Features

Nodule detection*

Longitudinal tracking

Volumetric segmentation

Lung-RADS

Open. Review. Confirm. Report. It's that easy.

Automatic detection* of solid, part solid, and ground glass nodules. Our interactive workflow allows the user to add, edit, or delete detections with automatic updates to quantitative information.

*Detection is for Research use only in US
Lung Nodule

Automatically assess each lesion's evolution over time.

Whether you have one or many studies to compare, Arterys has your back. Automatically track nodules over time with tabular and graphical progression.

Lung Report

Volumetric segmentation of nodules

With the Arterys Lung AI application, precise volumetric segmentation of lung nodules is available automatically for both detected and user found nodules. Deep Learning reduces variability across analyses.

Lung LinkedNodule

Built-in Lung-RADS calculations

Standardize reporting of screening exams using the integrated Lung-RADS workflow. Share and communicate results effectively with patients and among colleagues. Arterys Lung AI supports Lung-RADS versions 1.0 and 1.1, as well as linear and volumetric measurements.

Lung LungRADS

Strength in numbers

Reduce low dose CT reading time by

45%

Reduce missed nodule detections by up to

70%

Arterys Lung AI is your partner in chest CT analysis. We support the tedious, time consuming portions of your workflow with automation so that you can focus on the parts that matter.

Intended Use

Arterys MICA includes an optional Oncology AI module which provides analytical tools to help the user assess and document changes in morphological activity at diagnostic and therapy follow-up examinations. It is a tool used to support the oncological workflow by helping the user confirm the absence or presence of lesions, including evaluation, quantification, follow-up, and documentation of any such lesions.
Arterys MICA software is intended to be used as a support tool by trained healthcare professionals to aid in diagnosis. It is intended to provide image and related information that is interpreted by a trained professional to render findings and/or diagnosis, but it does not directly generate any diagnosis or potential findings.

Limitations

The nodule detection and segmentation algorithms are optimized for Low Dose CT. However, the algorithms will process any chest CT DICOM including regular dose CT, CAP and PA series without generating an error.

Information on training data

The lung nodule detection model was trained and validated on 2227 lung CT scans representing approximately 10000 nodules of 4 to 30 mm in size. To represent an asymptomatic patient population, a blend of primarily low-dose/non-contrast screening exams and minority standard-dose/contrast incidental findings exams was used.

Model performance metrics

Standalone model performance from 240 case lung assessment validation for findings between 4 to 30mm for a 3/4 Ground Truth expert radiologist consensus level:
Sensitivity: **0.93 **_(0.90 - 0.97) _
FP/scan: **1.53 **_(1.24 - 1.84)_

Performance Curves

Performance Curves

Arterys

Arterys

Arterys is the World's First Online Medical Imaging Platform 100% Cloud native, powered by AI and FDA cleared.

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