Hybrid segmentation of vessels and automated flow measures in in-vivo ultrasound imaging

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Vector Flow Imaging (VFI) has received an increasing attention in the scientific field of ultrasound, as it enables angle independent visualization of blood flow. VFI can be used in volume flow estimation, but a vessel segmentation is needed to make it fully automatic. A novel vessel segmentation procedure is crucial for wall-to-wall visualization, automation of adjustments, and quantification of flow in state-of-the-art ultrasound scanners. We propose and discuss a method for accurate vessel segmentation that fuses VFI data and B-mode for robustly detecting and delineating vessels. The proposed method implements automated VFI flow measures such as peak systolic velocity (PSV) and volume flow. An evaluation of the performance of the segmentation algorithm relative to expert manual segmentation of 60 frames randomly chosen from 6 ultrasound sequences (10 frame randomly chosen from each sequence) is also presented. Dice coefficient denoting the similarity between segmentations is used for the evaluation. The coefficient ranges between 0 and 1, where 1 indicates perfect agreement and 0 indicates no agreement. The Dice coefficient was 0.91 indicating to a very agreement between automated and manual expert segmentations. The flowrig results also demonstrated that the PSVs measured from VFI had a mean relative error of 14.5% in comparison with the actual PSVs. The error for the PSVs measured from spectral Doppler was 29.5%, indicating that VFI is 15% more precise than spectral Doppler in PSV measurement.

Original languageEnglish
Title of host publication2016 IEEE International Ultrasonics Symposium, IUS 2016
PublisherIEEE Computer Society Press
Publication date1 Nov 2016
Article number7728656
ISBN (Electronic)9781467398978
Publication statusPublished - 1 Nov 2016
Event2016 IEEE International Ultrasonics Symposium, IUS 2016 - Tours, France
Duration: 18 Sep 201621 Sep 2016


Conference2016 IEEE International Ultrasonics Symposium, IUS 2016
SeriesIEEE International Ultrasonics Symposium, IUS

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

ID: 331498257