Abadi, E.* ; Sturgeon, G.M.* ; Agasthya, G.* ; Harrawood, B.* ; Hoeschen, C. ; Kapadia, A.* ; Segars, W.P.* ; Samei, E.*
     
 
    
        
Airways, vasculature, and interstitial tissue: Anatomically informed computational modeling of human lungs for virtual clinical trials.
    
    
        
    
    
        
        Proc. SPIE 10132:101321Q (2017)
    
    
    
		
		
			
				his study aimed to model virtual human lung phantoms including both non-parenchymal and parenchymal structures. Initial branches of the non-parenchymal structures (airways, arteries, and veins) were segmented from anatomical data in each lobe separately. A volume-filling branching algorithm was utilized to grow the higher generations of the airways and vessels to the level of terminal branches. The diameters of the airways and vessels were estimated using established relationships between flow rates and diameters. The parenchyma was modeled based on secondary pulmonary lobule units. Polyhedral shapes with variable sizes were modeled, and the borders were assigned to interlobular septa. A heterogeneous background was added inside these units using a non-parametric texture synthesis algorithm which was informed by a high-resolution CT lung specimen dataset. A voxelized based CT simulator was developed to create synthetic helical CT images of the phantom with different pitch values. Results showed the progressive degradation in depiction of lung details with increased pitch. Overall, the enhanced lung models combined with the XCAT phantoms prove to provide a powerful toolset to perform virtual clinical trials in the context of thoracic imaging. Such trials, not practical using clinical datasets or simplistic phantoms, can quantitatively evaluate and optimize advanced imaging techniques towards patient-based care.
			
			
				
			
		 
		
			
				
					
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        Publikationstyp
        Artikel: Journalartikel
    
 
    
        Dokumenttyp
        Wissenschaftlicher Artikel
    
 
    
        Typ der Hochschulschrift
        
    
 
    
        Herausgeber
        
    
    
        Schlagwörter
        Computational phantom, CT simulator, Lung modeling, XCAT phantoms
    
 
    
        Keywords plus
        
    
 
    
    
        Sprache
        englisch
    
 
    
        Veröffentlichungsjahr
        2017
    
 
    
        Prepublished im Jahr 
        
    
 
    
        HGF-Berichtsjahr
        2017
    
 
    
    
        ISSN (print) / ISBN
        0277-786X
    
 
    
        e-ISSN
        1996-756X
    
 
    
        ISBN
        
    
 
    
        Bandtitel
        
    
 
    
        Konferenztitel
        Medical Imaging 2017: Physics of Medical Imaging
    
 
	
        Konferzenzdatum
        11 February 2017
    
     
	
        Konferenzort
        Orlando, Florida, United States 
    
 
	
        Konferenzband
        
    
 
     
		
    
        Quellenangaben
        
	    Band: 10132,  
	    Heft: ,  
	    Seiten: ,  
	    Artikelnummer: 101321Q 
	    Supplement: ,  
	
    
 
  
        
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            SPIE
        
 
        
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        Begutachtungsstatus
        Peer reviewed
    
 
     
    
        POF Topic(s)
        30504 - Mechanisms of Genetic and Environmental Influences on Health and Disease
    
 
    
        Forschungsfeld(er)
        Radiation Sciences
    
 
    
        PSP-Element(e)
        G-501100-008
    
 
    
        Förderungen
        
    
 
    
        Copyright
        
    
 	
    
    
    
        Erfassungsdatum
        2017-03-20