4 papers
Estimation and Analysis of Slice Propagation Uncertainty in 3D Anatomy Segmentation
Rachaell Nihalaani, Tushar Kataria, Jadie Adams +1
Supervised methods for 3D anatomy segmentation demonstrate superior performance but are often limited by the availability of annotated data. This limitation has led to a growing in…
SCorP: Statistics-Informed Dense Correspondence Prediction Directly from Unsegmented Medical Images
Krithika Iyer, Jadie Adams, Shireen Y. Elhabian
Statistical shape modeling (SSM) is a powerful computational framework for quantifying and analyzing the geometric variability of anatomical structures, facilitating advancements i…
Point2SSM++: Self-Supervised Learning of Anatomical Shape Models from Point Clouds
Jadie Adams, Shireen Elhabian
Correspondence-based statistical shape modeling (SSM) stands as a powerful technology for morphometric analysis in clinical research. SSM facilitates population-level characterizat…
Weakly Supervised Bayesian Shape Modeling from Unsegmented Medical Images
Jadie Adams, Krithika Iyer, Shireen Elhabian
Anatomical shape analysis plays a pivotal role in clinical research and hypothesis testing, where the relationship between form and function is paramount. Correspondence-based stat…