High-Quality Intra-operative Ultrasound Reconstruction Based on Catheter Path

This paper presents a new method for improving image quality of intra-operative ultrasound for catheter intervention. A preliminary volume was constructed by extracting all colored pixels of 2D Doppler images. After center line was computed, cross sections of vessel were sampled and segmented by a modified region growing combining intensity distribution, curvature and area threshold. An ellipse was estimated based on the segmented contour. Finally, the estimated ellipses were interpolated onto the new center line which was registered to catheter path. The method was evaluated by a vessel phantom with bifurcations. The results show that the modified region growing can estimate an accurate contour and a high quality reconstruction can be obtained by interpolating estimated cross sections.

[1]  Terry M. Peters,et al.  Medical Image Computing and Computer-Assisted Intervention - MICCAI 2003 , 2003, Lecture Notes in Computer Science.

[2]  Klaus D. Tönnies,et al.  Segmentation of medical images using adaptive region growing , 2001, SPIE Medical Imaging.

[3]  Jean Meunier,et al.  Intravascular Ultrasound Image Segmentation: A Fast-Marching Method , 2003, MICCAI.

[4]  Geirmund Unsgaard,et al.  Brain Operations Guided by Real-time Two-dimensional Ultrasound: New Possibilities as a Result of Improved Image Quality , 2002, Neurosurgery.

[5]  Farzin Mokhtarian,et al.  A Theory of Multiscale, Curvature-Based Shape Representation for Planar Curves , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Jeanne Cullinan,et al.  Doppler artifacts and pitfalls. , 2006, Radiologic clinics of North America.

[7]  Miguel Á. Carreira-Perpiñán,et al.  Non-rigid point set registration: Coherent Point Drift , 2006, NIPS.

[8]  Isabelle Bloch,et al.  A review of 3D vessel lumen segmentation techniques: Models, features and extraction schemes , 2009, Medical Image Anal..

[9]  Pierre Hellier,et al.  Level Set Methods in an EM Framework for Shape Classification and Estimation , 2004, International Conference on Medical Image Computing and Computer-Assisted Intervention.

[10]  Thomas Lange,et al.  Augmenting Intraoperative 3D Ultrasound with Preoperative Models for Navigation in Liver Surgery , 2004, MICCAI.

[11]  F. Lindseth,et al.  SonoWand, an Ultrasound-based Neuronavigation System , 2000, Neurosurgery.

[12]  Ulf Müller-Ladner,et al.  Three-dimensional Doppler sonographic vascular imaging in regions with increased MR enhancement in inflamed wrists of patients with rheumatoid arthritis. , 2006, Joint, bone, spine : revue du rhumatisme.

[13]  Andrew W. Fitzgibbon,et al.  Direct Least Square Fitting of Ellipses , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[14]  Linda G. Shapiro,et al.  Shape Decomposition Approach for Ultrasound Color Doppler Image Segmentation , 2006, 18th International Conference on Pattern Recognition (ICPR'06).

[15]  L. Antiga,et al.  Computational geometry for patient-specific reconstruction and meshing of blood vessels from MR and CT angiography , 2003, IEEE Transactions on Medical Imaging.

[16]  Paul J. Besl,et al.  A Method for Registration of 3-D Shapes , 1992, IEEE Trans. Pattern Anal. Mach. Intell..