  To support minimally-invasive intraoperative mitral valve repair,
quantitative measurements from the valve can be obtained using an infra-red
tracked stylus. It is desirable to view such manually measured points together
with the endoscopic image for further assistance. Therefore, hand-eye
calibration is required that links both coordinate systems and is a
prerequisite to project the points onto the image plane. A complementary
approach to this is to use a vision-based endoscopic stereo-setup to detect and
triangulate points of interest, to obtain the 3D coordinates. In this paper, we
aim to compare both approaches on a rigid phantom and two patient-individual
silicone replica which resemble the intraoperative scenario. The preliminary
results indicate that 3D landmark estimation, either labeled manually or
through partly automated detection with a deep learning approach, provides more
accurate triangulated depth measurements when performed with a tailored
image-based method than with stylus measurements.
