Estimate Trajectory of the Ultrasound Scan using Inertia Sensor
Estimate Trajectory of the Ultrasound Scan using Inertia Sensor
批准号:
522817-2017
负责人:
Lou, Edmond
金额:
$1.82万
依托单位:
依托单位国家:
加拿大
项目类别:
Engage Grants Program
财政年份:
2017
资助国家:
加拿大
项目状态:
已结题
起止时间:
2017-01-01 至 2018-12-31
中文摘要
该项目的目标是开发和验证使用超声进行医学成像的工具,方法是:a)开发一种基于惯性传感器的算法,该惯性传感器由3轴加速度计、3轴陀螺仪和3轴磁力计组成,嵌入超声探头中以估计超声扫描的轨迹,B)将所述轨迹信息与2D超声扫描图像结合以重建3D图像,以及c)建立所述3D重建图像的精度。所开发的算法将为Clarius公司推广其超声系统进行三维图像重建提供科学依据。Clarius目前的超声系统是一种手持设备,它使用Wi-Fi Direct和蓝牙连接到iOS或Android智能设备以显示2D图像。来自加速度计、陀螺仪和磁力计的数据以60 Hz和14位分辨率发送到智能设备。Clarius尚未实现惯性传感器数据提供位置和方向信息。陀螺仪测量加上磁力计数据的积分应该准确地估计方位。计算出的方位将与减去地球重力信息的加速度计数据进行二次积分以估计位置。然而,由于惯性测量通常是噪声和有偏的,从角速度到旋转和从加速度到位置的积分步骤将引入积分漂移。为了使积分漂移最小化,周期性复位或在短时间内捕获数据可以解决漂移问题。
英文摘要
The objectives of this project are to develop and validate tools to use ultrasound for medical imaging by a)developing an algorithm based on an inertia sensor, consisting of a 3 axis-accelerometer, a 3-axis gyroscopeand a 3-axis magnetometer, which is embedded inside the ultrasound probe to estimate the trajectory ofultrasound scan, b) integrating the trajectory information with 2D ultrasound scanned images to reconstruct 3Dimages and c) establishing the accuracy of the 3D reconstructed images. The developed algorithm will providescientific underpinning for Clarius' promotion of their ultrasound system for 3D images reconstruction. Thecurrent ultrasound system from Clarius is a handheld device which uses Wi-Fi Direct and Bluetooth to connectto an iOS or Android smart device to display 2D images. The data from the accelerometer, gyroscope andmagnetometer are sent to the smart device at 60 Hz with 14-bit resolution. Clarius has not yet implemented theinertia sensor data to provide position and orientation information. Integration of the gyroscope measurementsplus the magnetometer data should accurately estimate the orientation. The calculated orientation will becombined with the accelerometer data which subtracts the earth's gravity information and perform a doubleintegration to estimate the position. However, since the inertial measurements are usually noisy and biased, theintegration steps from angular velocity to rotation and from acceleration to position will introduce integrationdrift. To minimize the integration drift, a periodic reset or capturing data in a short period of time may resolvethe drifting problem.
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