| Literature DB >> 25003972 |
E Ataer-Cansizoglu1, S You1, J Kalpathy-Cramer2, K Keck3, M F Chiang3, D Erdogmus1.
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.Entities:
Keywords: feature selection; observer analysis; retinal image analysis
Year: 2012 PMID: 25003972 PMCID: PMC4076142 DOI: 10.1109/MLSP.2012.6349809
Source DB: PubMed Journal: IEEE Int Workshop Mach Learn Signal Process