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Automatic Sentinel Lymph Node Localization in Head and Neck Cancer Using a Coupled Shape Model Algorithm

Jung, Florian ; Medea, Biebl-Rydlo ; Daisne, Jean-François ; Wesarg, Stefan (2017)
Automatic Sentinel Lymph Node Localization in Head and Neck Cancer Using a Coupled Shape Model Algorithm.
CARE 2017, CLIP 2017. Québec, Kanada (14 September 2017)
doi: 10.1007/978-3-319-67543-5_13
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

The localization and analysis of the sentinel lymph node for patients diagnosed with cancer, has significant influence on the prognosis, outcome and treatment of the disease. We present a fully automatic approach to localize the sentinel lymph node and additional active nodes and determine their lymph node level on SPECT-CT data. This is a crucial prerequisite for the planning of radiation therapy or a surgical neck dissection. Our approach was evaluated on 17 lymph nodes. The detection rate of the lymph nodes was 94%; and 88% of the lymph nodes were correctly assigned to their corresponding lymph node level. The proposed algorithm targets a very important topic in clinical practice. The first results are already very promising. The next step has to be the evaluation on a larger data set.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2017
Autor(en): Jung, Florian ; Medea, Biebl-Rydlo ; Daisne, Jean-François ; Wesarg, Stefan
Art des Eintrags: Bibliographie
Titel: Automatic Sentinel Lymph Node Localization in Head and Neck Cancer Using a Coupled Shape Model Algorithm
Sprache: Englisch
Publikationsjahr: 2017
Ort: Berlin
Verlag: Springer
Buchtitel: Computer Assisted and Robotic Endoscopy and Clinical Image-Based Procedures
Veranstaltungstitel: CARE 2017, CLIP 2017
Veranstaltungsort: Québec, Kanada
Veranstaltungsdatum: 14 September 2017
DOI: 10.1007/978-3-319-67543-5_13
URL / URN: https://doi.org/10.1007/978-3-319-67543-5_13
Kurzbeschreibung (Abstract):

The localization and analysis of the sentinel lymph node for patients diagnosed with cancer, has significant influence on the prognosis, outcome and treatment of the disease. We present a fully automatic approach to localize the sentinel lymph node and additional active nodes and determine their lymph node level on SPECT-CT data. This is a crucial prerequisite for the planning of radiation therapy or a surgical neck dissection. Our approach was evaluated on 17 lymph nodes. The detection rate of the lymph nodes was 94%; and 88% of the lymph nodes were correctly assigned to their corresponding lymph node level. The proposed algorithm targets a very important topic in clinical practice. The first results are already very promising. The next step has to be the evaluation on a larger data set.

Freie Schlagworte: Medical applications, Medical diagnosis, Oral cancer
Zusätzliche Informationen:

Lecture Notes in Computer Science, vol 10550

Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Graphisch-Interaktive Systeme
Hinterlegungsdatum: 04 Mai 2020 08:44
Letzte Änderung: 04 Mai 2020 08:44
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