Jung, Florian ; Steger, Sebastian ; Knapp, Oliver ; Noll, Matthias ; Wesarg, Stefan (2014)
COSMO - Coupled Shape Model for Radiation Therapy Planning of Head and Neck Cancer.
Clinical Image-Based Procedures. Translational Research in Medical Imaging.
doi: 10.1007/978-3-319-13909-8_4
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
Radiation therapy plays a major role in head and neck cancer treatment. Segmentation of organs at risk prior to the radiation therapy helps to prevent the radiation beam from damaging healthy tissue, whereas a concentrated ray can target the cancerous regions. Unfortunately, the manual annotation of all relevant structures in the head and neck area is very time-consuming and existing atlas-based solutions don't provide sufficient segmentation accuracy. Therefore, we propose a coupled shape model (CoSMo) for the segmentation of key structures within the head and neck area. The model's adaptation to a test image is done with respect to the appearance of its items and the trained articulation space. 40 data sets labeled by clinicians containing 22 structures were used to build the CoSMo. Even on very challenging data sets with unnatural postures, which occur far more often than expected, the model adaptation algorithm succeeds. A first evaluation showed an average directed Hausdorff distance of 13.22mm and an average DICE overlap of 0.62. Furthermore, we review some of the challenges we encountered during the course of building our model from image data, taken from actual radiation therapy planing cases.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2014 |
| Autor(en): | Jung, Florian ; Steger, Sebastian ; Knapp, Oliver ; Noll, Matthias ; Wesarg, Stefan |
| Art des Eintrags: | Bibliographie |
| Titel: | COSMO - Coupled Shape Model for Radiation Therapy Planning of Head and Neck Cancer |
| Sprache: | Englisch |
| Publikationsjahr: | 2014 |
| Verlag: | Springer, Berlin, Heidelberg, New York |
| Reihe: | Lecture Notes in Computer Science (LNCS); 8680 |
| Veranstaltungstitel: | Clinical Image-Based Procedures. Translational Research in Medical Imaging |
| DOI: | 10.1007/978-3-319-13909-8_4 |
| Kurzbeschreibung (Abstract): | Radiation therapy plays a major role in head and neck cancer treatment. Segmentation of organs at risk prior to the radiation therapy helps to prevent the radiation beam from damaging healthy tissue, whereas a concentrated ray can target the cancerous regions. Unfortunately, the manual annotation of all relevant structures in the head and neck area is very time-consuming and existing atlas-based solutions don't provide sufficient segmentation accuracy. Therefore, we propose a coupled shape model (CoSMo) for the segmentation of key structures within the head and neck area. The model's adaptation to a test image is done with respect to the appearance of its items and the trained articulation space. 40 data sets labeled by clinicians containing 22 structures were used to build the CoSMo. Even on very challenging data sets with unnatural postures, which occur far more often than expected, the model adaptation algorithm succeeds. A first evaluation showed an average directed Hausdorff distance of 13.22mm and an average DICE overlap of 0.62. Furthermore, we review some of the challenges we encountered during the course of building our model from image data, taken from actual radiation therapy planing cases. |
| Freie Schlagworte: | Business Field: Visual decision support, Research Area: Human computer interaction (HCI), Automatic segmentation, Statistical shape models (SSM), Radiation therapies |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Graphisch-Interaktive Systeme |
| Hinterlegungsdatum: | 12 Nov 2018 11:16 |
| Letzte Änderung: | 12 Nov 2018 11:16 |
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