DOI: 10.5061/dryad.47d7wm3qg
title: Data from: Monitoring microvascular changes over time with a repositionable 3D ultrasonic capacitive micromachined row-column sensor

description: eHealth devices, including smartwatches and smart scales, have the
 potential to transform healthcare by enabling continuous, real-time
 monitoring of vital signs over extended periods. Existing technologies,
 however, lack comprehensive monitoring of the microvascular network, which
 is linked to conditions such as diabetes, hypertension, and small vessel
 diseases. This study introduces a novel ultrasound approach using a
 Capacitive Micromachined Ultrasound Transducers (CMUT) Row-Column Array
 (RCA) for continuous, ultrasensitive 3D Doppler imaging of microvascular
 changes such as hemodynamic variations or vascular remodeling. In vitro
 tests and in vivo studies with healthy volunteers demonstrated the
 sensor's ability to image the 3D microvascular network at high
 resolution over different time scales with automatic registration, and to
 detect microvascular changes with high sensitivity. Integrating this
 technology into wearable devices could one day enhance understanding,
 monitoring, and possibly early detection of microvascular-related health
 conditions.
description: This dataset is provided to reproduce the supplementary figure S2
 of the article "Monitoring microvascular changes over time with a
 repositionable 3D ultrasonic capacitive micromachined row-column
 sensor".  This figure shows power Doppler of the
 fingertip of a healthy volunteer acquired with the CMUT RCA sensor with
 different imaging sequences: Synthetic Aperture (SA), Hadamard Synthetic
 Aperture (HSA) and Plane Waves Imaging (PW) described in the methods of
 the article. 400 or 800 frames were acquired to keep the acquisition
 duration constant. Here, the Pulse Repetition Rate is set to 3 kHz for
 long acquisitions (8.5 s).<br><br>This dataset consists of
 data files, named Data_XXXX that are beamformed volumes of the different
 sequences. The fingertip surface has been removed to erase
 fingerprints. The Matlab program
 main_supplementary_figure_2.m applies an SVD clutter filter on these
 volumes to compute power Doppler volumes that are then projected to make
 the figure. Two different processing are applied to the Plane Waves
 acquisitions (X-Doppler and coherent compounding also described in the
 article) to compare those methods for our RCA acquisitions. 
description: # Monitoring microvascular changes over time with a repositionable 3D
 ultrasonic capacitive micromachined row-column sensor
 [https://doi.org/10.5061/dryad.47d7wm3qg](https://doi.org/10.5061/dryad.47d7wm3qg) ## Description of the data and file structure These data have been collected to compare different ultrasound imaging sequences used on a capacitive (CMUT) Row-Column Array (RCA). ### Files and variables #### File: data.zip **Description:** *Beamformed volume of the acquisitions in a matlab file* SA64 * **Data_SA64.mat** * *SA64 : Synthetic Aperture (64 emissions on 1 array, 400 frames)* * *Variable: Data_SA64, dimensions [axis Z, axis X, axis Y, Frames, Emitting Array]: [37, 64, 64, 400, 1]* * *Voxel size : 0.15 mm, Frame Rate : 46.875 Hz* HSA64 * **Data_HSA64.mat** * *HSA64 : Hadamard Synthetic Aperture imaging (64 emissions on 1 array, 400 frames)* * *Variable: Data_HSA64, dimensions [axis Z, axis X, axis Y, Frames, Emitting Array]: [37, 64, 64, 400, 1]* * *Voxel size : 0.15 mm, Frame Rate : 46.875 Hz* PW1616 * **Data_PW1616.mat** * *PW: Plane Waves imaging (16 emissions on both arrays, 800 frames)* * *Variable: Data_PW1616, dimensions [axis Z, axis X, axis Y, Frames, Emitting Array]: [37, 64, 64, 800, 2]* * *Voxel size : 0.15 mm, Frame Rate : 93.75 Hz* PW3232 * **Data_PW3232.mat** * *PW: Plane Waves imaging  (32 emissions on both arrays, 400 frames)* * *Variable: Data_PW3232, dimensions [axis Z, axis X, axis Y, Frames, Emitting Array]: [37, 64, 64, 400, 2]* * *Voxel size : 0.15 mm, Frame Rate : 46.875 Hz* ## Code/software **main_supplementary_figure_2.m** Works on : MATLAB Version: 9.10.0.2198249 (R2021a) Update 8 The program reproduce the figure S2 of the article. It just needs to be run and is divided in 3 parts :  * loading of the data files * processing of the data to get power Doppler of the different imaging sequences * display of the power Doppler for the different imaging sequences.