It's official – Google AI gives you cancer ...diagnosis in real time: Neural net can spot breast, prostate tumors

Boffins spill beans on super 'scope machine-learning tech


Google Health's so-called augmented-reality microscope has proven surprisingly accurate at detecting and diagnosing cancerous tumors in real time.

The device is essentially a standard microscope decked out with two extra components: a camera, and a computer running AI software with an Nvidia Titan Xp GPU to accelerate the number crunching. The camera continuously snaps images of body tissue placed under microscope, and passes these images to a convolutional neural network on the computer to analyze. In return, the neural net spits out, in real time allegedly, a heatmap of the cells in the image, labeling areas that are benign and abnormal on the screen for doctors to inspect.

Google's eggheads tried using the device to detect the presence of cancer in samples of breast and prostate cells. The algorithms had a performance score of 0.92 when detecting cancerous lymph nodes in breast cancer and 0.93 for prostate cancer, with one being a perfect score, so it’s not too bad for what they describe as a proof of concept.

Details of the microscope system have been described in a paper published in Nature this week. The training data for breast cancer was taken from here, and here for prostate cancer. Some of the training data was reserved for inference testing.

The device is a pretty challenging system to build: it requires a processing pipeline that can handle, on the fly, microscope snaps that are high resolution enough to capture details at the cellular level. The size of the images used in this experiment measure 5,120 × 5,120 pixels. That’s much larger than what’s typically used for today's deep learning algorithms, which have millions of parameters and require billions of floating-point operations just to process images as big as 300 pixels by 300 pixels.

psychosis

Boffins' neural network can work out from your speech whether you'll develop psychosis

READ MORE

To cope with these larger images, the convolutional neural network, which is based on Google's Inception V3 architecture, breaks them up into little patches that are analysed individually. It also takes time to train the technology to detect and classify cancerous cells, with the help of humans, from pictures of varying levels of quality. All of this then has to work in real time during the inference stage in order for it to be useful for doctors: they'd like to know as soon as possible, not hours or days later.

“The latency quantifies the absolute computational performance of the ARM [augmented-reality microscope] system,” the researchers wrote. Although they used it to study cancer, they believe device might prove useful for other applications too.

“Beyond the clinic, the ARM could potentially be useful as a teaching tool by leveraging reverse image search tools that can help trainees quickly search reference resources and answer the question ‘what is this histologic feature that I am looking at?’ More experienced doctors could also leverage the ARM for clinical research to prospectively validate AI algorithms not previously approved for patient care, such as mutational status or microsatellite instability predictions.”

ARM is also promising for another reason. It’s cheaper than “conventional whole-slide scanners” by about one or two magnitudes, apparently. We have asked Google for more comment. ®


Other stories you might like

  • Talos names eight deadly sins in widely used industrial software
    Entire swaths of gear relies on vulnerability-laden Open Automation Software (OAS)

    A researcher at Cisco's Talos threat intelligence team found eight vulnerabilities in the Open Automation Software (OAS) platform that, if exploited, could enable a bad actor to access a device and run code on a targeted system.

    The OAS platform is widely used by a range of industrial enterprises, essentially facilitating the transfer of data within an IT environment between hardware and software and playing a central role in organizations' industrial Internet of Things (IIoT) efforts. It touches a range of devices, including PLCs and OPCs and IoT devices, as well as custom applications and APIs, databases and edge systems.

    Companies like Volvo, General Dynamics, JBT Aerotech and wind-turbine maker AES are among the users of the OAS platform.

    Continue reading
  • Despite global uncertainty, $500m hit doesn't rattle Nvidia execs
    CEO acknowledges impact of war, pandemic but says fundamentals ‘are really good’

    Nvidia is expecting a $500 million hit to its global datacenter and consumer business in the second quarter due to COVID lockdowns in China and Russia's invasion of Ukraine. Despite those and other macroeconomic concerns, executives are still optimistic about future prospects.

    "The full impact and duration of the war in Ukraine and COVID lockdowns in China is difficult to predict. However, the impact of our technology and our market opportunities remain unchanged," said Jensen Huang, Nvidia's CEO and co-founder, during the company's first-quarter earnings call.

    Those two statements might sound a little contradictory, including to some investors, particularly following the stock selloff yesterday after concerns over Russia and China prompted Nvidia to issue lower-than-expected guidance for second-quarter revenue.

    Continue reading
  • Another AI supercomputer from HPE: Champollion lands in France
    That's the second in a week following similar system in Munich also aimed at researchers

    HPE is lifting the lid on a new AI supercomputer – the second this week – aimed at building and training larger machine learning models to underpin research.

    Based at HPE's Center of Excellence in Grenoble, France, the new supercomputer is to be named Champollion after the French scholar who made advances in deciphering Egyptian hieroglyphs in the 19th century. It was built in partnership with Nvidia using AMD-based Apollo computer nodes fitted with Nvidia's A100 GPUs.

    Champollion brings together HPC and purpose-built AI technologies to train machine learning models at scale and unlock results faster, HPE said. HPE already provides HPC and AI resources from its Grenoble facilities for customers, and the broader research community to access, and said it plans to provide access to Champollion for scientists and engineers globally to accelerate testing of their AI models and research.

    Continue reading

Biting the hand that feeds IT © 1998–2022