Automatic malignancy estimation for pulmonary nodules from CT images

Mentl K, Saffoury R, Maier A (2018)

Publication Type: Conference contribution

Publication year: 2018

Journal

Informatik aktuell Gesellschaft für Informatik (GI)

Publisher: Springer Berlin Heidelberg

Pages Range: 13-

Conference Proceedings Title: Informatik aktuell

Event location: Erlangen, DEU

DOI: 10.1007/978-3-662-56537-7_12

Abstract

Early detection of lung cancer is crucial to increase the chance of cure. As lung cancer often manifests itself in the presence of malignant pulmonary nodules, the assessment of such is of high clinical importance. Lung cancer screening is primarily performed using diagnostic imaging modalities such as CT, while invasive methods such as biopsy are used as a last resort to confirm diagnosis.

Authors with CRIS profile

Katrin Mentl Lehrstuhl für Informatik 14 (Bild- und Sprachverarbeitung) (LME) Andreas Maier Lehrstuhl für Informatik 5 (Mustererkennung)

How to cite

APA:

Mentl, K., Saffoury, R., & Maier, A. (2018). Automatic malignancy estimation for pulmonary nodules from CT images. In Heinz Handels, Thomas Tolxdorff, Thomas M. Deserno, Klaus H. Maier-Hein, Andreas Maier, Christoph Palm (Eds.), Informatik aktuell (pp. 13-). Erlangen, DEU: Springer Berlin Heidelberg.

MLA:

Mentl, Katrin, Rimon Saffoury, and Andreas Maier. "Automatic malignancy estimation for pulmonary nodules from CT images." Proceedings of the Workshop on Bildverarbeitung fur die Medizin, 2018, Erlangen, DEU Ed. Heinz Handels, Thomas Tolxdorff, Thomas M. Deserno, Klaus H. Maier-Hein, Andreas Maier, Christoph Palm, Springer Berlin Heidelberg, 2018. 13-.

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