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https://dx.doi.org/10.17192/z2...
Doctoral thesis . 2012
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Intraoperative Visualisierung multimodaler Daten in der Neurochirurgie

Authors: Egger, Jan;

Intraoperative Visualisierung multimodaler Daten in der Neurochirurgie

Abstract

Die Neurochirurgie als medizinisches Fachgebiet befasst sich mit der Erkennung und der (operativen) Behandlung von Pathologien des zentralen und peripheren Nervensystems. Dazu gehören unter anderem die operative Entfernung (Resektion) von Gehirntumoren und das Einsetzen von Neurostimulatoren bei Parkinson-patienten. In dieser Arbeit werden Beiträge zur computergestützten Behandlung von zerebralen Erkrankungen – Tumoren, Aneurysmen und Bewegungsstörungen – geleistet. Bei operativen Eingriffen zur Behandlung dieser zerebralen Erkrankungen muss eine exakte Planung vor der Operation erfolgen. Für die Volumen-bestimmung von zerebralen Erkrankungen wurde im Rahmen dieser Arbeit ein graphbasierter Segmentierungsalgorithmus für kugelförmige und elliptische Objekte entwickelt. Außerdem ist ein effizienter geometrischer Ansatz für die präoperative Planung von Zugangswegen bei der tiefen Hirnstimulation ausgearbeitet worden. Weiterhin wurde der Workflow zur multimodalen Integration von Stoffwechselvorgängen – erzeugt mit Hilfe der 3 Tesla Protonen MR-Spektroskopie (1H-MRS) – in ein neurochirurgisches Navigationssystem realisiert. Alle Verfahren werden in der vorliegenden Arbeit im Detail vorgestellt und anhand von Patientendaten evaluiert. Außerdem werden die klinischen Prototypen präsentiert, die auf den Verfahren aufbauen.

The medical field of neurosurgery addresses the diagnosis and (surgical) treatment of pathologies of the central and peripheral nervous system. The contributions of this thesis are in the area of computer aided treatment of cerebral diseases such as brain tumors, aneurysms, and movement disorders. Specifically, the methodology developed in this thesis is used during the pre-operative planning phase of brain tumor resection or deep brain stimulation for Parkinson’s disease. For the volume determination of cerebral diseases a graph-based segmentation algorithm for spherically- and elliptically-shaped objects has been developed in this thesis. In addition, an efficient geometrical approach for the preoperative planning of access paths for the deep brain stimulation has been elaborated. Furthermore, the workflow for the multimodal integration of metabolic processes – generated with 3 Tesla Proton MR-Spectroscopic Imaging (1H-MRS) – in a neurosurgical navigation system has been realized. All methods are introduced in detail in this thesis and are evaluated with real patient data from the clinical routine. Additionally, the clinical prototypes that are based upon these methods are presented.

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Germany
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Keywords

Bildsegmentierung, ddc:610, MRS, Hirnstimulation, Protonen-NMR-Spektroskopie, Neurochirurgie, Pituitary Adenoma, Hypophysenadenom, Medizin, Intrakranielles Aneurysma, Neurosurgery, 830, 610, DBS, Glioblastom, Medical sciences Medicine, GBM, Aneurysm, Segmentation, Medizin, Gesundheit

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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