Second Order Kinematic Surface Fitting in Anatomical Structures

TL;DR

This paper introduces a second order kinematic surface fitting method that enhances symmetry detection and morphological classification of complex anatomical structures, such as the human cochlea, in medical imaging.

Contribution

It proposes a novel second order velocity field approach for better capturing curved and twisted anatomical shapes, improving symmetry detection accuracy.

Findings

Effective in detecting curved rotational symmetries

Improves morphological classification accuracy

Validated on synthetic and real anatomical data

Abstract

Symmetry detection and morphological classification of anatomical structures play pivotal roles in medical image analysis. The application of kinematic surface fitting, a method for characterizing shapes through parametric stationary velocity fields, has shown promising results in computer vision and computer-aided design. However, existing research has predominantly focused on first order rotational velocity fields, which may not adequately capture the intricate curved and twisted nature of anatomical structures. To address this limitation, we propose an innovative approach utilizing a second order velocity field for kinematic surface fitting. This advancement accommodates higher rotational shape complexity and improves the accuracy of symmetry detection in anatomical structures. We introduce a robust fitting technique and validate its performance through testing on synthetic shapes and real anatomical structures. Our method not only enables the detection of curved rotational symmetries (core lines) but also facilitates morphological classification by deriving intrinsic shape parameters related to curvature and torsion. We illustrate the usefulness of our technique by categorizing the shape of human cochleae in terms of the intrinsic velocity field parameters. The results showcase the potential of our method as a valuable tool for medical image analysis, contributing to the assessment of complex anatomical shapes.