Weakly supervised Bayesian shape modeling from unsegmented medical images
Anatomical shape analysis is pivotal in clinical research and hypothesis testing, where the
relationship between form and function is paramount. Correspondence-based statistical …
relationship between form and function is paramount. Correspondence-based statistical …
Weakly SSM: on the viability of weakly supervised segmentations for statistical shape modeling
Statistical Shape Models (SSMs) excel at identifying population level anatomical variations,
which is at the core of various clinical and biomedical applications, including morphology …
which is at the core of various clinical and biomedical applications, including morphology …
MASSM: An End-to-End Deep Learning Framework for Multi Anatomy Statistical Shape Modeling Directly From Images
Statistical shape modeling (SSM) effectively analyzes anatomical variations within
populations but is limited by the need for manual localization and segmentation, which relies …
populations but is limited by the need for manual localization and segmentation, which relies …
Probabilistic 3D Correspondence Prediction from Sparse Unsegmented Images
K Iyer, SY Elhabian - International Workshop on Machine Learning in …, 2024 - Springer
The study of physiology demonstrates that the form (shape) of anatomical structures dictates
their functions, and analyzing the form of anatomies plays a crucial role in clinical research …
their functions, and analyzing the form of anatomies plays a crucial role in clinical research …
Streamlining Statistical Shape Modeling: Safety, Feasibility, and Broader Applications
JR Adams - 2024 - search.proquest.com
Statistical shape modeling (SSM) is emerging as an important tool in medical image
analysis, allowing for population-based quantitative evaluation of morphometrics. SSM …
analysis, allowing for population-based quantitative evaluation of morphometrics. SSM …