Details
| Original language | English |
|---|---|
| Title of host publication | Medical Imaging 2015 |
| Subtitle of host publication | Image Processing |
| Editors | Martin A. Styner, Sebastien Ourselin |
| Publisher | SPIE |
| ISBN (electronic) | 9781628415032 |
| Publication status | Published - 2015 |
| Event | Medical Imaging 2015: Image Processing - Orlando, United States Duration: 24 Feb 2015 → 26 Feb 2015 |
Publication series
| Name | Progress in Biomedical Optics and Imaging - Proceedings of SPIE |
|---|---|
| Volume | 9413 |
| ISSN (Print) | 1605-7422 |
Abstract
Planning and analyzing of surgical interventions are often based on computer models derived from computed tomography images of the patient. In the field of cochlear implant insertion the modeling of several structures of the inner ear is needed. One structure is the overall helical shape of the cochlea itself. In this paper we analyze the cochlea by applying statistical shape models with medial representation. The cochlea is considered as tubular structure. A model representing the skeleton of training data and an atomic composition of the structure is built. We reduce the representation to a linear chain of atoms. As result a compact discrete model is possible. It is demonstrated how to place the atoms and build up their correspondence through a population of training data. The outcome of the applied representation is discussed in terms of impact on automated segmentation algorithms and known advantages of medial models are revisited.
Keywords
- active shape models, cochlea, inner ear, segmentation
ASJC Scopus subject areas
- Materials Science(all)
- Electronic, Optical and Magnetic Materials
- Materials Science(all)
- Biomaterials
- Physics and Astronomy(all)
- Atomic and Molecular Physics, and Optics
- Medicine(all)
- Radiology Nuclear Medicine and imaging
Cite this
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Medical Imaging 2015: Image Processing. ed. / Martin A. Styner; Sebastien Ourselin. SPIE, 2015. 941345 (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 9413).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Cochlear shape description and analyzing via medial models
AU - Gaa, Johannes
AU - Kahrs, Lüder A.
AU - Müller, Samuel
AU - Majdani, Omid
AU - Ortmaier, Tobias
PY - 2015
Y1 - 2015
N2 - Planning and analyzing of surgical interventions are often based on computer models derived from computed tomography images of the patient. In the field of cochlear implant insertion the modeling of several structures of the inner ear is needed. One structure is the overall helical shape of the cochlea itself. In this paper we analyze the cochlea by applying statistical shape models with medial representation. The cochlea is considered as tubular structure. A model representing the skeleton of training data and an atomic composition of the structure is built. We reduce the representation to a linear chain of atoms. As result a compact discrete model is possible. It is demonstrated how to place the atoms and build up their correspondence through a population of training data. The outcome of the applied representation is discussed in terms of impact on automated segmentation algorithms and known advantages of medial models are revisited.
AB - Planning and analyzing of surgical interventions are often based on computer models derived from computed tomography images of the patient. In the field of cochlear implant insertion the modeling of several structures of the inner ear is needed. One structure is the overall helical shape of the cochlea itself. In this paper we analyze the cochlea by applying statistical shape models with medial representation. The cochlea is considered as tubular structure. A model representing the skeleton of training data and an atomic composition of the structure is built. We reduce the representation to a linear chain of atoms. As result a compact discrete model is possible. It is demonstrated how to place the atoms and build up their correspondence through a population of training data. The outcome of the applied representation is discussed in terms of impact on automated segmentation algorithms and known advantages of medial models are revisited.
KW - active shape models
KW - cochlea
KW - inner ear
KW - segmentation
UR - http://www.scopus.com/inward/record.url?scp=84943396401&partnerID=8YFLogxK
U2 - 10.1117/12.2082033
DO - 10.1117/12.2082033
M3 - Conference contribution
AN - SCOPUS:84943396401
T3 - Progress in Biomedical Optics and Imaging - Proceedings of SPIE
BT - Medical Imaging 2015
A2 - Styner, Martin A.
A2 - Ourselin, Sebastien
PB - SPIE
T2 - Medical Imaging 2015: Image Processing
Y2 - 24 February 2015 through 26 February 2015
ER -