Vector field convolution-based B-spline deformation model for 3D segmentation of cartilage in MRI

Abstract

In this paper, a novel 3D vector field convolution (VFC)-based B-spline deformation model is proposed for accurate and robust cartilage segmentation. Firstly, the anisotropic diffusion method is utilized for noise reduction, and the Sinc interpolation method is employed for resampling. Then, to extract the rough cartilage, features derived from the real symmetric Hessian matrix are chosen to enhance the cartilage, followed by binarizing the images via an optimal thresholding method. Finally, the proposed VFC-based B-spline deformation model is used to refine the rough segmentation. In the experiments, the proposed method was evaluated and demonstrated on 46 magnetic resonance images (MRI) (including 20 hip joints and 26 knee joints), and the results were compared with three state-of-the-art cartilage segmentation methods. Both qualitative and quantitative segmentation results indicate that the proposed method can be deployed for accurate and robust cartilage segmentation. Furthermore, from the segmentation results, patient-specific 3D models of the patient's anatomy can be derived, which then can be utilized in a wide range of clinical applications, such as 3D visualization for surgical planning and guidance.