Multi-Atlas Segmentation of the Facial Nerve

Multi-Atlas Segmentation of the Facial Nerve

Medical image segmentation is an important step to identify the shape and position of patient anatomy prior to surgical simulation, surgical rehearsal, and surgical planning. It is crucial that the facial nerve (FN) is segmented accurately as damage to this nerve can severely impact facial expressio...

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Bibliographic Details
Main Author: Gare, Bradley M
Format: Dissertation
Language:English
Published: ProQuest Dissertations & Theses 01-01-2019
Subjects:
Algorithms
Audiology
Cochlear implants
Computer science
Deafness
Dentistry
Disability studies
Drilling
Ears & hearing
Electrodes
Hearing aids
Hearing loss
Medical imaging
Medical personnel
Medicine
Otolaryngology
Registration
Surgeons
Surgery
Tomography
Transplants & implants
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Summary:Medical image segmentation is an important step to identify the shape and position of patient anatomy prior to surgical simulation, surgical rehearsal, and surgical planning. It is crucial that the facial nerve (FN) is segmented accurately as damage to this nerve can severely impact facial expression, speech, and taste. Manual segmentation provides accurate results but is time-consuming and labor-intensive; semi-automatic methods of segmentation are more feasible in a clinical setting and can provide accurate results with minimal user involvement.The objective of this work was to create a novel, open-source, multi-atlas based segmentation algorithm of the entire FN requiring minimal user intervention.Twenty-eight temporal bones were segmented producing an average Dice metric of 0.76 and an average Hausdorff distance of 0.17 mm which is similar to previously published algorithms. These results indicate that this segmentation approach can accurately segment the FN and greatly reduce time spent with manual segmentation.
ISBN:9798845487698