty in 2017 and focuses on radiation oncology applications of MRI, proton therapy, and deep learning using medical imaging. Dr. Scholey leads the educational curriculum of MRI and proton therapy in the Department of Radiation Oncology and is an active member of the American Association of Physicists in Medicine, International Society for Magnetic Resonance in Medicine, Particle Therapy Co-Operative Group, and the UCSF Center for Intelligent Imaging.

Publications

Evaluating the Hounsfield unit assignment and dose differences between CT-based standard and deep learning-based synthetic CT images for MRI-only radiation therapy of the head and neck.

End-to-end validation of fiducial tracking accuracy in robotic radiosurgery using MRI-only simulation imaging.

Multimodal Imaging-based material mass density estimation for Proton therapy using supervised deep learning.

Validation of an MR-based multimodal method for molecular composition and proton stopping power ratio determination usingex vivoanimal tissues and tissue-mimicking phantoms.

Contrast-Enhanced Liver Magnetic Resonance Image Synthesis Using Gradient Regularized Multi-Modal Multi-Discrimination Sparse Attention Fusion GAN.

Quality Assurance for AI-Based Applications in Radiation Therapy.

Generation of synthetic megavoltage CT for MRI-only radiotherapy treatment planning using a 3D deep convolutional neural network.

Improved accuracy of relative electron density and proton stopping power ratio through CycleGAN machine learning.

Technical Note: A methodology for improved accuracy in stopping power estimation using MRI and CT.

Oral isotretinoin and topical retinoid use in a series of young patients with ocular melanoma.

Practice Considerations for Proton Beam Radiation Therapy of Uveal Melanoma During the Coronavirus Disease Pandemic: Particle Therapy Co-Operative Group Ocular Experience.

Initial Report of Pencil Beam Scanning Proton Therapy for Posthysterectomy Patients With Gynecologic Cancer.