Thorup, Signe Strann

Denne afhandling omhandler automatisk analyse af kraniofaciale billeder mht. forandringer forårsaget af vækst og kirurgiske indgreb, variation mellem individer og estimering af det intrakranielle volumen. Metoderne bidrager til forståelsen af specikke kraniofaciale misdannelser, og fungerer som værktøj ifm. detaljerede analyser til kliniske og forskningsbaserede formal.De fleste anvendelser i afhandlingen beror pa ikke-rigid billedregistrering, hvor et billede transformeres over i et andet billedes koordinatsystem. Denne transformering resulterer i et deformationsfelt, som beskriver den anatomiske korrespondance mellem de to billeder. For at uddybe dette nærmere blev et atlas af den gennemsnitlige anatomi konstrueret. Ikke-rigid billed-registrering blev herefter brugt til automatisk at transformere billeddata fra et individ til atlassets koordinatsystem.I denne proces blev den anatomiske viden indbygget i atlasset overført til individet, for pa den måde at generere et personligt atlas. Den anatomiske viden i atlasser kan f.eks. vre specifikke anatomiske deles placering eller vigtige referencepunkter til brug i f.eks. operationsplanlægning, operationsevaluering eller populationsstudier. Korrespondancerne muliggør adskillelige analyser f.eks.kvantificering af vækst, variation mellem individer osv. Udover billedregistrering blev en volumetrisk segmenterings metode baseret pa graph cuts udviklet og brugt til estimering af det intrakranielle volumen hos patienter. Graph cut er en hurtig metode til segmentering såfremt en passende graf er sat op.I denne afhandling blev tre forskellige kraniofaciale misdannelser undersgt: Læbe-ganespalte, enkeltsig coronal synostose og Crouzon syndrom. Ved brug af de fremsatte metoder blev variation undersgt i høj detaljeringsgrad for spædbørn med læbe-ganespalte, korrespondance blev etableret mellem billedet optaget hhv. fr og efter kirurgisk lukning af læbespalten hos spædbørn med læbeganespalte. Det intrakranielle volume blev estimeret hos spædbørn med enkeltsig coronal synostose. Endvidere blev kraniofaciale vækstmønstre kvantificeret i en musemodel af Crouzon syndrom.The topic of this thesis is automatic analysis of craniofacial images with respect to changes due to growth and surgery, inter-subject variation and intracranial volume estimation. The methods proposed contribute to the knowledge about specific craniofacial anomalies, as well as provide a tool for detailed analyses for clinical and research purposes.Most of the applications in this thesis rely on non-rigid image registration by the means of warping one image into the coordinate system of another image. This warping results in a deformation field that describes the anatomical correspondence between the two images. To elaborate further: a computational atlas of the average anatomy was constructed. Using non-rigid registration, image data from a subject is automatically transformed into the coordinate space of the atlas. In this process, all knowledge built into the atlas is transferred to the subject, thus creating a personalized atlas. The knowledge built into the atlas is e.g. location of anatomical regions and landmarks of importance to surgery planning and evaluation or population studies. With these correspondences, various analyses could be carried out e.g. quantification of growth, inter-subject variation etc. Besides image registration, a volumetric segmentation method using graph cuts was developed and applied for intracranial volume estimation. Graph cut is a fast method for segmentation utilizing a suitable graph. Three different craniofacial anomalies were examined in this thesis: Cleft lip and palate, unicoronal synostosis, and Crouzon syndrome. Using the proposed methods, highly detailed variation was assessed for cleft lip and palate, correspondence between images obtained before and after lip repair was established for cleft lip and palate, the intracranial volume was estimated for infants with unicoronal synostosis, and nally, craniofacial growth patterns were quantied for Crouzon syndrome in a mouse model

Online Research Database In Technology

Modeling of Craniofacial Anatomy, Variation, and Growth

http://orbit.dtu.dk/ws/files/60524240/phd290_Thorup_SS.pdf

Modeling of Craniofacial Anatomy, Variation, and Growth

Abstract

Similar works

Full text

Available Versions

Online Research Database In Technology