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  4. Using Photon-Counting CT Images for Lung Nodule Classification
 
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2025
Conference Paper
Title

Using Photon-Counting CT Images for Lung Nodule Classification

Abstract
An automatic classification of the malignancy of lung nodules in computed tomography (CT) scans can support early detection of lung cancer, which is crucial for the treatment success. The novel photon-counting CT (PCCT) technology enables high image quality with a low radiation dose and provides additional spectral information. This research focuses on whether PCCT scans offer a benefit in the automatic classification of lung nodules. Establishing a dataset of PCCT images poses several challenges, such as the extraction of annotations or the data imbalance.
Author(s)
Basso, Leonie
Hannover Medical School
Ahmadi, Zahra
Hannover Medical School
Oeltze-Jafra, Steffen
Hannover Medical School
Petersen, Eike
Fraunhofer-Institut für Digitale Medizin MEVIS  
Shin, Hoen Oh
Hannover Medical School
Schenk, Andrea
Fraunhofer-Institut für Digitale Medizin MEVIS  
Mainwork
WSDM 2025, Eighteenth ACM International Conference on Web Search and Data Mining. Proceedings  
Conference
International Conference on Web Search and Data Mining 2025  
DOI
10.1145/3701551.3708810
Language
English
Fraunhofer-Institut für Digitale Medizin MEVIS  
Keyword(s)
  • Lung Nodules

  • Medical Image Processing

  • Photon-counting CT

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