4-D ICE: A 2-D Array Transducer With Integrated ASIC in a 10-Fr Catheter for Real-Time 3-D Intracardiac Echocardiography

Wildes, Douglas; Litsky, Warren; Haider, B.; Cogan, Scott; Sundaresan, K.; Mills, David; Yetter, Christopher; Hart, Patrick H.; Haun, Christopher R.; Concepcion, Mikael; Kirkhorn, J.; Bitoun, Marc

doi:10.1109/tuffc.2016.2615602

Cited by 78 publications

(69 citation statements)

References 44 publications

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“…Today, front-end connectivity and bandwidth challenges are addressed through e.g. application-specific integrated circuits that perform microbeamforming [59] or simple summation of the receive signals across neighbouring elements [60] to compress the full channel data into a manageable amount, and multiplexing of the receive signals. This inherently entails information loss, and typically leads to reduced image quality.…”

Section: Compressive Encodings For Tissue Dopplermentioning

confidence: 99%

Deep Learning in Ultrasound Imaging

2020

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Deep learning is taking an ever more prominent role in medical imaging. This paper discusses applications of this powerful approach in ultrasound imaging systems along with domain-specific opportunities and challenges.ABSTRACT | We consider deep learning strategies in ultrasound systems, from the front-end to advanced applications. Our goal is to provide the reader with a broad understanding of the possible impact of deep learning methodologies on many aspects of ultrasound imaging. In particular, we discuss methods that lie at the interface of signal acquisition and machine learning, exploiting both data structure (e.g. sparsity in some domain) and data dimensionality (big data) already at the raw radio-frequency channel stage.As some examples, we outline efficient and effective deep learning solutions for adaptive beamforming and adaptive spectral Doppler through artificial agents, learn compressive encodings for color Doppler, and provide a framework for structured signal recovery by learning fast approximations of iterative minimization problems, with applications to clutter suppression and super-resolution ultrasound. These emerging technologies may have considerable impact on ultrasound imaging, showing promise across key components in the receive processing chain.

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Section: Compressive Encodings For Tissue Dopplermentioning

confidence: 99%

Deep Learning in Ultrasound Imaging

2020

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“…Intravascular ultrasound imaging and endoscopic ultrasonography have thinner cables where the influence can be higher. Pre-amplifiers have been employed to tune output impedance of the transducer to the characteristic impedance of the cable where the energy reflection at the interface is greatly minimized [84][85][86]. Daft et al [87] used a transformer to match the electric impedance of driving electronics to the cable.…”

Section: Modeling Cable Effect On Transducer Performancementioning

confidence: 99%

A Review of Electric Impedance Matching Techniques for Piezoelectric Sensors, Actuators and Transducers

Rathod

2019

Electronics

107

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Any electric transmission lines involving the transfer of power or electric signal requires the matching of electric parameters with the driver, source, cable, or the receiver electronics. Proceeding with the design of electric impedance matching circuit for piezoelectric sensors, actuators, and transducers require careful consideration of the frequencies of operation, transmitter or receiver impedance, power supply or driver impedance and the impedance of the receiver electronics. This paper reviews the techniques available for matching the electric impedance of piezoelectric sensors, actuators, and transducers with their accessories like amplifiers, cables, power supply, receiver electronics and power storage. The techniques related to the design of power supply, preamplifier, cable, matching circuits for electric impedance matching with sensors, actuators, and transducers have been presented. The paper begins with the common tools, models, and material properties used for the design of electric impedance matching. Common analytical and numerical methods used to develop electric impedance matching networks have been reviewed. The role and importance of electrical impedance matching on the overall performance of the transducer system have been emphasized throughout. The paper reviews the common methods and new methods reported for electrical impedance matching for specific applications. The paper concludes with special applications and future perspectives considering the recent advancements in materials and electronics.

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“…It is, as the name suggests, invasive and requires additional femoral vessel access for deployment. Real time 4D ICE also appears to be on the horizon with reports on its development and pilot study usage are now emerging [39] .…”

Section: Intracardiac Echocardiogrammentioning

confidence: 99%

Atrial septal defect repair in the age of transcatheter devices

Zimmermann¹,

Hussain²,

Worku³

et al. 2019

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The aim of this review is to discuss the management of atrial septal defects (ASD) in the adult patient paying special attention to the elderly population and the most recent transcatheter advancements. ASDs are characterized by the following categories: ostium secundum, ostium primum, sinus venosus, and coronary sinus defects; though multiple defects may exist concurrently. Intervention for closure of ASDs are indicated with the development of right ventricular volume overload, or in the clinical context of paradoxical embolic stroke. Previously, there was significant disagreement regarding the timing of ASD closure in adult patients, but there is now general consensus that adult patients with clinical evidence of right ventricular overload should undergo closure of ASDs at the time of presentation. The present review describes the typical presentation of patients with symptomatic ASD's, medical management, and whether surgical or percutaneous approach should be pursued. We will also discuss other important considerations for patient selection and potential early and late complications of transcatheter ASD closure such as congestive heart failure, device embolization, and tissue erosion. At the time of this writing, there are currently three FDA-approved devices for percutaneous VSD closure including the Amplatzer TM Septal Occluder (ASO, St. Jude Medical, St. Paul, MN), Gore HELEX TM Septal Occluder (W.L. Gore and Associates, Newark, NJ), and Gore CARDIOFORM TM Septal occluder (GCSO, W.L. Gore and Associates, Newark, NJ) devices. Many premarket approvals were granted for devices that never went to market due to poor investigational study performance. Likewise, the HELEX device has since been discontinued upon bringing the GCSO device to market. We will focus primarily on the ASO device with a brief review of current investigations into the GCSO device, both of which carry an indication for closure small to medium sized ASDs in the ostium secundum position. Additionally, this review covers the safety of transcatheter closure of ASDs with currently available devices, review studies associated with devices available outside the United States, and perioperative considerations for transcatheter Page 2 of 18 Zimmermann et al. Vessel Plus 2019;3:31 I http://dx.intervention. Obstacles to device employment and countermeasures to overcome operational challenges will also be discussed. To this end, variations or similarities of currently approved devices will be emphasized throughout this discussion where possible. Lastly, we will offer insights into device evolution trends with the expectation of new device developments on the horizon. We will briefly discuss up and coming areas of active research, including the emerging fields of novel biomaterials and gene therapy. MORPHOLOGY AND CLINICAL FEATURES OF ASDS Location, Morphology, and suitability for surgery vs. transcatheter interventionIt is important to note that morphological variations of different types of ASDs, which determines whether a particular defect is amenabl...

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4-D ICE: A 2-D Array Transducer With Integrated ASIC in a 10-Fr Catheter for Real-Time 3-D Intracardiac Echocardiography

Cited by 78 publications

References 44 publications

Deep Learning in Ultrasound Imaging

Deep Learning in Ultrasound Imaging

A Review of Electric Impedance Matching Techniques for Piezoelectric Sensors, Actuators and Transducers

Atrial septal defect repair in the age of transcatheter devices

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