Smart 3D Camera Automates CT Patient Positioning

A new premium computerized tomography (CT) system leverages artificial intelligence (AI) in order to automatically assure precise and consistent patient positioning.

The Siemens Healthineers (Erlangen, Germany) SOMATOM Edge Plus 128-slice CT system enables quantitative imaging and improved tissue characterization using an imaging component based on TwinBeam Dual Energy technology. The split filter captures two spectral energies at the same time, permitting clinicians in many cases to avoid additional non-contrast exams, as it can thus generate virtual non-contrast images. An added feature is Tin Filter technology, which enables CT scans at very low doses by shielding patients from clinically irrelevant radiation.


Fully Assisting Scanner Technologies (FAST) features a 3D infrared camera positioned above the patient bed that allows the system to recognize the head, torso, and other parts of the body using AI, which helps it to automate CT scan preparation. Once identified, the table aligns itself to the correct position required for scanning the body region at isocenter, based on the selected protocol. FAST thus simplifies the preparation of patients, accelerates workflows, and allows lower doses.

The SOMATOM Edge Plus also enables scanning of obese patients with strong diagnostic confidence due to the Straton MX Sigma X-ray tube, which provides high power reserves at every kV value in 10-kV increments, and the Stellar Infinity detector. The combination results in sharp, high-contrast images at high speed and low dose, even when passing through wide swaths of tissue.

“Siemens Healthineers is excited about the potential of the SOMATOM Edge Plus with FAST Integrated Workflow to help healthcare providers improve workflow and patient management,” said Douglas Ryan, vice president of CT at Siemens Healthineers North America. “Integration of artificial intelligence into patient positioning not only improves image quality, but also expands precision medicine by reducing unnecessary variability for healthcare providers.”