A Semi-Automated Technique for Internal Jugular Vein Segmentation in Ultrasound Images Using Active Contours

TL;DR

This paper introduces a semi-automated segmentation method combining region growing and active contours to accurately and efficiently segment the internal jugular vein in ultrasound videos, aiding blood volume assessment.

Contribution

The paper presents a novel semi-automatic segmentation algorithm that improves speed and accuracy over existing methods for ultrasound IJV imaging.

Findings

Performs well compared to manual segmentation

Outperforms existing speckle tracking algorithms

Effective across various image qualities and shapes

Abstract

The assessment of the blood volume is crucial for the management of many acute and chronic diseases. Recent studies have shown that circulating blood volume correlates with the cross-sectional area (CSA) of the internal jugular vein (IJV) estimated from ultrasound imagery. In this paper, a semi-automatic segmentation algorithm is proposed using a combination of region growing and active contour techniques to provide a fast and accurate segmentation of IJV ultrasound videos. The algorithm is applied to track and segment the IJV across a range of image qualities, shapes, and temporal variation. The experimental results show that the algorithm performs well compared to expert manual segmentation and outperforms several published algorithms incorporating speckle tracking.