Hypothesis: Machine learning-derived algorithms are capable of automated calculation of vestibular schwannoma tumor volumes without operator input.
Background: Volumetric measurements are most sensitive for detection of vestibular schwannoma growth and important for patient counseling and management decisions. Yet, manually measuring volume is logistically challenging and time-consuming.