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In interstitial lung diseases, early diagnosis is important
because there is no appropriate treatment when fibrosis is in progress.

Medical AI automatically quantifies fibrotic lesions to aid in accurate diagnosis.

Medical AI automatically
quantifies fibrotic lesions to aid
in accurate diagnosis.

MFDS • CE Clearance

Classifying 6 different ILD types

AVIEW Lung Texture can assist in analyzing the location and distribution of 6 patterns.

  • Pattern N - Pattern of normal area without lesion
  • Pattern E - Pattern of dilated alveolar space
  • Pattern G - A pattern that looks like cloudy glass
  • Pattern R - Reticulated intricately intertwined pattern
  • Pattern H - honeycomb pattern
  • Pattern C - Pattern in the form of hardened soft tissue

Confirm results with automated reports

The results of the patterns distributed on lungs and lobes can be reviewed at a glance as a Bull’s eye table.

Analyzes areas that can potentially develop into Interstitial lung disease (ILA).

  • The fibrotic area and the non-fibrotic area are differentiated and the results are provided according to the guidelines proposed by Fleischner society.
  • The lung is divided into 6 zones, and when the ILA area exceeds 5%, it is highlighted and displayed.

Evidence

  • Interstitial lung abnormalities: New insights between theory and clinical practice

    insights into imaging, 2022

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  • Content-based image retrieval using deep learning for interstitial lung disease diagnosis by chest CT

    Radiology, 2021

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  • Interstitial lung abnormalities detected incidentally on CT: a Position Paper from the Fleischner Society

    Lancet Respir Med, 2020

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  • Content-Based Image Retrieval of Chest CT with Convolutional Neural Network for Diffuse Interstitial Lung Disease: Performance Assessment in Three Major Idiopathic Interstitial Pneumonias

    Korean Journal of Radiology, 2020

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