Deep Convolutional Neural Network Image Reconstruction Technology for CT Receives FDA Clearance

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Building on its advanced image reconstruction technologies, Canon Medical Systems USA, Inc. has received 510(k) clearance on its new deep convolutional neural network (DCNN) image reconstruction technology, ushering in a new era for CT. Canon Medical’s Advanced Intelligent Clear-IQ Engine (AiCE) uses a deep learning algorithm 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. 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.

“Our AiCE technology utilizes a next generation approach to CT image reconstruction, further proving Canon Medical’s leadership and commitment to innovation in diagnostic imaging,” said Dominic Smith, senior director, CT, PET/CT, and MR Business Units, Canon Medical Systems USA. “This technology doesn’t just meet our customers’ evolving needs, it exceeds them, opening doors to clearer, more precise images to help optimize patient care.”

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