Lungs

MYRIAN® XP-LUNG AND XP-LUNG NODULE

XP-Lung provides you with automatic segmentation and analysis tools of the lung parenchyma and airways to facilitate your diagnosis as well as surgical planning tools. In the case of suspected cancerous lesions, the advanced functions of the XP-Lung Nodule module will allow you to segment, quantify and follow up lung nodules in an intuitive way. This tool can be used for diagnosis, screening and therapeutic follow-up, as well as evaluation of the response to treatment.

The added values

An advanced visualization solution

Benefit from a set of functionalities dedicated to the visualization and analysis of thoracic scans. Segment volumes, visualize and quantify parenchymal lesions, then dive into airway exploration in an intuitive way.

A dedicated covid-19 protocol

The first solution CE-marked for Covid-19 analysis. With customizable thresholds for ground glass and dense opacities, visualize and quantify the volume of Covid-19 affected areas and export these results in a structured report.

Features for early lung cancer diagnosis

Investigate co-morbidities between lung disease and lung cancer with Myrian XP-Lung. A single interface to assess lung disease and detect lung nodules on chest scans. From diagnosis to treatment, thanks to the follow-up tools, Myrian allows you to follow the evolution of the nodule or the response to treatment on it.

Applications

MYRIAN XP-LUNG

Segmentation and quantification of low attenuation tissues
Automatic segmentation of lung and airway volumes
Airway visualization in CPR and stenting as part of surgical planning
Ability to perform virtual bronchoscopy
Segmentation of lesions
3D visualization of interactions between vascularization, airways and lesions
Simulation of lobectomy with automatic calculation of post-surgery lung volumes

MYRIAN XP-LUNG NODULE

Segmentation and characterization of pulmonary nodules
Display of anteriorities for longitudinal follow-up of nodules
Calculation of doubling time and growth percentage
Visualization of lesions in 3D
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