Bonnie Freitas, M.D. is the RadNet Director of Neuro Imaging for Southern California. Dr. Freitas is certified by the American Board of Radiology, and received fellowship training in neuroradiology imaging from UCLA School of Medicine and is CAQ certified in Neuroradiology.

Dr. Freitas obtained her undergraduate degree in Psychobiology from the UCLA and graduated Magna Cum Laude. She went on to medical school at the University of Southern California, where she graduated at the top of her class, as an inductee in the Alpha Omega Alpha honor medical society. She was awarded top graduate by the American Medical Womens Association.

She completed an internal medicine residency in the US Army Medical Corps. On completion of her medicine residency, she received the Neurology departmental award for best resident on the neurology service, a sign of her interest in the neurosciences. She was chosen to act as chief resident for an additional year and went on to serve as an ACLS instructor, and perioperative and consultative medicine director as well as director of the internal medicine clerkship for the national military medical school in Hawaii. During her time as an internist, Dr. Freitas became a fellow of the American College of Physicians recognizing her accomplishments in teaching.

After completing her military service, Dr. Freitas returned to complete a residency in diagnostic radiology at UCLA and served again as chief resident, voted outstanding radiology resident by the Santa Monica UCLA radiology staff. She continued at UCLA to complete her fellowship in neuroradiology at UCLA and went on to achieve the American Board of Radiology Certificate of Added Qualification (CAQ) in Neuroradiology.

With prior hospital experience on the head and neck tumor board, stereotactic radiosurgery planning and general tumor board, Dr. Freitas has had extensive experience with oncologic imaging. She has special expertise in all areas of Neuroradiology and head and neck imaging, and values collaboration with her clinical colleagues for the optimal care of the patient. She is currently working with artificial intelligence developers and RadNet to optimize patient imaging and comfort.