title: Severity quantification of pediatric viral respiratory illnesses in chest X-ray images.
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.
authors.forename: Kazunori
authors.initials: K
authors.lastname: Okada
authors.forename: Marzieh
authors.initials: M
authors.lastname: Golbaz
authors.forename: Awais
authors.initials: A
authors.lastname: Mansoor
authors.forename: Geovanny F
authors.initials: GF
authors.lastname: Perez
authors.forename: Krishna
authors.initials: K
authors.lastname: Pancham
authors.forename: Abia
authors.initials: A
authors.lastname: Khan
authors.forename: Gustavo
authors.initials: G
authors.lastname: Nino
authors.forename: Marius George
authors.initials: MG
authors.lastname: Linguraru
mesh_terms: D000465:Algorithms; D002648:Child; D002675:Child, Preschool; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D007223:Infant; D007231:Infant, Newborn; D008962:Models, Theoretical; D013902:Radiography, Thoracic / Q000379:methods*; D012140:Respiratory Tract Diseases / Q000000981:diagnostic imaging* / Q000209:etiology; D014777:Virus Diseases / Q000000981:diagnostic imaging* / Q000209:etiology