Research interface on a programmable ultrasound scanner

Shamdasani, Vijay; Bae, Unmin; Sikdar, Siddhartha; Yoo, Yangmo; Karadayi, Kerem; Managuli, Ravi; Kim, Yongmin

doi:10.1016/j.ultras.2007.11.009

Cited by 23 publications

(11 citation statements)

References 46 publications

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“…2 where TAF ACR = 0.07 PRF and CSL -P clutter = -50.0 dB, two clutter filters (i.e., PI-IIR3 and PI-IIR4) meet the requirement, and PI-IIR3 is selected since it has the lower passband cutoff frequency. To evaluate the proposed method with the CON and DM methods, in vivo data were acquired from the popliteal vein of a volunteer by a trained sonographer using a commercial ultrasound machine equipped with a research interface (HiVision 5500, Hitachi Medical Systems America, Twinsburg, OH, USA) [8]. The acquired data were processed off-line using the MATLAB (The Mathworks Inc., Natick, MA, USA).…”

Section: B Adaptive Clutter Rejectionmentioning

confidence: 99%

Adaptive clutter rejection for ultrasound color doppler imaging of lower extremity blood flow: Preliminary results

Kim

Lee

et al. 2009

2009 IEEE International Ultrasonics Symposium

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In this paper, the adaptive clutter rejection (ACR) method, in which an optimum clutter filter is dynamically selected at each location based on clutter power and instantaneous velocities, is applied to effectively remove flash artifacts during the assessment of deep venous thrombosis (DVT). To evaluate the ACR method, the in vivo data were acquired from an ultrasound machine by moving a 9-MHz linear array probe distally along the politeal vein of a volunteer. The ACR method was compared with the conventional static clutter rejection (CON) and down-mixing (DM) methods in terms of flow-signal-to-clutter ratio (SCR) for 80 frames. The ACR method provides 8.5 dB and 11.4 dB improvements in SCR compared to the DM and CON methods, respectively.Index Terms-ultrasound color Doppler imaging; adaptive clutter rejection; deep venous thrombosis; down mixing 978-1-4244-4390-1/09/$25.00

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Section: B Adaptive Clutter Rejectionmentioning

confidence: 99%

Adaptive clutter rejection for ultrasound color doppler imaging of lower extremity blood flow: Preliminary results

Kim

Lee

et al. 2009

2009 IEEE International Ultrasonics Symposium

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“…All modern commercial scanners also offer internal real-time sampling of signals from the transducer and some have dedicated research interfaces [16], [17], [18], [19]. The basic idea is therefore to use this sampling capability to acquire the hydrophone signal while the actual imaging sequence is run.…”

Section: Introductionmentioning

confidence: 99%

Safety Assessment of Advanced Imaging Sequences I: Measurements

Jensen

Rasmussen

Pihl

et al. 2016

IEEE Trans. Ultrason., Ferroelect., Freq. Contr.

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Abstract-A method for rapid measurement of intensities (I spta ), mechanical index (MI), and probe surface temperature for any ultrasound scanning sequence is presented. It uses the scanner's sampling capability to give an accurate measurement of the whole imaging sequence for all emissions to yield the true distributions. The method is several orders of magnitude faster than approaches using an oscilloscope, and it also facilitates validating the emitted pressure field and the scanner's emission sequence software. It has been implemented using the experimental SARUS scanner and the Onda AIMS III intensity measurement system (Onda Corporation, Sunnyvale, CA, USA). Four different sequences have been measured: a fixed focus emission, a duplex sequence containing B-mode and flow emissions, a vector flow sequence with B-mode and flow emissions in 17 directions, and finally a synthetic aperture (SA) duplex flow sequence. A BK8820e (BK Medical, Herlev, Denmark) convex array probe is used for the first three sequences and a BK8670 linear array probe for the SA sequence. The method is shown to give the same intensity values within 0.24% of the AIMS III Soniq 5.0 (Onda Corporation, Sunnyvale, CA, USA) commercial intensity measurement program. The approach can measure and store data for a full imaging sequence in 3.8 to 8.2 s per spatial position. Based on I spta , MI, and probe surface temperature, the method gives the ability to determine whether a sequence is within US FDA limits, or alternatively indicate how to scale it to be within limits.

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“…To address this research need, some groups have developed data acquisition (DAQ) interfaces in the form of add-ons designed specifically for clinical ultrasound scanners. For instance, Ashfaq et al [2] have implemented an add-on DAQ tool for the Siemens Antares system, while Shamdasani et al [3] have developed one that interfaces with a Hitachi HiVision scanner. Other imaging researchers have met their data access needs either by purchasing an openarchitecture scanner available on the market [4] or by designing their own in-house systems [5], [6].…”

Section: Introductionmentioning

confidence: 99%

Design of a multi-channel pre-beamform data acquisition system for an ultrasound research scanner

Tsang¹,

Yiu²,

Cheung³

et al. 2009

2009 IEEE International Ultrasonics Symposium

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Access to the pre-beamform data of each array channel on an ultrasound scanner is important to experimental investigations on advanced imaging research topics like adaptive beamforming and synthetic aperture imaging. Through such data access, we can obtain in-vitro or in-vivo insights on various imaging methods without resorting to hardware implementation. This paper reports the development of a pre-beamform data acquisition (DAQ) system that can collect data from 128 array elements in parallel. Our DAQ system is intended to interface with a Sonix-RP research scanner through a probe connector port. It comprises three major blocks: 1) a connector board that interfaces with the array probe and the scanner; 2) a main board that triggers data acquisition and controls data transfer to a computer; 3) four receiver boards that are each responsible for acquiring 32 channels of digitized raw data and storing them to the on-board DDR2 memory. The probe-connecting end of this system is interfaced with TX810 chips to facilitate switching between transmit and receive modes. When receiving data, the incoming analog signal is first passed into a low-noise amplifier. These signals are then sent into AD9272 chips on the four receiver boards to perform time gain compensation, anti-alias filtering, and 12-bit data sampling at an 80MHz rate. Subsequently, the digitized signal samples are de-serialized using a Virtex-5 FPGA and are stored into DDR2 memory. To facilitate data retrieval, we implemented a Virtex-5 FPGA on the main board to initiate data transfer, and if preferred, to perform onboard beamforming (programmable by user) prior to sending data to a computer through a USB 2.0 link. For our prototype, we used 16GB of DDR2 memory for data storage. With a frame rate of 35Hz, a 10cm depth-of-view and 128 transmit firings per frame, this DAQ system is capable of collecting pre-beamform data from all array channels for 2.5 seconds. We are currently completing the prototype development in collaboration with Ultrasonix.

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Research interface on a programmable ultrasound scanner

Cited by 23 publications

References 46 publications

Adaptive clutter rejection for ultrasound color doppler imaging of lower extremity blood flow: Preliminary results

Adaptive clutter rejection for ultrasound color doppler imaging of lower extremity blood flow: Preliminary results

Safety Assessment of Advanced Imaging Sequences I: Measurements

Design of a multi-channel pre-beamform data acquisition system for an ultrasound research scanner

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