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LUNG AI SOLUTION PROVES QUICK AND RELIABLE IN NODULE DETECTION

Published by Arterys on Apr 18, 2022

Discover through a Radiologists' clinical experience how Lung AI helps
physicians analyze and track lung nodules by automatically processing Lung CT
scans to deliver improved speed, efficiency, and accuracy of diagnostic
decisions. 


Dr. Eleanna Saloura is an Attending Radiologist at the Department of Computed
Tomography at Sakarellos Diagnostic Center in Greece.  She has been using Lung
AI, an advanced lung imaging technology that employs artificial intelligence
(AI) for over a year.

AI-enabled technologies allow radiologists to detect and track suspicious lung
nodules efficiently and effectively.

Dr. Saloura describes her experience and the capabilities of the technology:

 “I’m currently working for a diagnostic center and I have been using nodule
detection for every case over the past 6 months. Typically, I review the exam
first and then compare my findings with the findings of Arterys' Lung AI
Solution.

The Lung AI solution is very useful in detecting nodules that are close to small
arteries and small bronchi that are difficult to identify. It has a high
sensitivity in detecting nodules, larger than 3 millimeters but it also can
detect smaller nodules. Nonetheless, the smaller nodules are less impactful to
the clinical decision-making process.

In parallel, we need to take into consideration the medical history of the
patient, and the Lung AI solution provides more information related to the size
and density of the nodules. With this additional information, the physicians can
make more accurate diagnostic and treatment decisions.

Overall I think the Lung AI Solution is fast and reliable as a second opinion."




 

 


LEARN ABOUT OUR AI-ASSISTED CHEST CT ANALYSIS SOFTWARE

Discover how AI and cloud computing are expanding the possibilities for nodule
detection in our white paper Innovations in Lung Imaging. The information
presented includes:

 * Thoracic CT: A Key to Lung Cancer Survival
 * LDCT Imaging Challenges
 * Artificial Intelligence and Applications to CT
 * Deep Learning and Nodule Detection
 * Deep Learning and Workflow, Tracking, and Reporting
 * Cloud Computing: The Key to Advanced Imaging Analytics



Tags: Lung AI, Radiology
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