During medical procedures, doctors may miss important abnormalities or tissues specific to a patient, e.g. blood clots and inflamed tissues. These errors may be attributed to the lack of an effective approach to observe imaging data relative to the patient’s body during the procedure. Using machine learning and computer vision algorithms enables identifying different human anatomies from medical images. We can use an augmented reality visualization device, such as the Microsoft Hololens, to overlay an MRI scan on the body for doctors to have a direct relational view. This would facilitate the accurate identification of anatomical structures within the body. This technology can detect and highlight important organs or anatomical volumes within the body cavity, thus informing surgeons of the pseudoboundaries of important body structures during surgical procedures.