AiCE: Deep Learning, Machine Learning, Artificial Intelligence

Advanced Intelligent Clear-IQ Engine (AiCE)

Advanced intelligent Clear-IQ Engine (AiCE)

Sharp, clear and distinct images.
At low dose.

Harnessing the enormous computational power of a Deep Convolutional Neural Network (DCNN), AiCE Deep Learning Reconstruction (DLR) is trained to differentiate signal from noise, so that the algorithm can suppress noise while enhancing signal. Because it is trained with advanced MBIR, it exhibits high spatial resolution. But unlike MBIR, AiCE DLR overcomes the challenges (image appearance and/or reconstruction speed) in clinical adoption.

AiCE DLR features:

Our best low-contrast resolution, ever†**
Improved low-contrast detectability, noise and spatial resolution relative to hybrid iterative reconstruction
Image noise appearance similar to FBP compared to MBIR reconstruction**
Dose neutral industry-leading ultra-high resolution*
Fast reconstruction
Easy workflow

†1.5mm @ 0.3%
*Aquilion Precision, Dose neutral between Ultra-high resolution mode with AiCE and normal resolution mode with hybrid iterative reconstruction
**Aquilion ONE Genesis

Advanced Intelligent Clear-IQ Engine

AiCE Deep Learning Reconstruction (AiCE DLR)

AiCE DLR applies a pre-trained Deep Convolutional Neural Network (DCNN)
AiCE is able to enhance spatial resolution and low contrast detectability while simultaneously reducing noise
The pre-trained DCNN makes reconstruction speeds much faster than MBIR and fast enough for routine clinical use
AiCE DLR image reconstruction differentiates signal from noise, so the algorithm can suppress noise while enhancing signal

AiCE Integrated Intelligence Product Lineup

Watch Video

The AiCE Server

Designed for collation and analysis of large amounts of data.

Our partnership with NVIDIA® has allowed Canon Medical Systems to make significant advances in artificial intelligence (AI) and data-intensive deep learning techniques in the healthcare sector. The AiCE Server enables the processing of large volumes of medical data while simultaneously coordinating a variety of patient information.

Deep Learning Reconstruction