Biomedical subjects

Svetoslav Ivanov Nikolov

Publications and source records attributed to Svetoslav Ivanov Nikolov.

5 recordsLinked to original sources

PubMed2006

Synthetic aperture ultrasound imaging.

The paper describes the use of synthetic aperture (SA) imaging in medical ultrasound. SA imaging is a radical break with today's commercial systems, where the image is acquired sequentially one image line at a time. This puts a strict limit on the frame rate and the possibility of acquiring a sufficient amount of data for high precision flow estimation. These constrictions can be lifted by employing SA imaging. Here data is acquired simultaneously from all directions over a number of emissions, and the full image can be reconstructed from this data. The paper demonstrates the many benefits of SA imaging. Due to the complete data set, it is possible to have both dynamic transmit and receive focusing to improve contrast and resolution. It is also possible to improve penetration depth by employing codes during ultrasound transmission. Data sets for vector flow imaging can be acquired using short imaging sequences, whereby both the correct velocity magnitude and angle can be estimated. A number of examples of both phantom and in vivo SA images will be presented measured by the experimental ultrasound scanner RASMUS to demonstrate the many benefits of SA imaging.

Arteries↗

PubMed2005

Ultrasound research scanner for real-time synthetic aperture data acquisition.

Conventional ultrasound systems acquire ultrasound data sequentially one image line at a time. The architecture of these systems is therefore also sequential in nature and processes most of the data in a sequential pipeline. This often makes it difficult to implement radically different imaging strategies on the platforms and makes the scanners less accessible for research purposes. A system designed for imaging research flexibility is the prime concern. The possibility of sending out arbitrary signals and the storage of data from all transducer elements for 5 to 10 seconds allows clinical evaluation of synthetic aperture and 3D imaging. This paper describes a real-time system specifically designed for research purposes. The system can acquire multichannel data in real-time from multi-element ultrasound transducers, and can perform some real-time processing on the acquired data. The system is capable of performing real-time beamforming for conventional imaging methods using linear, phased, and convex arrays. Image acquisition modes can be intermixed, and this makes it possible to perform initial trials in a clinical environment with new imaging modalities for synthetic aperture imaging, 2D and 3D B-mode, and velocity imaging using advanced coded emissions. The system can be used with 128-element transducers and can excite 128 transducer elements and receive and sample data from 64 channels simultaneously at 40 MHz with 12-bit precision. Two-to-one multiplexing in receive can be used to cover 128 receive channels. Data can be beamformed in real time using the system's 80 signal processing units, or it can be stored directly in RAM. The system has 16 Gbytes RAM and can, thus, store more than 3.4 seconds of multichannel data. It is fully software programmable and its signal processing units can also be reconfigured under software control. The control of the system is done over a 100-Mbits/s Ethernet using C and Matlab. Programs for doing, e.g., B-mode imaging can be written directly in Matlab and executed on the system over the net from any workstation running Matlab. The overall system concept is presented along with its implementation and examples of B-mode and in vivo synthetic aperture flow imaging.

Analog-Digital Conversion↗

PubMed2004

Directional synthetic aperture flow imaging.

A method for flow estimation using synthetic aperture imaging and focusing along the flow direction is presented. The method can find the correct velocity magnitude for any flow angle, and full color flow images can be measured using only 32 to 128 pulse emissions. The approach uses spherical wave emissions with a number of defocused elements and a linear frequency-modulated pulse (chirp) to improve the signal-to-noise ratio. The received signals are dynamically focused along the flow direction and these signals are used in a cross-correlation estimator for finding the velocity magnitude. The flow angle is manually determined from the B-mode image. The approach can be used for both tissue and blood velocity determination. The approach was investigated using both simulations and a flow system with a laminar flow. The flow profile was measured with a commercial 7.5 MHz linear array transducer. A plastic tube with an internal diameter of 17 mm was used with an EcoWatt 1 pump generating a laminar, stationary flow. The velocity profile was measured for flow angles of 90 and 60 degrees. The RASMUS research scanner was used for acquiring radio frequency (RF) data from 128 elements of the array, using 8 emissions with 11 elements in each emission. A 20-micros chirp was used during emission. The RF data were subsequently beamformed off-line and stationary echo canceling was performed. The 60-degree flow with a peak velocity of 0.15 m/s was determined using 16 groups of 8 emissions, and the relative standard deviation was 0.36% (0.65 mm/s). Using the same setup for purely transverse flow gave a standard deviation of 1.2% (2.1 mm/s). Variation of the different parameters revealed the sensitivity to number of lines, angle deviations, length of correlation interval, and sampling interval. An in vivo image of the carotid artery and jugular vein of a healthy 29-year-old volunteer was acquired. A full color flow image using only 128 emissions could be made with a high-velocity precision.

Adult↗

PubMed2003

Real time 3D visualization of ultrasonic data using a standard PC.

This paper describes a flexible, software-based scan converter capable of rendering 3D volumetric data in real time on a standard PC. The display system is used in the remotely accessible and software-configurable multichannel ultrasound sampling system (RASMUS system) developed at the Center for Fast Ultrasound Imaging. The display system is split into two modules: data transfer and display. These two modules are independent and communicate using shared memory and a predefined set of functions. It is, thus, possible to use the display program with a different data-transfer module which is tailored to another source of data (scanner, database, etc.). The data-transfer module of the RASMUS system is based on a digital signal processor from Analog Devices--ADSP 21060. The beamformer is connected to a PC via the link channels of the ADSP. A direct memory access channel transfers the data from the ADSP to a memory buffer. The display module, which is based on OpenGL, uses this memory buffer as a texture map that is passed to the graphics board. The scan conversion, image interpolation, and logarithmic compression are performed by the graphics board, thus reducing the load on the main processor to a minimum. The scan conversion is done by mapping the ultrasonic data to polygons. The format of the image is determined only by the coordinates of the polygons allowing for any kind of geometry to be displayed on the screen. Data from color flow mapping is added by alpha-blending. The 3D data are displayed either as cross-sectional planes, or as a fully rendered 3D volume displayed as a pyramid. All sides of the pyramid can be changed to reveal B-mode or C-mode scans, and the pyramid can be rotated in all directions in real time.

Humans↗

PubMed2003

In-vivo synthetic aperture flow imaging in medical ultrasound.

A new method for acquiring flow images using synthetic aperture techniques in medical ultrasound is presented. The new approach makes it possible to have a continuous acquisition of flow data throughout the whole image simultaneously, and this can significantly improve blood velocity estimation. Any type of filter can be used for discrimination between tissue and blood flow without initialization, and the number of lines used for velocity estimation is limited only by the nonstationarity of the flow. The new approach is investigated through both simulations and measurements. A flow rig is used for generating a parabolic laminar flow, and a research scanner is used for acquiring RF data from individual transducer elements. A reference profile is calculated from a mass flow meter. The parabolic velocity profile is estimated using the new approach with a relative standard deviation of 2.2% and a mean relative bias of 3.4% using 24 pulse emissions at a flow angle of 45 degrees. The 24 emissions can be used for making a full-color flow map image. An in-vivo image of flow in the carotid artery for a 29-year-old male also is presented. The full image is acquired using 24 emissions.

Adult↗