Oyarzun Laura, Cristina ; Hofmann, Patrick ; Drechsler, Klaus ; Wesarg, Stefan (2019)
Automatic Detection of the Nasal Cavities and Paranasal Sinuses Using Deep Neural Networks.
ISBI'19 - 16th International Symposium on Biomedical Imaging. Venice, Italy (08.-11.04.2019)
doi: 10.1109/ISBI.2019.8759481
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
The nasal cavity and paranasal sinuses present large interpatient variabilities. Additional circumstances like for example, concha bullosa or nasal septum deviations complicate their segmentation. As in other areas of the body a previous multistructure detection could facilitate the segmentation task. In this paper an approach is proposed to individually detect all sinuses and the nasal cavity. For a better delimitation of their borders the use of an irregular polyhedron is proposed. For an accurate prediction the Darknet-19 deep neural network is used which combined with the You Only Look Once method has shown very promising results in other fields of computer vision. 57 CT scans were available of which 85% were used for training and the remaining 15% for validation.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2019 |
| Autor(en): | Oyarzun Laura, Cristina ; Hofmann, Patrick ; Drechsler, Klaus ; Wesarg, Stefan |
| Art des Eintrags: | Bibliographie |
| Titel: | Automatic Detection of the Nasal Cavities and Paranasal Sinuses Using Deep Neural Networks |
| Sprache: | Englisch |
| Publikationsjahr: | 2019 |
| Veranstaltungstitel: | ISBI'19 - 16th International Symposium on Biomedical Imaging |
| Veranstaltungsort: | Venice, Italy |
| Veranstaltungsdatum: | 08.-11.04.2019 |
| DOI: | 10.1109/ISBI.2019.8759481 |
| URL / URN: | https://doi.org/10.1109/ISBI.2019.8759481 |
| Kurzbeschreibung (Abstract): | The nasal cavity and paranasal sinuses present large interpatient variabilities. Additional circumstances like for example, concha bullosa or nasal septum deviations complicate their segmentation. As in other areas of the body a previous multistructure detection could facilitate the segmentation task. In this paper an approach is proposed to individually detect all sinuses and the nasal cavity. For a better delimitation of their borders the use of an irregular polyhedron is proposed. For an accurate prediction the Darknet-19 deep neural network is used which combined with the You Only Look Once method has shown very promising results in other fields of computer vision. 57 CT scans were available of which 85% were used for training and the remaining 15% for validation. |
| Freie Schlagworte: | Medical imaging, Medical image processing, Object detection |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Graphisch-Interaktive Systeme |
| Hinterlegungsdatum: | 10 Jul 2019 15:00 |
| Letzte Änderung: | 09 Apr 2020 14:01 |
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