Improved Methods for Navigated 3-D Vascular Ultrasound Imaging

Abstract

3-D reconstruction of flow based on 2-D ultrasound images and position sensor information can be used to portray clinical information not currently available in vascular imaging. However, due to Doppler angle-dependencies and the complexity of the vascular architecture, clinical valuable 3-D information of flow direction and velocity is currently not available. The quality of the 3-D images are often not sufficient for clinical use, due to artifacts from angle dependency and too low spatial resolution. The work presented in this thesis is devoted to the development of improved quantitative and qualitative 3-D blood flow imaging based on 2-D ultrasound imaging and a position sensor system. The thesis consists of three technical contributions. The different contributions are written in article form and can be read individually. A background chapter is also included to introduce the unfamiliar reader to concepts in ultrasound imaging.

In the first paper we aim to correct for angle-dependencies in 3-D flow images based on a geometric model of the neurovascular tree generated on-the-fly from freehand 2-D imaging and an accurate position sensor system. The 3-D vessel model acts as a priori information of vessel orientation used to angle-correct the Doppler measurements, as well as provide an estimate of the average flow direction. Based on the flow direction we were also able to do aliasing correction to approximately double the measurable velocity range.

In the second paper we aim to improve the quality of vascular 3-D images, by compounding 2-D color flow images with different steering angles. The 3-D vessel image is further generated based on navigated 3-D freehand scanning, where the position and orientation of the probe is registered by an optical sensor. This may result in higher quality 3-D flow images, without changing or complicating the clinical practice.

In the third paper we aim to generate on-the-fly 3-D images of the carotid artery from automatic segmented 2-D B-mode images based on a Kalman filter approach. During acquisition the position and orientation of each crossectional image of the carotid were registered by an accurate position sensor system, and further combined to reconstruct a 3-D image of the carotid artery lumen. The fast and relatively accurate reconstruction of 3-D carotid images may be suited for bedside 3-D visualization and volume estimation of moderate to large plaques.