Next-Gen Ultrasound

Medical imaging borrows techniques from the microelectronics industry

9 min read
Photo of woman's abdomen holding ultrasound image.
Sharper Image: Micromachined transducer probes for ultrasound scanners should provide prenatal images that are even sharper than those new parents now get to see. The pictures, though, may never be as crisp as the one in this fanciful photo-illustration.
Photo-IllustratIon: Paul Vozdic/Getty Images

Almost invariably , a new baby’s photo album begins with a grainy black-and-white picture taken months before birth—a ­prenatal ultrasound image, which is often detailed enough to inspire comments about the child’s resemblance to various members of the family. But jokes about balding uncles notwithstanding, such scans serve a serious purpose and can prove immensely important, as when they allow doctors to diagnose and sometimes even repair a congenital malformation while the baby is still in the womb.

When seeing such an image for the first time, most people are awestruck. How can mere sound waves provide such remarkably clear views? Engineers may well ask something more: How can we give doctors even better ultrasound images? That question has engaged the three of us, along with other members of our Stanford acoustics group, for much of the last decade.

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Q&A: Marc Raibert on the Boston Dynamics AI Institute

The founder of Boston Dynamics talks with us about the new $400 million research institute

12 min read
Marc Raibert, an older white man with a bald head and a short white beard and glasses, gestures as he speaks on a stage. He is wearing formal pants and a flower-print short sleeve shirt.

Marc Raibert, founder and chairman of Boston Dynamics, speaks at a Hyundai Motor Group news conference during CES 2022 in Las Vegas, Nevada.

Steve Marcus/Reuters/Alamy

Last week, Hyundai Motor Group and Boston Dynamics announced an initial investment of over $400 million to launch the new Boston Dynamics AI Institute. The Institute was conceptualized by (and will be led by) Marc Raibert, the founder of Boston Dynamics, with the goal of “solving the most important and difficult challenges facing the creation of advanced robots.” That sounds hugely promising, but of course we had questions—namely, what are those challenges, how is this new institute going to solve them, and what are these to-be-created advanced robots actually going to do? And fortunately, IEEE Spectrum was able to speak with Marc Raibert himself to get a better understanding of what the Institute will be all about.

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Emmy Award Winner’s Algorithms Bring High-Quality Video to Your TV

He is working on making high-res images for the metaverse

5 min read
portrait of Alan Bovik
Alan Bovik

Alan Conrad Bovik’s passion for science fiction inspired him to pursue a career in engineering. His favorite sci-fi authors when he was young were Arthur C. Clarke, who penned 2001: A Space Odyssey, and Isaac Asimov, author of the Foundation series. Bovik says they wrote from a “very scientific point of view”—which made him want to help develop aerospace technology that would send humans “to other worlds.”

But he decided to study nuclear engineering in school—which then seemed like the future of energy. He discovered, however, that he didn't like the subject because it “required too much chemistry and memorization,” he says with a laugh. When he took a course in computer programming, he fell in love with it and ended up changing his major to computer engineering.

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Modeling Microfluidic Organ-on-a-Chip Devices

Register for this webinar to enhance your modeling and design processes for microfluidic organ-on-a-chip devices using COMSOL Multiphysics

1 min read
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Comsol

If you want to enhance your modeling and design processes for microfluidic organ-on-a-chip devices, tune into this webinar.

You will learn methods for simulating the performance and behavior of microfluidic organ-on-a-chip devices and microphysiological systems in COMSOL Multiphysics. Additionally, you will see how to couple multiple physical effects in your model, including chemical transport, particle tracing, and fluid–structure interaction. You will also learn how to distill simulation output to find key design parameters and obtain a high-level description of system performance and behavior.

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