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Segmentation of Carotid Arteries from 3D and 4D Ultrasound Images
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
2002 (English)Independent thesis Basic level (professional degree), 10 credits / 15 HE creditsStudent thesisAlternative title
Segmentering av halsartärer från 3D och 4D ultraljudsbilder (Swedish)
Abstract [en]

This thesis presents a 3D semi-automatic segmentation technique for extracting the lumen surface of the Carotid arteries including the bifurcation from 3D and 4D ultrasound examinations.

Ultrasound images are inherently noisy. Therefore, to aid the inspection of the acquired data an adaptive edge preserving filtering technique is used to reduce the general high noise level. The segmentation process starts with edge detection with a recursive and separable 3D Monga-Deriche-Canny operator. To reduce the computation time needed for the segmentation process, a seeded region growing technique is used to make an initial model of the artery. The final segmentation is based on the inflatable balloon model, which deforms the initial model to fit the ultrasound data. The balloon model is implemented with the finite element method.

The segmentation technique produces 3D models that are intended as pre-planning tools for surgeons. The results from a healthy person are satisfactory and the results from a patient with stenosis seem rather promising. A novel 4D model of wall motion of the Carotid vessels has also been obtained. From this model, 3D compliance measures can easily be obtained.

Place, publisher, year, edition, pages
Institutionen för systemteknik , 2002. , 164 p.
LiTH-ISY-Ex, 3279
Keyword [en]
Technology, Stroke, Carotid arteries, 3D Ultrasound, Adaptive Filtering, Segmentation, Edge Detection, Monga-Deriche-Canny, Seeded Region Growing, Inflatable Balloon Model, Finite Element Method, Triangulation, 4D wall motion, 3D compliance
Keyword [sv]
National Category
Engineering and Technology
URN: urn:nbn:se:liu:diva-1141OAI: diva2:17818
Subject / course
Computer Vision Laboratory
Available from: 2002-03-26 Created: 2002-03-26 Last updated: 2012-05-30Bibliographically approved

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