Advanced Intelligent Clear-IQ Engine (AiCE) Delivers Advanced Image Quality with High Spatial Resolution

Building on its advanced image reconstruction technologies, today Canon Medical Systems USA, Inc. introduces deep convolutional neural network (DCNN) image reconstruction, ushering in a new era for CT. Canon Medical's Advanced Intelligent Clear-IQ Engine (AiCE) (pending 510(k) clearance) uses deep learning technology to differentiate signal from noise so that it can suppress noise while enhancing signal. The algorithm forges a new frontier for CT image reconstruction with its ability to learn from the high image quality of Model Based Iterative Reconstruction (MBIR) to reconstruct CT images with improved spatial resolution, 3-5x times faster than traditional MBIR.

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Canon Medical Systems USA, Inc. introduces deep convolutional neural network (DCNN) image reconstruction, ushering in a new era for CT. (Graphic: Business Wire)

With AiCE's deep learning approach, thousands of features learned during training help to differentiate signal from noise for improved resolution. AiCE applies a pre-trained DCNN to enhance spatial resolution while simultaneously reducing noise with reconstruction speeds fast enough for busy clinical environments.

"As a leader in deep learning reconstruction technology for CT images, Canon Medical is committed to forging new ground for CT imaging in order to meet our customers' evolving needs," said Dominic Smith, senior director, CT, PET/CT, and MR Business Units, Canon Medical Systems USA. "With AiCE technology, we haven't just raised the bar, we've set a new standard for image reconstruction in CT."

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