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Severity quantification of pediatric viral respiratory illnesses in chest X-ray images.
- Source :
-
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference [Annu Int Conf IEEE Eng Med Biol Soc] 2015; Vol. 2015, pp. 165-8. - Publication Year :
- 2015
-
Abstract
- Accurate assessment of severity of viral respiratory illnesses (VRIs) allows early interventions to prevent morbidity and mortality in young children. This paper proposes a novel imaging biomarker framework with chest X-ray image for assessing VRI's severity in infants, developed specifically to meet the distinct challenges for pediatric population. The proposed framework integrates three novel technical contributions: a) lung segmentation using weighted partitioned active shape model, b) obtrusive object removal using graph cut segmentation with asymmetry constraint, and c) severity quantification using information-theoretic heterogeneity measures. This paper presents our pilot experimental results with a dataset of 148 images and the ground-truth severity scores given by a board-certified pediatric pulmonologist, demonstrating the effectiveness and clinical relevance of the presented framework.
- Subjects :
- Algorithms
Child
Child, Preschool
Humans
Infant
Infant, Newborn
Models, Theoretical
Respiratory Tract Diseases etiology
Virus Diseases etiology
Image Processing, Computer-Assisted methods
Radiography, Thoracic methods
Respiratory Tract Diseases diagnostic imaging
Virus Diseases diagnostic imaging
Subjects
Details
- Language :
- English
- ISSN :
- 2694-0604
- Volume :
- 2015
- Database :
- MEDLINE
- Journal :
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
- Publication Type :
- Academic Journal
- Accession number :
- 26736226
- Full Text :
- https://doi.org/10.1109/EMBC.2015.7318326