309 citations · 477 across the 8 of their papers we have counts for
20 papers
Leveraging Unsupervised Image Registration for Discovery of Landmark Shape Descriptor
Riddhish Bhalodia, Shireen Elhabian, Ladislav Kavan +1
In current biological and medical research, statistical shape modeling (SSM) provides an essential framework for the characterization of anatomy/morphology. Such analysis is often…
Controlled Doping of Double Walled Carbon Nanotubes and Conducting Polymers in a Composite: An in situ Raman Spectroelectrochemical Study
Martin Kalbáč, Ladislav Kavan, Lothar Dunsch
The interaction of double wall carbon nanotubes (DWCNTs) and the conducting polymer poly(3,4-ethylenedioxythiphene/polystyrenesulfonate (PEDOT/PSS) was studied by in-situ Raman spe…
Capturing Detailed Deformations of Moving Human Bodies
He Chen, Hyojoon Park, Kutay Macit +1
We present a new method to capture detailed human motion, sampling more than 1000 unique points on the body. Our method outputs highly accurate 4D (spatio-temporal) point coordinat…
Differentiable Implicit Soft-Body Physics
Junior Rojas, Eftychios Sifakis, Ladislav Kavan
We present a differentiable soft-body physics simulator that can be composed with neural networks as a differentiable layer. In contrast to other differentiable physics approaches…
Unsupervised Shape Normality Metric for Severity Quantification
Wenzheng Tao, Riddhish Bhalodia, Erin Anstadt +3
This work describes an unsupervised method to objectively quantify the abnormality of general anatomical shapes. The severity of an anatomical deformity often serves as a determina…
Self-Supervised Discovery of Anatomical Shape Landmarks
Riddhish Bhalodia, Ladislav Kavan, Ross Whitaker
Statistical shape analysis is a very useful tool in a wide range of medical and biological applications. However, it typically relies on the ability to produce a relatively small n…