Recent advances in types and extant of medical imaging technologies has led to
proliferation of multimodal quantitative imaging data in cancer. Quantitative medical imaging …

Abstract Teeth from the Family Bovidae that are associated with our early humans ancestors
are important for reconstructing paleoenvironments. However, age, degree of attrition, and …

We study parameterisation-independent closed planar curve matching as a Bayesian
inverse problem. The motion of the curve is modelled via a curve on the diffeomorphism …

We propose a metric learning paradigm, Regression-based Elastic Metric Learning (REML),
which optimizes the elastic metric for geodesic regression on the manifold of discrete curves …

Elastic metrics can provide a powerful tool to study the heterogeneity arising from cellular
morphology. To assess their potential application (eg classifying cancer treated cells), we …

In this paper, we construct a novel finite dimensional shape manifold for shape analyses.
Elements of the shape manifold are a set of discrete, planar, and closed curves, which stand …

We propose a metric learning paradigm, Regression-based Elastic Metric Learning (REML),
which optimizes the elastic metric for geodesic regression on the manifold of discrete curves …

In nanotechnology, the size and shape control of nanoparticles is crucial as their properties
are highly dependent on their morphology. This obliges researchers to work on obtaining …

We examine how a specific instance of the elastic metric, the Square Root Velocity (SRV)
metric, can be used to study and compare cellular morphologies from the contours they form …