News | Artificial Intelligence | January 25, 2019

Siemens Healthineers Debuts AI-Rad Companion Chest CT

AI-based software assistant enables automated enhanced visualization of CT images of the lungs, heart and aorta

Siemens Healthineers Debuts AI-Rad Companion Chest CT

January 25, 2019 — Siemens Healthineers presented its first intelligent software assistant for radiology, the AI-Rad Companion Chest CT, at the 2018 Radiological Society of North America (RSNA) annual meeting, Nov. 25-30 in Chicago. The software brings artificial intelligence (AI) to computed tomography (CT). Using CT images of the chest, it can differentiate between various structures in that region of the body, highlighting them individually, and mark and measure potential abnormalities in the lungs, heart, aorta and coronary arteries. AI-Rad Companion Chest CT automatically translates its findings into structured reports.

Featuring underlying algorithms trained by Siemens Healthineers scientists on extensive clinical datasets, AI-Rad Companion Chest CT is designed to help radiologists interpret images via automation for potentially reduced time spent on results documentation. Siemens Healthineers plans additional intelligent assistants for the AI-Rad Companion platform.

The company said the goal of the intelligent software assistants is to help healthcare providers overcome the challenge of rising patient numbers coupled with shortfalls in staff.

While chest images display a wide variety of information, radiologists mainly assess these images with regard to the primary indication. The algorithms in AI-Rad Companion Chest CT are able to provide segmentation, measurement, and highlighting to support quantitative and qualitative analysis. The intelligent assistant generates standardized, reproducible and quantitative reports based on the AI-supported analysis.

AI-Rad Companion Chest CT supports a variety of tasks. Those tasks include automated identification, localization, labeling and measurement of lung lesions, as well as automated quantification of the total calcium volume in the coronary arteries.

Read the article "CT Calcium Scoring Becoming a Key Risk Factor Assessment"

A cloud-based solution, the software uses certified, secure teamplay infrastructure. It integrates seamlessly into existing clinical workflows and conforms to Digital Imaging and Communications in Medicine (DICOM) standards. The images and supporting information can be made available automatically in the picture archiving and communication system (PACS).

AI-Rad Companion Chest CT can analyze image data from all CT manufacturers. The software is pending 510(k) clearance with the U.S. Food and Drug Administration (FDA) and is not for sale in the U.S.

Watch the VIDEO: A Tour of the Artificial Intelligence Showcase at RSNA 2018

For more information: www.usa.healthcare.siemens.com

Related Content

Videos | Artificial Intelligence | November 07, 2019
Piotr J. Slomka, Ph.D., FACC, research scientist in the Artificial Intelligence in Medicine Program, Department of...
AI Could Use EKG Data to Measure Patient's Overall Health Status

Image courtesy of iStock

News | Artificial Intelligence | August 29, 2019
In the near future, doctors may be able to apply artificial intelligence (AI) to electrocardiogram data in order to...
Half of Hospital Decision Makers Plan to Invest in AI by 2021
News | Artificial Intelligence | August 08, 2019
A recent study conducted by Olive AI explores how hospital leaders are responding to the imperative to drive efficiency...
Artificial Intelligence Solution Improves Clinical Trial Recruitment

A nurse examines a patient in the Emergency Department of Cincinnati Children’s, where researchers successfully tested artificial intelligence-based technology to improve patient recruitment for clinical trials. Researchers report test results in the journal JMIR Medical Informatics. Image courtesy of Cincinnati Children’s.

News | Artificial Intelligence | July 31, 2019
Clinical trials are a critical tool for getting new treatments to people who need them, but research shows that...

An example of AI-assisted automation developed by TomTec, where a deep learning algorithm automatically marks the myocardial borders and performs auto quantification This removes time consuming tasks to free up the operator to spend more time with patients and helps make exams more reproducible.

Feature | Artificial Intelligence | July 26, 2019
Intelligent software solutions (aka...
vRad Presents AI Model to Assess Probability of Aortic Dissection
News | Artificial Intelligence | July 01, 2019
vRad (Virtual Radiologic), a Mednax company recently made a scientific presentation, “Screening for Aortic Dissection...
Videos | Artificial Intelligence | June 28, 2019
This is a quick example of how artificial intelligence (AI) is being integrated on the back end of cardiac ultrasound
Overlay Init