  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.
