High-resolution tomography is of great importance to many areas of biomedical imaging, but with it comes several apparent tradeoffs such as a narrowing depth-of-field and increasing optical aberrations. Overcoming these challenges has attracted many hardware and computational solutions. Hardware solutions, though, can become bulky or expensive and computational approaches can require high computing power or large processing times. This study demonstrates memory efficient implementations of interferometric synthetic aperture microscopy (ISAM) and computational adaptive optics (CAO) - two computational approaches for overcoming the depthof- field limitation and the effect of optical aberrations in optical coherence tomography (OCT). Traditionally requiring lengthy post processing, here we report implementations of ISAM and CAO on a single GPU for real-time in vivo imaging. Real-time, camera-limited ISAM processing enabled reliable acquisition of stable data for in vivo imaging, and CAO processing on the same GPU is shown to quickly correct static aberrations. These algorithmic advances hold the promise for high-resolution volumetric imaging in time-sensitive situations as well as enabling aberrationfree cellular-level volumetric tomography.