Lunit INSIGHT CXR helps detect and diagnose 10 of the most common abnormal radiologic findings in Chest X-rays
The probability of lesion presence is scored from 0 to 100.
AI Analysis Report summarizes the Detected Location and Abnormality Score in the form of a report.
Scores of abnormal findings above the predefined threshold are shown in the analyzed image.
Example of threshold for nodule adjusted to 20
* Note : Finding(s) applied with threshold 15 are not shown in the bar.
Lunit INSIGHT CXR automatically retrieves the previous patient’s X-ray images and compares them with the current images to indicate the changes in the areas of pneumothorax, consolidation, and pleural effusion.
* Availability may vary depending on the type of PACS.
According to the European Respiratory Journal,
Lunit INSIGHT CXR helped reduce the reading time for normal cases by 33% when assisting radiologists in reading Chest X-rays.
Ju Gang Nam, Minchul Kim, et al. Development and validation of a deep learning algorithm detecting 10 common abnormalities on chest radiographs.
Lunit INSIGHT CXR can be integrated into your workflow, transforming your reading experience.
The algorithm is updated annually with additional training datasets or new features by the manufacturer to manage the performance.
As this product is a medical device, please read the user manual carefully before use.
The publications listed below are not subject to the review of medical device advertising and are intended to showcase Lunit’s technology.
Watch the animated video about Lunit INSIGHT CXR featured in peer-reviewed journals