Automated Image System for Scoring Changes in Quantitative Interstitial Lung Disease
Increased accuracy, sensitivity and consistency over visual scoringFacilitating drug evaluation process with more rapid assessment, lower cost, and shortened clinical trialsDe-noising technique for multi-center trials
Assess degree of interstitial lung diseaseRoutine monitoring of lung functionMonitor lung function in clinical trials
Professor Hyun Kim and colleagues from UCLA’s Department of Radiology have developed a new, fully-automated Computer Aided Diagnosis (CAD) scoring system that provides quantitative, repeatable, and retraceable measures of interstitial lung disease (ILD). The system provides increased sensitivity and consistency over visual scoring and can reliably estimate transitional changes in the levels of fibrotic reticulation, ground glass patterns, and normal, healthy patterns. The system also includes a de-nosing technique for a reduction in image variation from multi-center trials, which has been a significant improvement over existing quantitative scoring. Overall, this technology combines the de-nosing technique, robust feature selection, model classification and artificial intelligence of a computer-aid diagnosis system to calculate ILD quantitative metric.
State Of Development The system is implemented as computer software. This software can be run on individual medical imaging workstation or at the image acquisition device or on a reading workstation. The software could also be run on a centralized server or cluster servers. This software can also be accessed remotely (via the internet). Background Related Materials Tech ID/UC Case 23503/2013-078-0 Related Cases 2013-078-0
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