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Object Identification via Ensemble Image Segmentations

An image segmentation technique using a collection of potential segmentations to provide better accuracy of object identification

Background

Chest computed tomography (CT)-scans are being used to diagnose both suspected and known COVID-19 cases in patients. CT scans produce digital images that are processed using image segmentation software which identifies and then classifies regions of interest within the images. Traditional segmentation is ineffective and unreliable due to source data typically being noisy, cluttered, or corrupted.

Technology Overview

Lawrence Livermore National Laboratory scientists have developed a new strategy that combines classification with randomized segmentation ensembles to significantly improve the overall performance of image segmentation systems. Instead of relying on a single best-guess segmentation, a large collection of potential segmentations are used providing better accuracy and reliability. This patented technique can be used on any host of digital images such

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