Ultrasound signal processing
Ultrasound imaging has been used as a diagnostic and therapeutic approach for various ailments in the fields of Cardiology, Endocrinology, for the observation of fetus in the mother’s womb and etc. It is a non-invasive and relatively economical technology. Doppler Ultrasound is one of the fields...
Saved in:
Main Author: | |
---|---|
Other Authors: | |
Format: | Final Year Project |
Language: | English |
Published: |
2009
|
Subjects: | |
Online Access: | http://hdl.handle.net/10356/17875 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
id |
sg-ntu-dr.10356-17875 |
---|---|
record_format |
dspace |
spelling |
sg-ntu-dr.10356-178752023-07-07T15:46:59Z Ultrasound signal processing Shivani Patra. Zhang Cishen School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing Ultrasound imaging has been used as a diagnostic and therapeutic approach for various ailments in the fields of Cardiology, Endocrinology, for the observation of fetus in the mother’s womb and etc. It is a non-invasive and relatively economical technology. Doppler Ultrasound is one of the fields of ultrasound which focuses on the blood flow in the body in order to detect various abnormalities in the blood vessels. This is done by using the Doppler effect to find the blood flow velocity and turbulence. These parameters can be found by calculating the Doppler mean frequency shift and variance using systematic steps. This project focuses on the signal processing of this Doppler ultrasound. The process of acquiring color radiofrequency data from the machine and to process the signal is discussed in the report. The process firstly includes, the proper arrangement of raw data into a four dimensional matrix which is then demodulated using Hilbert transform. Clutter filtering is then required to minimize the effect from slow moving tissues and stationary blood vessel walls on the blood flow frequency. The Autocorrelation algorithm is used to find the Doppler frequency shift which in turn is related to the velocity of the blood flow. In order to get the final image, processes like Smoothing, Thresholding, Colormapping are essential. The project has been successful in analyzing the ultrasound machine in order to get the real time image on the screen and then in writing a code to process the raw data to get a Doppler image. Bachelor of Engineering 2009-06-17T05:31:19Z 2009-06-17T05:31:19Z 2009 2009 Final Year Project (FYP) http://hdl.handle.net/10356/17875 en Nanyang Technological University 80 p. application/pdf |
institution |
Nanyang Technological University |
building |
NTU Library |
continent |
Asia |
country |
Singapore Singapore |
content_provider |
NTU Library |
collection |
DR-NTU |
language |
English |
topic |
DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing |
spellingShingle |
DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing Shivani Patra. Ultrasound signal processing |
description |
Ultrasound imaging has been used as a diagnostic and therapeutic approach for various ailments in the fields of Cardiology, Endocrinology, for the observation of fetus in the mother’s womb and etc. It is a non-invasive and relatively economical technology.
Doppler Ultrasound is one of the fields of ultrasound which focuses on the blood flow in the body in order to detect various abnormalities in the blood vessels. This is done by using the Doppler effect to find the blood flow velocity and turbulence. These parameters can be found by calculating the Doppler mean frequency shift and variance using systematic steps.
This project focuses on the signal processing of this Doppler ultrasound. The process of acquiring color radiofrequency data from the machine and to process the signal is discussed in the report. The process firstly includes, the proper arrangement of raw data into a four dimensional matrix which is then demodulated using Hilbert transform. Clutter filtering is then required to minimize the effect from slow moving tissues and stationary blood vessel walls on the blood flow frequency. The Autocorrelation algorithm is used to find the Doppler frequency shift which in turn is related to the velocity of the blood flow. In order to get the final image, processes like Smoothing, Thresholding, Colormapping are essential.
The project has been successful in analyzing the ultrasound machine in order to get the real time image on the screen and then in writing a code to process the raw data to get a Doppler image. |
author2 |
Zhang Cishen |
author_facet |
Zhang Cishen Shivani Patra. |
format |
Final Year Project |
author |
Shivani Patra. |
author_sort |
Shivani Patra. |
title |
Ultrasound signal processing |
title_short |
Ultrasound signal processing |
title_full |
Ultrasound signal processing |
title_fullStr |
Ultrasound signal processing |
title_full_unstemmed |
Ultrasound signal processing |
title_sort |
ultrasound signal processing |
publishDate |
2009 |
url |
http://hdl.handle.net/10356/17875 |
_version_ |
1772826804128579584 |