The use of AI systems in healthcare for the early screening of diseases is of great clinical
importance. Deep learning has shown great promise in medical imaging, but the reliability …

Deep learning technologies have dramatically reshaped the field of medical image
registration over the past decade. The initial developments, such as regression-based and U …

Uncertainty estimation in medical image registration enables surgeons to evaluate the
operative risk based on the trustworthiness of the registered image data thus of paramount …

Objectives Due to taphonomic processes such as burial, fire, or animal activity, bones are
often found incomplete, which can pose problematic for establishing the biological profile of …

In recent years, 3D data has been widely used in archaeology and in the field of
conservation and restoration of cultural properties. Virtual restoration, which reconstructs the …

This paper introduces an innovative numerical scheme that may accurately quantify the
parameter and response distributions with minimal computational costs, with specific …

A precision spherical joint is a type of spherical motion pair that can realize three degrees of
rotation freedom. In this paper, a specific method is used to assess the uncertainty of our …

Statistical shape models (SSMs) are state-of-the-art medical image analysis tools for
extracting and explaining shape across a set of biological structures. A combined analysis of …

To date, the comparison of Statistical Shape Models (SSMs) is often solely performance-
based, carried out by means of simplistic metrics such as compactness, generalization, or …

Understanding morphological variation is an important task in many areas of computational
biology. Recent studies have focused on developing computational tools for the task of sub …