DeepAI AI Chat
Log In Sign Up

Diffeomorphic Medial Modeling

by   Paul A. Yushkevich, et al.

Deformable shape modeling approaches that describe objects in terms of their medial axis geometry (e.g., m-reps [Pizer et al., 2003]) yield rich geometrical features that can be useful for analyzing the shape of sheet-like biological structures, such as the myocardium. We present a novel shape analysis approach that combines the benefits of medial shape modeling and diffeomorphometry. Our algorithm is formulated as a problem of matching shapes using diffeomorphic flows under constraints that approximately preserve medial axis geometry during deformation. As the result, correspondence between the medial axes of similar shapes is maintained. The approach is evaluated in the context of modeling the shape of the left ventricular wall from 3D echocardiography images.


page 9

page 11


Modeling and Correspondence of Topologically Complex 3D Shapes

3D shape creation and modeling remains a challenging task especially for...

GenCorres: Consistent Shape Matching via Coupled Implicit-Explicit Shape Generative Models

This paper introduces GenCorres, a novel unsupervised joint shape matchi...

Volumetric Procedural Models for Shape Representation

This article describes a volumetric approach for procedural shape modeli...

SEG-MAT: 3D Shape Segmentation Using Medial Axis Transform

Segmenting arbitrary 3D objects into constituent parts that are structur...

Sparse Modeling of Intrinsic Correspondences

We present a novel sparse modeling approach to non-rigid shape matching ...

Statistical shape analysis of brain arterial networks (BAN)

Structures of brain arterial networks (BANs) - that are complex arrangem...

A Scalable Combinatorial Solver for Elastic Geometrically Consistent 3D Shape Matching

We present a scalable combinatorial algorithm for globally optimizing ov...