Hip joint segmentation from 2D ultrasound data based on dynamic shape priors

Authors:
Rodrigo De Luis-García;Carlos Alberola-López
Affiliations:
University of Valladolid, Laboratorio de Procesado de Imagen, Spain;University of Valladolid, Laboratorio de Procesado de Imagen, Spain
Venue:
ICECS'05 Proceedings of the 4th WSEAS international conference on Electronics, control and signal processing
Year:
2005

Citing 11
Cited 0

Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations

Journal of Computational Physics
Multidimensional Orientation Estimation with Applications to Texture Analysis and Optical Flow

IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape Modeling with Front Propagation: A Level Set Approach

IEEE Transactions on Pattern Analysis and Machine Intelligence
Diffusion Snakes: Introducing Statistical Shape Knowledge into the Mumford-Shah Functional

International Journal of Computer Vision
Shape Priors for Level Set Representations

ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
Computer-Based Determination of the Newborn's Femoral Head Coverage Using Three-Dimensional Ultrasound Scans

MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
Nonlinear Matrix Diffusion for Optic Flow Estimation

Proceedings of the 24th DAGM Symposium on Pattern Recognition
Level Set Based Segmentation with Intensity and Curvature Priors

MMBIA '00 Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis
Level Set Based Shape Prior Segmentation

CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Tensor processing for texture and colour segmentation

SCIA'05 Proceedings of the 14th Scandinavian conference on Image Analysis
Active contours without edges

IEEE Transactions on Image Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we present an automatic algorithm for the segmentation of the hip joint from 2D ultrasound data. In a level set framework, the proposed method starts from a segmentation of the nonlinear structure tensor in the tensor domain. This feature includes both gray-level and texture information. Upon this, prior anatomical knowledge is employed for the design of a shape prior. Instead of manually delineating the shape prior or creating it from a training set, which was not available, we propose to dynamically construct the shape prior using the anatomical knowledge as well as the segmentation flow itself. Preliminary results on real images showed promising results.