12 citations · 34 across the 16 of their papers we have counts for
8 papers · 1 filter
Generalizations of Ripley's K-function with Application to Space Curves
Jon Sporring, Rasmus Waagepetersen, Stefan Sommer
The intensity function and Ripley's K-function have been used extensively in the literature to describe the first and second moment structure of spatial point sets. This has many a…
Stochastic Image Deformation in Frequency Domain and Parameter Estimation using Moment Evolutions
Line Kühnel, Alexis Arnaudon, Tom Fletcher +1
Modelling deformation of anatomical objects observed in medical images can help describe disease progression patterns and variations in anatomy across populations. We apply a stoch…
An Average of the Human Ear Canal: Recovering Acoustical Properties via Shape Analysis
Sune Darkner, Stefan Sommer, Andreas Schuhmacher +3
Humans are highly dependent on the ability to process audio in order to interact through conversation and navigate from sound. For this, the shape of the ear acts as a mechanical a…
Math in the Black Forest: Workshop on New Directions in Shape Analysis
Martin Bauer, Nicolas Charon, Philipp Harms +9
These are the proceedings of the workshop "Math in the Black Forest", which brought together researchers in shape analysis to discuss promising new directions. Shape analysis is an…
PADDIT: Probabilistic Augmentation of Data using Diffeomorphic Image Transformation
Mauricio Orbes Arteaga, Lauge Sørensen, M. Jorge Cardoso +6
For proper generalization performance of convolutional neural networks (CNNs) in medical image segmentation, the learnt features should be invariant under particular non-linear sha…
Latent Space Non-Linear Statistics
Line Kuhnel, Tom Fletcher, Sarang Joshi +1
Given data, deep generative models, such as variational autoencoders (VAE) and generative adversarial networks (GAN), train a lower dimensional latent representation of the data sp…