Deep learning-based lung segmentation and automatic regional template in chest x-ray images for pediatric tuberculosis

Daniel Capellán-Martín; Juan J. Gómez-Valverde; Ramon Sánchez-Jacob; David Bermejo-Peláez; Lara García-Delgado; Elisa López-Varela; Maria J. Ledesma-Carbayo

doi:10.1117/12.2652626

7 April 2023 Deep learning-based lung segmentation and automatic regional template in chest x-ray images for pediatric tuberculosis

Daniel Capellán-Martín, Juan J. Gómez-Valverde, Ramon Sánchez-Jacob, David Bermejo-Peláez, Lara García-Delgado, Elisa López-Varela, Maria J. Ledesma-Carbayo

Author Affiliations +

Proceedings Volume 12465, Medical Imaging 2023: Computer-Aided Diagnosis; 124651W (2023) https://doi.org/10.1117/12.2652626
Event: SPIE Medical Imaging, 2023, San Diego, California, United States

Conference Poster

Abstract

Tuberculosis (TB) is still considered a leading cause of death and a substantial threat to global child health. Both TB infection and disease are curable using antibiotics. However, most children who die of TB are never diagnosed or treated. In clinical practice, experienced physicians assess TB by examining chest X-rays (CXR). Pediatric CXR has specific challenges compared to adult CXR, which makes TB diagnosis in children more difficult. Computer-aided diagnosis systems supported by Artificial Intelligence have shown performance comparable to experienced radiologist TB readings, which could ease mass TB screening and reduce clinical burden. We propose a multi-view deep learning-based solution which, by following a proposed template, aims to automatically regionalize and extract lung and mediastinal regions of interest from pediatric CXR images where key TB findings may be present. Experimental results have shown accurate region extraction, which can be used for further analysis to confirm TB finding presence and severity assessment.

Citation Download Citation

Daniel Capellán-Martín, Juan J. Gómez-Valverde, Ramon Sánchez-Jacob, David Bermejo-Peláez, Lara García-Delgado, Elisa López-Varela, and Maria J. Ledesma-Carbayo "Deep learning-based lung segmentation and automatic regional template in chest x-ray images for pediatric tuberculosis", Proc. SPIE 12465, Medical Imaging 2023: Computer-Aided Diagnosis, 124651W (7 April 2023); https://doi.org/10.1117/12.2652626

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available