Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

A Novel Method for Lung Image Processing Using Complex Networks

Version 1 : Received: 8 July 2022 / Approved: 11 July 2022 / Online: 11 July 2022 (09:12:00 CEST)

How to cite: Broască, L.; Trușculescu, A.A.; Ancușa, V.M.; Ciocârlie, H.; Oancea, C.; Stoicescu, E.; Manolescu, D.L. A Novel Method for Lung Image Processing Using Complex Networks. Preprints 2022, 2022070156. https://doi.org/10.20944/preprints202207.0156.v1 Broască, L.; Trușculescu, A.A.; Ancușa, V.M.; Ciocârlie, H.; Oancea, C.; Stoicescu, E.; Manolescu, D.L. A Novel Method for Lung Image Processing Using Complex Networks. Preprints 2022, 2022070156. https://doi.org/10.20944/preprints202207.0156.v1

Abstract

The High-Resolution Computed Tomography (HRCT) detection and diagnosis of diffuse lung disease is primarily based on the recognition of a limited number of specific abnormal findings, pattern combinations or their distributions, as well as anamnesis and clinical information. Since texture recognition has a very high accuracy percentage if a complex network approach is used, this paper aims to implement such a technique customized for diffuse interstitial lung diseases (DILD). The proposed procedure translates HRCT lung imaging into complex networks by taking samples containing a secondary lobule, converting them into complex networks and analyzing them in 3 dimensions: emphysema, ground glass opacity and consolidation. This method was evaluated on a 60 patient lot and the results show a clear quantifiable difference between healthy and affected lungs. By deconstructing the image on three pathological axes, the method offers an objective way to quantify DILD details which, so far, have only been analyzed subjectively.

Keywords

diffuse interstitial lung disease; complex networks; model; HRCT

Subject

Computer Science and Mathematics, Mathematical and Computational Biology

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our Diversity statement.

Leave a public comment
Send a private comment to the author(s)
* All users must log in before leaving a comment
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.