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Vector field analysis for surface registration in computer‐assisted ENT surgery

BACKGROUND: Manual paired‐point registration for navigated ENT‐surgery is prone to human errors; automatic surface registration is often caught in local minima. METHODS: Anatomical features of the human occiput are integrated into an algorithm for surface registration. A vector force field is define...

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Detalles Bibliográficos
Autores principales: Diakov, Georgi, Freysinger, Wolfgang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6590403/
https://www.ncbi.nlm.nih.gov/pubmed/30548164
http://dx.doi.org/10.1002/rcs.1977
Descripción
Sumario:BACKGROUND: Manual paired‐point registration for navigated ENT‐surgery is prone to human errors; automatic surface registration is often caught in local minima. METHODS: Anatomical features of the human occiput are integrated into an algorithm for surface registration. A vector force field is defined between the patient and operating room datasets; registration is facilitated through gradient‐based vector field analysis optimization of an energy function. The method is validated exemplarily on patient surface data provided by a mechanically positioned A‐mode ultrasound sensor. RESULTS: Successful registrations were achieved within the entire parameter space, as well as from positions of local minima that were found by the Gaussian fields algorithm for surface registration. Sub‐millimetric registration error was measured in clinically relevant anatomical areas on the anterior skull and within the generally accepted margin of 1.5 mm for the entire head. CONCLUSION: The satisfactory behavior of this approach potentially suggests a wider clinical integration.