–(BUSINESS WIRE)– Enlitic, a privately-held company utilizing artificial intelligence to streamline medical imaging workflows for radiologists, announced the close of its $15M Series B financing round. The investment was led by Marubeni, with whom the company has been developing the Japanese market since 2017.
The round saw further investment from Capitol Health, who previously led the company’s Series A in 2016, as well as new participation from several top investors in Australia.
Kevin Lyman, CEO of Enlitic, commented:
“Radiologists have one of the hardest jobs in the world. They need to be able to identify thousands of different abnormalities in hundreds of different types of images. Even a single mistake can mean life or death, and yet they’re asked to read under tremendous time pressure in an environment full of distractions.”
Enlitic – deep learning medical imaging process
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The Neural Compute Stick 2 (NCS2), the latest incarnation of Intel’s USB-stick with Artificial Intelligence hardware inside, makes working with Artificial Intelligence affordable. Target environments are embedded IoT applications. This compact, fanless computer-vision and deep-neural-network (DNN) accelerator is now shipping through RS Components (RS), the trading brand of tech company Electrocomponents plc.
As well as for use by data scientists and academics, the device is said to be ideal for a wide selection of developers and engineers looking at integrating computer-vision and artificial intelligence (AI) capabilities into their Internet of Things (IoT) applications. Available in the convenient USB form factor, the stick is enabling deep-learning prototyping on a laptop or any other computing device with a USB interface.
This new hardware could be used to start prototype one of the most valuable deep learning applications in Diagnostic Imaging: the detection algorithm to localize structures (for example) in 2D or 3D space, detection of lung nodules or liver metastases on CT images.
The NCS 2 also becomes a highly versatile prototyping and development tool when combined with the Intel Distribution of OpenVINO toolkit, which offers support for deep learning, computer vision and hardware acceleration to enable applications that have human-like vision capabilities.
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Utilizing artificial intelligence (AI) and the internet, radiology and medical imaging have greatly improved patient care and the transfer of medical records and images.