Adaptive Polar Active Contour for Segmentation and Tracking in Ultrasound Videos
This work addresses the need for accurate blood volume monitoring in medical conditions like sepsis and trauma, but it is incremental as it builds on existing active contour techniques.
The paper tackled the challenging problem of segmenting and tracking the internal jugular vein in ultrasound videos to estimate blood volume, proposing an adaptive polar active contour algorithm that improved segmentation performance compared to state-of-the-art methods.
Detection of relative changes in circulating blood volume is important to guide resuscitation and manage a variety of medical conditions including sepsis, trauma, dialysis and congestive heart failure. Recent studies have shown that estimates of circulating blood volume can be obtained from the cross-sectional area (CSA) of the internal jugular vein (IJV) from ultrasound images. However, accurate segmentation and tracking of the IJV in ultrasound imaging is a challenging task and is significantly influenced by a number of parameters such as the image quality, shape, and temporal variation. In this paper, we propose a novel adaptive polar active contour (Ad-PAC) algorithm for the segmentation and tracking of the IJV in ultrasound videos. In the proposed algorithm, the parameters of the Ad-PAC algorithm are adapted based on the results of segmentation in previous frames. The Ad-PAC algorithm is applied to 65 ultrasound videos captured from 13 healthy subjects, with each video containing 450 frames. The results show that spatial and temporal adaptation of the energy function significantly improves segmentation performance when compared to current state-of-the-art active contour algorithms.