The 0.5 mm acquisition across all FOVs and collimations unveils finer details with precision. Its fully integrated design, powered by Through-Silicon-Via (TSV) technology, revolutionizes detector architecture by reducing the signal conduction path from centimeters to micrometers, significantly lowering electronic noise and delivering ultra-low noise signal output. The 3D anti-scatter grid, precisely aligned with the X-ray source, effectively blocks scattered photons, achieving a scatter-to-primary ratio of less than 8.5%.

Equipped with high-performance GPUs, the AIIR reconstruction host meets the complex computational demands of combined deep neural networks and MBIR. Its robust infrastructure accommodates a growing volume of CT scans and large-scale data transmissions, delivering efficient imaging workflows.

Ultra EFOV is an innovative deep learning-based algorithm that enables full bore-size imaging, revealing additional anatomical structures and enhancing skin contours. Compared to the conventional EFOV algorithm, Ultra EFOV offers superior continuity at the edge of the Scan FOV, extends the imaging range from 50 to 82 cm, providing enhanced coverage and more detailed visualization across a broader field.

The Ultra EFOV's neural network model is designed to learn and correct different truncation artifacts within the extended field of view, resulting in better quantitative accuracy and improved image quality. This advanced algorithm provides high precision in CT density determination, with an accuracy of ±20 HU.

※ Results from phantom test

Addressing motion artifacts requires combining improved temporal resolution with deep learning algorithms. While hardware improvements reduce artifacts, deep learning selects optimal phases and corrects severe motion artifacts beyond hardware's limits. This enables the uCT 868 to "freeze" motion and deliver undistorted images with enhanced coronary clarity.

In CT imaging, high acquisition speed minimizes motion artifacts and reduces radiation exposure. The native temporal resolution, which is determined by the rotation speed, directly impacts the quality of the raw data acquired. Currently, it is considered the most relevant indicator for eliminating motion artifacts in coronary artery imaging.

Conventional methods prioritize minimal heart motion but may not correspond to the phase that provides the best image quality for coronary arteries. Instead of using just CT value, CardioXphase leverages AI to accurately extract arteries, focusing on shape regularity and edge sharpness to select the best phase for imaging, enhancing further analysis.

Different cardiac cycles have different optimal phases.
For CT systems with the detector coverage less than 16cm, data acquisition of the whole heart requires multiple cardiac cycles. This implies that each cardiac cycle will have a corresponding optimal phase, especially in the case of irregular heart rhythms. CardioXphase chooses the optimal phase independently from each cardiac cycle, improving the overall coronary artery image quality.

With the AI-based coronary artery motion correction technology, our CT scanner is able to break the limit of system native temporal resolution and achieve an effective temporal resolution of 25ms, which greatly enhances the success rate and image clarity of coronary CTA imaging.

Conventional vessel extraction methods typically rely on CT value thresholds and fixed coronary models, which often fail, particularly when dealing with vessels affected by motion artifacts. In contrast, CardioCapture excels at accurately extracting the centerlines of various types of coronary arteries, even in challenging cases involving poor vessel quality or distal vessels.

The tube's liquid-bearing, low-friction design enable continuous anode rotation at high speed throughout the day without stopping, accelerating workflow and boosting productivity. With little preparation time required between scans, this setup is especially beneficial in time-critical scenarios.

The uAI Vision automates ISO-center positioning, enhancing efficiency, image consistency, and reducing radiation. Additionally, Easy Range optimizes workflow by recommending personalized scan ranges based on protocols.

The Organ-based Auto ALARA mA automatically recognizes the coordinate regions of the chest and abdomen to optimize dose modulation parameters for different organs.

With an 8 cm detector width and a high table speed of up to 440 mm/s, the system enables rapid scanning, completing whole-body imaging in just a few seconds.

uOmnispace enhances imaging with automated pre-processing and pre-fetching for immediate operation. Intelligent algorithms for segmentation, extraction, and labeling reduce manual effort, while a customizable layout tailors workflows to specific imaging needs, cutting processing time and ensuring precise, consistent results.

uOmnispace provides a comprehensive suite of 3D imaging and advanced visualization tools, supporting diverse clinical needs across specialties like general radiology, oncology, cardiology, and neurology. It empowers clinicians with greater confidence in decision-making.

Hyper Realistic Rendering (HRR) transforms medical imaging data into highly detailed and lifelike 3D digital visuals. Compared to conventional VR rendering, HRR provides a more accurate and realistic depiction of medical image details and features.