Feasibility of pulse wave velocity estimation from low frame rate US sequences in vivo
| Autor: | Matthew Bruce, Matthew O'Donnell, Michelle Hippke, Maria Zontak, A. J. Schwartz |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Scanner
business.industry Acoustics Frame (networking) Image segmentation 030204 cardiovascular system & hematology RANSAC Frame rate Tracking (particle physics) 01 natural sciences 03 medical and health sciences Speckle pattern 0302 clinical medicine 0103 physical sciences Computer vision Artificial intelligence business 010301 acoustics Pulse wave velocity Mathematics |
| Zdroj: | SPIE Proceedings. |
| ISSN: | 0277-786X |
| Popis: | The pulse wave velocity (PWV) is considered one of the most important clinical parameters to evaluate CV risk, vascular adaptation, etc. There has been substantial work attempting to measure the PWV in peripheral vessels using ultrasound (US). This paper presents a fully automatic algorithm for PWV estimation from the human carotid using US sequences acquired with a Logic E9 scanner (modified for RF data capture) and a 9L probe. Our algorithm samples the pressure wave in time by tracking wall displacements over the sequence, and estimates the PWV by calculating the temporal shift between two sampled waves at two distinct locations. Several recent studies have utilized similar ideas along with speckle tracking tools and high frame rate (above 1 KHz) sequences to estimate the PWV. To explore PWV estimation in a more typical clinical setting, we used focused-beam scanning, which yields relatively low frame rates and small fields of view (e.g., 200 Hz for 16.7 mm filed of view). For our application, a 200 Hz frame rate is low. In particular, the sub-frame temporal accuracy required for PWV estimation between locations 16.7 mm apart, ranges from 0.82 of a frame for 4m/s, to 0.33 for 10m/s. When the distance is further reduced (to 0.28 mm between two beams), the sub-frame precision is in parts per thousand (ppt) of the frame (5 ppt for 10m/s). As such, the contributions of our algorithm and this paper are: 1. Ability to work with low frame-rate ( 200Hz) and decreased lateral field of view. 2. Fully automatic segmentation of the wall intima (using raw RF images). 3. Collaborative Speckle Tracking of 2D axial and lateral carotid wall motion. 4. Outlier robust PWV calculation from multiple votes using RANSAC. 5. Algorithm evaluation on volunteers of different ages and health conditions. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|