Image-based navigation is widely considered the next frontier of minimally invasive surgery.
It is believed that image-based navigation will increase the access to reproducible, safe, and …

Score-based generative models (SGMs) are a powerful class of generative models that
exhibit remarkable empirical performance. Score-based generative modelling (SGM) …

Accurate LiDAR-camera online calibration is critical for modern autonomous vehicles and
robot platforms. Dominant methods heavily rely on hand-crafted features, which are not …

Rotation-invariance is a desired property of machine-learning models for medical image
analysis and in particular for computational pathology applications. We propose a …

Sensorless freehand 3D ultrasound (US) reconstruction based on deep networks shows
promising advantages, such as large field of view, relatively high resolution, low cost, and …

Volumetric reconstruction of fetal brains from multiple stacks of MR slices, acquired in the
presence of almost unpredictable and often severe subject motion, is a challenging task that …

We introduce Geomstats, an open-source Python package for computations and statistics on
nonlinear manifolds such as hyperbolic spaces, spaces of symmetric positive definite …

Regressing rotations on SO (3) manifold using deep neural networks is an important yet
unsolved problem. The gap between the Euclidean network output space and the non …

Forensic odontologists use biological patterns to estimate chronological age for the judicial
system. The age of majority is a legally significant period with a limited set of reliable oral …

We present a convolutional neural network based on panoramic convolutions for saliency
prediction in 360o equirectangular panoramas. Our network architecture is designed …