Lung boundary detection in pediatric chest x-rays

Sema Candemir; Sameer Antani; Stefan Jaeger; Renee Browning; George R. Thoma

doi:10.1117/12.2081060

17 March 2015 Lung boundary detection in pediatric chest x-rays

Sema Candemir, Sameer Antani, Stefan Jaeger, Renee Browning, George R. Thoma

Proceedings Volume 9418, Medical Imaging 2015: PACS and Imaging Informatics: Next Generation and Innovations; 94180Q (2015) https://doi.org/10.1117/12.2081060
Event: SPIE Medical Imaging, 2015, Orlando, Florida, United States

Abstract

Tuberculosis (TB) is a major public health problem worldwide, and highly prevalent in developing countries. According to the World Health Organization (WHO), over 95% of TB deaths occur in low- and middle- income countries that often have under-resourced health care systems. In an effort to aid population screening in such resource challenged settings, the U.S. National Library of Medicine has developed a chest X-ray (CXR) screening system that provides a pre-decision on pulmonary abnormalities. When the system is presented with a digital CXR image from the Picture Archive and Communication Systems (PACS) or an imaging source, it automatically identifies the lung regions in the image, extracts image features, and classifies the image as normal or abnormal using trained machine-learning algorithms. The system has been trained on adult CXR images, and this article presents enhancements toward including pediatric CXR images. Our adult lung boundary detection algorithm is model-based. We note the lung shape differences during pediatric developmental stages, and adulthood, and propose building new lung models suitable for pediatric developmental stages. In this study, we quantify changes in lung shape from infancy to adulthood toward enhancing our lung segmentation algorithm. Our initial findings suggest pediatric age groupings of 0 - 23 months, 2 - 10 years, and 11 - 18 years. We present justification for our groupings. We report on the quality of boundary detection algorithm with the pediatric lung models.

Citation Download Citation

Sema Candemir, Sameer Antani, Stefan Jaeger, Renee Browning, and George R. Thoma "Lung boundary detection in pediatric chest x-rays", Proc. SPIE 9418, Medical Imaging 2015: PACS and Imaging Informatics: Next Generation and Innovations, 94180Q (17 March 2015); https://doi.org/10.1117/12.2081060

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