4 citations · 6 across the 11 of their papers we have counts for
5 papers · 1 filter
Allocation strategies for high fidelity models in the multifidelity regime
Daniel J. Perry, Robert M. Kirby, Akil Narayan +1
We propose a novel approach to allocating resources for expensive simulations of high fidelity models when used in a multifidelity framework. Allocation decisions that distribute c…
On the Evaluation and Validation of Off-the-shelf Statistical Shape Modeling Tools: A Clinical Application
Anupama Goparaju, Ibolya Csecs, Alan Morris +4
Statistical shape modeling (SSM) has proven useful in many areas of biology and medicine as a new generation of morphometric approaches for the quantitative analysis of anatomical…
Deep Learning for End-to-End Atrial Fibrillation Recurrence Estimation
Riddhish Bhalodia, Anupama Goparaju, Tim Sodergren +6
Left atrium shape has been shown to be an independent predictor of recurrence after atrial fibrillation (AF) ablation. Shape-based representation is imperative to such an estimatio…
DeepSSM: A Deep Learning Framework for Statistical Shape Modeling from Raw Images
Riddhish Bhalodia, Shireen Y. Elhabian, Ladislav Kavan +1
Statistical shape modeling is an important tool to characterize variation in anatomical morphology. Typical shapes of interest are measured using 3D imaging and a subsequent pipeli…
Clustering With Pairwise Relationships: A Generative Approach
Yen-Yun Yu, Shireen Y. Elhabian, Ross T. Whitaker
Semi-supervised learning (SSL) has become important in current data analysis applications, where the amount of unlabeled data is growing exponentially and user input remains limite…