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dc.contributor.advisorSuki, Belaen_US
dc.contributor.authorYuan, Ziwenen_US
dc.date.accessioned2021-06-02T18:47:27Z
dc.date.available2021-06-02T18:47:27Z
dc.date.issued2021
dc.identifier.urihttps://hdl.handle.net/2144/42626
dc.description.abstractEmphysema is a progressive disease characterized by irreversible tissue destruction and airspace enlargement, which manifest as low attenuation area (LAA) on CT images. Previous studies have shown that inflammation, protease imbalance, extracellular matrix remodeling and mechanical forces are collectively playing a role in the progression of emphysema. Elastic spring network models have been applied to investigate the pathogenesis of emphysema from the mechanical perspective. However, all existing models include random removal of springs to mimic the initial locations of LAA clusters from which emphysema progression is initiated. This approach is generically lacking patient specificity of CT scans that precisely reflect the location of LAA in an emphysematous lung. The aim of this work is to develop a novel approach that provides an optimal spring network representation of emphysematous lungs based on apparent density in CT images. The results suggest that the personalized elastic spring network can be used to predict the propagation of structural destruction during emphysema progression. Thus, our approach has the potential to predict disease progression that should be verified by clinical dataen_US
dc.language.isoen_US
dc.subjectBiomedical engineeringen_US
dc.subjectElastic spring networken_US
dc.subjectEmphysemaen_US
dc.titleConsistent spring network representation of emphysematous lung from CT imagesen_US
dc.typeThesis/Dissertationen_US
dc.date.updated2021-05-19T22:09:19Z
etd.degree.nameMaster of Scienceen_US
etd.degree.levelmastersen_US
etd.degree.disciplineBiomedical Engineeringen_US
etd.degree.grantorBoston Universityen_US
dc.identifier.orcid0000-0001-7816-7095


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