title: OBSERVER AND FEATURE ANALYSIS ON DIAGNOSIS OF RETINOPATHY OF PREMATURITY.
abstract: Retinopathy of prematurity (ROP) is a disease affecting low-birth weight infants and is a major cause of childhood blindness. However, human diagnoses is often subjective and qualitative. We propose a method to analyze the variability of expert decisions and the relationship between the expert diagnoses and features. The analysis is based on Mutual Information and Kernel Density Estimation on features. The experiments are carried out on a dataset of 34 retinal images diagnosed by 22 experts. The results show that a group of observers decide consistently with each other and there are popular features that have a high correlation with labels.
authors.affiliation: Cognitive Systems Laboratory, Northeastern University, Boston, MA.
authors.forename: E
authors.initials: E
authors.lastname: Ataer-Cansizoglu
authors.affiliation: Cognitive Systems Laboratory, Northeastern University, Boston, MA.
authors.forename: S
authors.initials: S
authors.lastname: You
authors.affiliation: Martinos Center for Biomedical Imaging, Charlestown, MA.
authors.forename: J
authors.initials: J
authors.lastname: Kalpathy-Cramer
authors.affiliation: Departments of Ophthalmology & Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR.
authors.forename: K
authors.initials: K
authors.lastname: Keck
authors.affiliation: Departments of Ophthalmology & Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR.
authors.forename: M F
authors.initials: MF
authors.lastname: Chiang
authors.affiliation: Cognitive Systems Laboratory, Northeastern University, Boston, MA.
authors.forename: D
authors.initials: D
authors.lastname: Erdogmus
keywords: feature selection; observer analysis; retinal image analysis