Depth Anything in Medical Images: A Comparative Study. (arXiv:2401.16600v1 [cs.CV])

Monocular depth estimation (MDE) is a critical component of many medical
tracking and mapping algorithms, particularly from endoscopic or laparoscopic
video. However, because ground truth depth maps cannot be acquired from real
patient data, supervised learning is not a viable approach to predict depth
maps for medical scenes. Although self-supervised learning for MDE has recently
gained attention, the outputs are difficult to evaluate reliably and each MDE's
generalizability to other patients and anatomies is limited. This work
evaluates the zero-shot …

acquired algorithms arxiv cs.cv data images mapping maps mde medical patient study supervised learning tracking truth video