Network-Based AI Engine Performs Airway Segmentation from CT Images

Ltd. (Seoul, Rep. of Korea), the COPD analysis solution named AVIEW Metric-Lung offers AI-powered lung/lobe segmentation, airway measurement and INSP/EXP lung registration for various quantifications. Designed for quantitative image biomarker of COPD, the software uses chest CT images to provide various quantitative analysis reports.

It provides seven cutting-edge methods to analyze the conditions of lung parenchyma, airway, and lung vessels that affect the lung function of the patient: LAA, size-based LAA, airway characteristic, INS-EXP parametric map, air-trapping, lung vessel distribution and ILD classification analysis methods. Easy workflow minimizes user interaction during lung/lobe segmentation, airway segmentation and, elastic inspiration/expiration registration.

Since thousands of quantitative results make it difficult to interpret the lung function of the patient, AVIEW Metric-Lung provides intuitive charts and visualizes groups of values to the lung anatomical structure for a comprehensive understanding. It helps to reduce the inconsistencies between readers and accurately determine how far the disease has progressed.

Using fast, high-quality 3D rendering, AVIEW Metric-Lung figures out more than 1,400 quantifications per case that can all be exported in CSV format for further research. It performs all quantifications without a single click, making it the first of its kind solution in the world. The web-based software can be accessed anywhere with any device using a web browser.

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