Unsupervised out-of-distribution detection for safer robotically guided retinal microsurgery

1 code implementation • 11 Apr 2023 • Alain Jungo, Lars Doorenbos, Tommaso Da Col, Maarten Beelen, Martin Zinkernagel, Pablo Márquez-Neila, Raphael Sznitman

Detecting so-called out-of-distribution (OoD) samples is crucial in safety-critical applications such as robotically guided retinal microsurgery, where distances between the instrument and the retina are derived from sequences of 1D images that are acquired by an instrument-integrated optical coherence tomography (iiOCT) probe.

Out-of-Distribution Detection