Nature Communications (Jun 2022)
Automated detection and segmentation of non-small cell lung cancer computed tomography images
- Sergey P. Primakov,
- Abdalla Ibrahim,
- Janita E. van Timmeren,
- Guangyao Wu,
- Simon A. Keek,
- Manon Beuque,
- Renée W. Y. Granzier,
- Elizaveta Lavrova,
- Madeleine Scrivener,
- Sebastian Sanduleanu,
- Esma Kayan,
- Iva Halilaj,
- Anouk Lenaers,
- Jianlin Wu,
- René Monshouwer,
- Xavier Geets,
- Hester A. Gietema,
- Lizza E. L. Hendriks,
- Olivier Morin,
- Arthur Jochems,
- Henry C. Woodruff,
- Philippe Lambin
Affiliations
- Sergey P. Primakov
- The D-Lab, Department of Precision Medicine, GROW- School for Oncology and Reproduction, Maastricht University
- Abdalla Ibrahim
- The D-Lab, Department of Precision Medicine, GROW- School for Oncology and Reproduction, Maastricht University
- Janita E. van Timmeren
- The D-Lab, Department of Precision Medicine, GROW- School for Oncology and Reproduction, Maastricht University
- Guangyao Wu
- The D-Lab, Department of Precision Medicine, GROW- School for Oncology and Reproduction, Maastricht University
- Simon A. Keek
- The D-Lab, Department of Precision Medicine, GROW- School for Oncology and Reproduction, Maastricht University
- Manon Beuque
- The D-Lab, Department of Precision Medicine, GROW- School for Oncology and Reproduction, Maastricht University
- Renée W. Y. Granzier
- Department of Surgery, GROW - School for Oncology and Reproduction, Maastricht University Medical Centre+
- Elizaveta Lavrova
- The D-Lab, Department of Precision Medicine, GROW- School for Oncology and Reproduction, Maastricht University
- Madeleine Scrivener
- Department of Radiation Oncology, Cliniques universitaires St-Luc
- Sebastian Sanduleanu
- The D-Lab, Department of Precision Medicine, GROW- School for Oncology and Reproduction, Maastricht University
- Esma Kayan
- The D-Lab, Department of Precision Medicine, GROW- School for Oncology and Reproduction, Maastricht University
- Iva Halilaj
- The D-Lab, Department of Precision Medicine, GROW- School for Oncology and Reproduction, Maastricht University
- Anouk Lenaers
- The D-Lab, Department of Precision Medicine, GROW- School for Oncology and Reproduction, Maastricht University
- Jianlin Wu
- Department of Radiology, Affiliated Zhongshan Hospital of Dalian University
- René Monshouwer
- Department of Radiation Oncology, Radboud University Medical Center
- Xavier Geets
- Department of Radiation Oncology, Cliniques universitaires St-Luc
- Hester A. Gietema
- Department of Radiology and Nuclear Medicine, GROW - School for Oncology and Reproduction, Maastricht University Medical Centre+
- Lizza E. L. Hendriks
- Department of Pulmonary Diseases, GROW - School for Oncology and Reproduction, Maastricht University Medical Center
- Olivier Morin
- Department of Radiation Oncology, University of California San Francisco, San Francisco
- Arthur Jochems
- The D-Lab, Department of Precision Medicine, GROW- School for Oncology and Reproduction, Maastricht University
- Henry C. Woodruff
- The D-Lab, Department of Precision Medicine, GROW- School for Oncology and Reproduction, Maastricht University
- Philippe Lambin
- The D-Lab, Department of Precision Medicine, GROW- School for Oncology and Reproduction, Maastricht University
- DOI
- https://doi.org/10.1038/s41467-022-30841-3
- Journal volume & issue
-
Vol. 13,
no. 1
pp. 1 – 12
Abstract
Correct interpretation of computer tomography (CT) scans is important for the correct assessment of a patient’s disease but can be subjective and timely. Here, the authors develop a system that can automatically segment the non-small cell lung cancer on CT images of patients and show in an in silico trial that the method was faster and more reproducible than clinicians.
