Computer program images beating heart
In the United States, cardiovascular diseases are among the leading causes of persistent health problems, especially among the elderly. Early detection of potential heart problems can dramatically improve a patient's prognosis. One diagnostic method of increasing importance is the development of non-invasive tools to image the heart.
Researchers in the Whiting School of Engineering's Department of Computer Science have developed new motion tracking algorithms that can map out magnetic resonance images of cardiac structures in a way that improves the speed, quality and contrast of cardiovascular magnetic resonance imaging (MRI).
MRI is a widely used means for screening the heart and surrounding blood vessels. MRI uses radio waves to generate energy and then measure the response or signal of a specific tissue in the body. It uses this data to build a 3-D image of the internal organ being studied.
The process for creating images through an MRI requires obtaining data in small increments and then reconstructing a 3-D model by performing complicated mathematical manipulations on the data. The process for obtaining high-resolution images is very slow and time-consuming.
For the cardiovascular system, the data acquisition occurs over multiple heartbeats, causing the coronary arteries and valves being studied to move substantially while the image is taken. This often introduces artifacts and produces blurred, low-contrast images of the heart.
Additionally there is great variation between the respiratory functions of different patients, further complicating physicians' efforts to analyze and predict the motion of the heart and correct for it through motion compensation algorithms.
The Computational Interaction and Robots Lab, led by computer scientist Gregory Hager, designed a novel computer program called DEMOTRACS that is used to simplify MRI of the heart in real-time. A report on the computer program appears in the June 2007 proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.
Researchers in the Whiting School of Engineering's Department of Computer Science have developed new motion tracking algorithms that can map out magnetic resonance images of cardiac structures in a way that improves the speed, quality and contrast of cardiovascular magnetic resonance imaging (MRI).
MRI is a widely used means for screening the heart and surrounding blood vessels. MRI uses radio waves to generate energy and then measure the response or signal of a specific tissue in the body. It uses this data to build a 3-D image of the internal organ being studied.
The process for creating images through an MRI requires obtaining data in small increments and then reconstructing a 3-D model by performing complicated mathematical manipulations on the data. The process for obtaining high-resolution images is very slow and time-consuming.
For the cardiovascular system, the data acquisition occurs over multiple heartbeats, causing the coronary arteries and valves being studied to move substantially while the image is taken. This often introduces artifacts and produces blurred, low-contrast images of the heart.
Additionally there is great variation between the respiratory functions of different patients, further complicating physicians' efforts to analyze and predict the motion of the heart and correct for it through motion compensation algorithms.
The Computational Interaction and Robots Lab, led by computer scientist Gregory Hager, designed a novel computer program called DEMOTRACS that is used to simplify MRI of the heart in real-time. A report on the computer program appears in the June 2007 proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.
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