Title :
Cohort Selection through Content-Based Image Retrieval: vfM A Case Study
Author :
Agarwal, Mohini ; Mostafa, J.
Author_Institution :
Lexical Inf., New Delhi, India
Abstract :
In this paper, we propose ViewFinder Medicine (vfM) for automatically identifying cohort classes for MRI scans. It involves predicting a cohort class for the heretofore unseen patient (and related images) and offering linkages to historical diagnosis data associated with the members of the predicted cohort class. The basic idea is to offer a relatively accurate cohort class for a new patient so that the cohort can be used as a baseline to understand current patient´s status and develop a treatment plan.
Keywords :
biomedical MRI; content-based retrieval; medical image processing; medicine; patient treatment; MRI scans; ViewFinder Medicine; cohort class prediction; cohort selection; content-based image retrieval; historical data diagnosis; patient treatment; vfM; Alzheimer´s disease; Image retrieval; Magnetic resonance imaging; Medical diagnostic imaging; Visualization;
Conference_Titel :
Healthcare Informatics, Imaging and Systems Biology (HISB), 2012 IEEE Second International Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4673-4803-4
DOI :
10.1109/HISB.2012.42
