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Segmentation of Risk Structures for Otologic Surgery using the Probabilistic Active Shape Model

Becker, Meike and Kirschner, Matthias and Sakas, Georgios (2014):
Segmentation of Risk Structures for Otologic Surgery using the Probabilistic Active Shape Model.
In: Proceedings of SPIE; 9036, SPIE Press, Bellingham, In: Medical Imaging 2014: Image-Guided Procedures, Robotic Interventions, and Modeling, pp. 90360O-1-90360O-7, DOI: 10.1117/12.2043411,
[Conference or Workshop Item]

Abstract

Our research project investigates a multi-port approach for minimally-invasive otologic surgery. For planning such a surgery, an accurate segmentation of the risk structures is crucial. However, the segmentation of these risk structures is a challenging task: The anatomical structures are very small and some have a complex shape, low contrast and vary both in shape and appearance. Therefore, prior knowledge is needed which is why we apply model-based approaches. In the present work, we use the Probabilistic Active Shape Model (PASM), which is a more flexible and specific variant of the Active Shape Model (ASM), to segment the following risk structures: cochlea, semicircular canals, facial nerve, chorda tympani, ossicles, internal auditory canal, external auditory canal and internal carotid artery. For the evaluation we trained and tested the algorithm on 42 computed tomography data sets using leave-one-out tests. Visual assessment of the results shows in general a good agreement of manual and algorithmic segmentations. Further, we achieve a good Average Symmetric Surface Distance while the maximum error is comparatively large due to low contrast at start and end points. Last, we compare the PASM to the standard ASM and show that the PASM leads to a higher accuracy.

Item Type: Conference or Workshop Item
Erschienen: 2014
Creators: Becker, Meike and Kirschner, Matthias and Sakas, Georgios
Title: Segmentation of Risk Structures for Otologic Surgery using the Probabilistic Active Shape Model
Language: English
Abstract:

Our research project investigates a multi-port approach for minimally-invasive otologic surgery. For planning such a surgery, an accurate segmentation of the risk structures is crucial. However, the segmentation of these risk structures is a challenging task: The anatomical structures are very small and some have a complex shape, low contrast and vary both in shape and appearance. Therefore, prior knowledge is needed which is why we apply model-based approaches. In the present work, we use the Probabilistic Active Shape Model (PASM), which is a more flexible and specific variant of the Active Shape Model (ASM), to segment the following risk structures: cochlea, semicircular canals, facial nerve, chorda tympani, ossicles, internal auditory canal, external auditory canal and internal carotid artery. For the evaluation we trained and tested the algorithm on 42 computed tomography data sets using leave-one-out tests. Visual assessment of the results shows in general a good agreement of manual and algorithmic segmentations. Further, we achieve a good Average Symmetric Surface Distance while the maximum error is comparatively large due to low contrast at start and end points. Last, we compare the PASM to the standard ASM and show that the PASM leads to a higher accuracy.

Series Name: Proceedings of SPIE; 9036
Publisher: SPIE Press, Bellingham
Uncontrolled Keywords: Forschungsgruppe Medical Computing (MECO), Operation planning, Computer assisted surgery, Minimally invasive surgery, Active shape models (ASM), Segmentation
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Interactive Graphics Systems
Event Title: Medical Imaging 2014: Image-Guided Procedures, Robotic Interventions, and Modeling
Date Deposited: 12 Nov 2018 11:16
DOI: 10.1117/12.2043411
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