Literature DB >> 19635691

Intervertebral disc segmentation and volumetric reconstruction from peripheral quantitative computed tomography imaging.

Alexander Wong1, Akshaya Mishra, Justin Yates, Paul Fieguth, David A Clausi, Jack P Callaghan.   

Abstract

An automatic system for segmenting and constructing volumetric representations of excised intervertebral discs from peripheral quantitative computed tomography (PQCT) imagery is presented. The system is designed to allow for automatic quantitative analysis of progressive herniation damage to the intervertebral discs under flexion/extension motions combined with a compressive load. Automatic segmentation and volumetric reconstruction of intervertebral disc from PQCT imagery is a very challenging problem due to factors such as streak artifacts and unclear material density separation between contrasted intervertebral disc and surrounding bone in the PQCT imagery, as well as the formation of multiple contrasted regions under axial scans. To address these factors, a novel multiscale level set approach based on the Mumford-Shah energy functional in iterative bilateral scale space is employed to segment the intervertebral disc regions from the PQCT imagery. A Delaunay triangulation is then performed based on the set of points associated with the intervertebral disc regions to construct the volumetric representation of the intervertebral disc. Experimental results show that the proposed system achieves segmentation and volumetric reconstructions of intervertebral discs with mean absolute distance error below 0.8 mm when compared to ground truth measurements. The proposed system is currently in operational use as a visualization tool for studying progressive intervertebral disc damage.

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Year:  2009        PMID: 19635691     DOI: 10.1109/TBME.2009.2027225

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  1 in total

1.  Automatic framework for extraction and characterization of wetting front propagation using tomographic image sequences of water infiltrated soils.

Authors:  Dionicio Vasquez; Jacob Scharcanski; Alexander Wong
Journal:  PLoS One       Date:  2015-01-20       Impact factor: 3.240

  1 in total

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