Title :
Computer-Based Image Analysis of Liver Steatosis with Large-Scale Microscopy Imagery and Correlation with Magnetic Resonance Imaging Lipid Analysis
Author :
Kong, Jun ; Lee, Michael J. ; Bagci, Pelin ; Sharma, Puneet ; Martin, Diego ; Adsay, N. Volkan ; Saltz, Joel H. ; Farris, Alton B.
Abstract :
Most pathology analyses and measurements are prevalently carried out by trained reviewers in both clinical and research settings. Therefore, the resulting outputs are inexorably biased by interpreters and degraded with poor reproducibility. In this paper, we propose a computerized image analysis paradigm enabling quantitative characterizations of steatosis areas in microscopy images of pediatric liver biopsies. With the same set of patients, we also acquired the lipid measurements from magnetic resonance imaging data analysis for correlation investigation. Our preliminary results suggest a high correlation between the steatosis areas quantized with microscopy images and the lipid percentages calculated from radiology imaging data. Additionally, we compared the per formance of the proposed analysis method with those of three certified pathologists and a popular commercial algorithm. The results suggest the superiority of our method to both human reviewers and the commercial method in terms of the steatosis lipid correlation strength. This demonstrates that the developed method is promising for generating quantitative and reliable analysis results to better support further liver disease study.
Keywords :
biomedical MRI; data analysis; diseases; liver; medical image processing; paediatrics; computer-based image analysis; correlation investigation; large-scale microscopy imagery; liver disease study; liver steatosis; magnetic resonance imaging lipid data analysis; pediatric liver biopsies; radiology imaging data; steatosis lipid correlation strength; Correlation; Image segmentation; Lipidomics; Liver; Microscopy; Radiology; Shape; Data correlation; Large-scale microscopy image analysis; Liver steatosis quantification; Parallel computation; Tissue representation;
Conference_Titel :
Bioinformatics and Biomedicine (BIBM), 2011 IEEE International Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
978-1-4577-1799-4
DOI :
10.1109/BIBM.2011.37