AUTOMATED CONSTRUCTION OF 3D STATISTICAL SHAPE MODELS
Image Analysis and Stereology, 2011 Automated segmentation of medical images is a difficult task because of the complexity of anatomic structures, inter-patient variability, and imperfect image acquisition.
Tomaž Vrtovec +4 more
doaj +5 more sources
Diffeomorphic Statistical Shape Models [PDF]
Procedings of the British Machine Vision Conference 2004, 2004 We describe a method of constructing parametric statistical models of shape variation which can generate continuous diffeomorphic (non-folding) deformation fields. Traditional statistical shape models are constructed by analysis of the positions of a set of landmark points.
Timothy F. Cootes +2 more
core +3 more sources
Reliability Estimation for Statistical Shape Models [PDF]
IEEE Transactions on Image Processing, 2008 One of the drawbacks of statistical shape models is their occasional failure to converge. Although visually this fact is usually easy to recognize, there is no automatic way to detect it. In this paper, we introduce a generic reliability measure for statistical shape models. It is based on a probabilistic framework and uses information extracted by the
Federico Sukno, Alejandro F. Frangi
openaire +3 more sources
Using Statistical Shape Models to Optimize TKA Implant Design
Applied Sciences, 2022 (1) TKA implants should well fit on each patient’s anatomy. Statistical Shape Models (SSM) statistically represent the anatomy of a given population.
Ingrid Dupraz +5 more
doaj +2 more sources
Virtual Assessment Of Internal Rotation In Reverse Shoulder Arthroplasty Based On Statistical Shape Models Of Scapular Size [PDF]
JSES InternationalBackground: The purpose of this study was to assess impingement-free internal rotation (IR) in a virtual reverse shoulder arthroplasty simulation using a Statistical Shape Model based on scapula size.
Brian C. Werner +5 more
doaj +4 more sources
Automatic Construction of Statistical Shape Models for Vertebrae [PDF]
, 2011 For segmenting complex structures like vertebrae, a priori knowledge by means of statistical shape models (SSMs) is often incorporated. One of the main challenges using SSMs is the solution of the correspondence problem. In this work we present a generic automated approach for solving the correspondence problem for vertebrae.
Meike Becker +3 more
core +4 more sources
Application of Statistical Shape Models to Standard Lumbar MRI for Stenosis Treatment Stratification: Severe Versus Normal Stenosis [PDF]
JOR SpineBackground Lumbar spinal stenosis is a prevalent and debilitating diagnosis, which in severe cases requires surgical treatment to relieve nerve root pressure. Often, treatment plans are based in part on subjective, qualitative, and limited MRI assessment.
Mary H. Foltz +4 more
doaj +2 more sources
Mesh2SSM: From Surface Meshes to Statistical Shape Models of Anatomy. [PDF]
Med Image Comput Comput Assist Interv, 2023 Statistical shape modeling is the computational process of discovering significant shape parameters from segmented anatomies captured by medical images (such as MRI and CT scans), which can fully describe subject-specific anatomy in the context of a ...
Iyer K, Elhabian S.
europepmc +3 more sources
ADASSM: Adversarial Data Augmentation in Statistical Shape Models From Images. [PDF]
Shape Med Imaging (2023), 2023 Statistical shape models (SSM) have been well-established as an excellent tool for identifying variations in the morphology of anatomy across the underlying population.
Karanam MST +3 more
europepmc +3 more sources
Statistical multi-level shape models for scalable modeling of multi-organ anatomies
Frontiers in Bioengineering and Biotechnology, 2023 Statistical shape modeling is an indispensable tool in the quantitative analysis of anatomies. Particle-based shape modeling (PSM) is a state-of-the-art approach that enables the learning of population-level shape representation from medical imaging data
Nawazish Khan +11 more
doaj +1 more source