Time-of-flight and phase shift methods have both been used for vascular imaging with magnetic res... more Time-of-flight and phase shift methods have both been used for vascular imaging with magnetic resonance. Phase methods, and phase contrast in particular, are well suited to quantitative measurements of velocity and volume flow rate. The most robust methods for measuring flow encode through-plane velocity into phase shift and compute flow by integrating the measured velocity over the vessel lumen. The accuracy of the flow data can be degraded by the effects of acceleration and eddy currents and by partial volume effects, including the effects of finite slice thickness and resolution, pulsatile waveforms, motion, and chemical shift. The reproducibility depends on the signal-to-noise of the data and the strength of the flow encoding and can be degraded by inconsistent definition of the vessel boundary. The adjustable flow sensitivity inherent in this method is a particular asset, allowing phase contrast flow measurement to operate over a dynamic range exceeding 10(5). Recently developed rapid imaging methods are helpful in applications that would be compromised by respiratory motion. With care, excellent quantitative data can be quickly obtained in vivo, and the resulting flow information is valuable for the diagnosis and management of a variety of conditions.
Jorg F. Debatin, MD #{149}Robert H. Ting, MD #{149}Herbert Wegmuller, MD #{149}F. Graham Sommer, ... more Jorg F. Debatin, MD #{149}Robert H. Ting, MD #{149}Herbert Wegmuller, MD #{149}F. Graham Sommer, MD Jill 0. Fredrickson, MS #{149}Thomas J. Brosnan, PhD #{149}Brett S. Bowman, BS Bryan D. Myers, MD #{149}Robert J. Herfkens, MD #{149}Norbert J. Pelc, ScD ...
We describe Surface Editor—a tool for interactive specification of regions of interest (ROIs) on ... more We describe Surface Editor—a tool for interactive specification of regions of interest (ROIs) on brain surfaces. The tool allows users to define subsurfaces by tracing around areas within a triangle-mesh brain surface. The input to the program is a triangle-mesh representation of a brain volume and a set of user-defined input points on the mesh. The program connects each pair
An image-processing method called measurement-dependent filtering has been introduced to improve ... more An image-processing method called measurement-dependent filtering has been introduced to improve the SNR (signal-to-noise ratio) of selective images produced by various medical imaging systems. The basic algorithm involves the combination of the low-frequency information of the selective image with the high-frequency information of a nonselective image. A spatially variant control function modulates the amount of high frequency to be added at each point. A least-mean-square (LMS) control function formed from two basis images, namely the high-passed versions of the nonselective image (M(b)) and the selective image (S(b)), is introduced. The original algorithm is now viewed as a two-stage filtering method, including the low-pass filtering noise reduction and least squares filtering for the edge restoration. An appropriate linear transformation is used to convert the original basis images M(b) and S(b) into a new pair with orthogonal noise. This allows the implementation of the LMS and control function with practically obtainable a priori knowledge.
Time-of-flight and phase shift methods have both been used for vascular imaging with magnetic res... more Time-of-flight and phase shift methods have both been used for vascular imaging with magnetic resonance. Phase methods, and phase contrast in particular, are well suited to quantitative measurements of velocity and volume flow rate. The most robust methods for measuring flow encode through-plane velocity into phase shift and compute flow by integrating the measured velocity over the vessel lumen. The accuracy of the flow data can be degraded by the effects of acceleration and eddy currents and by partial volume effects, including the effects of finite slice thickness and resolution, pulsatile waveforms, motion, and chemical shift. The reproducibility depends on the signal-to-noise of the data and the strength of the flow encoding and can be degraded by inconsistent definition of the vessel boundary. The adjustable flow sensitivity inherent in this method is a particular asset, allowing phase contrast flow measurement to operate over a dynamic range exceeding 10(5). Recently developed rapid imaging methods are helpful in applications that would be compromised by respiratory motion. With care, excellent quantitative data can be quickly obtained in vivo, and the resulting flow information is valuable for the diagnosis and management of a variety of conditions.
Jorg F. Debatin, MD #{149}Robert H. Ting, MD #{149}Herbert Wegmuller, MD #{149}F. Graham Sommer, ... more Jorg F. Debatin, MD #{149}Robert H. Ting, MD #{149}Herbert Wegmuller, MD #{149}F. Graham Sommer, MD Jill 0. Fredrickson, MS #{149}Thomas J. Brosnan, PhD #{149}Brett S. Bowman, BS Bryan D. Myers, MD #{149}Robert J. Herfkens, MD #{149}Norbert J. Pelc, ScD ...
We describe Surface Editor—a tool for interactive specification of regions of interest (ROIs) on ... more We describe Surface Editor—a tool for interactive specification of regions of interest (ROIs) on brain surfaces. The tool allows users to define subsurfaces by tracing around areas within a triangle-mesh brain surface. The input to the program is a triangle-mesh representation of a brain volume and a set of user-defined input points on the mesh. The program connects each pair
An image-processing method called measurement-dependent filtering has been introduced to improve ... more An image-processing method called measurement-dependent filtering has been introduced to improve the SNR (signal-to-noise ratio) of selective images produced by various medical imaging systems. The basic algorithm involves the combination of the low-frequency information of the selective image with the high-frequency information of a nonselective image. A spatially variant control function modulates the amount of high frequency to be added at each point. A least-mean-square (LMS) control function formed from two basis images, namely the high-passed versions of the nonselective image (M(b)) and the selective image (S(b)), is introduced. The original algorithm is now viewed as a two-stage filtering method, including the low-pass filtering noise reduction and least squares filtering for the edge restoration. An appropriate linear transformation is used to convert the original basis images M(b) and S(b) into a new pair with orthogonal noise. This allows the implementation of the LMS and control function with practically obtainable a priori knowledge.
Uploads