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dc.contributor.advisorHannaford, Blake
dc.contributor.authorAghdasi, Nava
dc.date.accessioned2017-10-26T20:49:31Z
dc.date.available2017-10-26T20:49:31Z
dc.date.submitted2017-06
dc.identifier.otherAghdasi_washington_0250E_17646.pdf
dc.identifier.urihttp://hdl.handle.net/1773/40555
dc.descriptionThesis (Ph.D.)--University of Washington, 2017-06
dc.description.abstractDespite major technology advancements in image analysis, simulation and endoscopic pro- cedures, surgeons do not have access to simple, yet practical and efficient planning tools for complex operations in skull base surgery. Currently, in advanced medical centers that per- form these operations, all decisions about the surgical approach and treatment are made at tumor board meetings by reviewing 2D image slices in standard axial, coronal, and sagittal planes. For experienced skull base surgeons, finding the connection and correlation of pre-operative scans to intra-operative 3D anatomy is easy due to years of practice. Others must examine each slice of the pre-operative Computed Tomography (CT) scan, to answer whether the trajectory is crossing or how close the trajectory is to the critical anatomies. This make the process time-consuming and gives results which may not be optimal. In addition, surgeons often rely on their training, background, and experiences to select their approaches. So there is no quantitative information to support the decision process. This dissertation presents a method for assisting the surgeons in pre-operative planning by automatically providing the surgeons one or more optimal approaches by optimizing the cost function that is based on surgeon’s decision-making objectives. It is anticipated that using this approach, will transform a process that is subjective to a method that is coherent and quantifiable.
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.rightsnone
dc.subject
dc.subjectElectrical engineering
dc.subject.otherElectrical engineering
dc.titleComputer-Aided Pre-operative Planning System for Skull Base Surgery
dc.typeThesis
dc.embargo.termsOpen Access


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