Automatic and interactive segmentation of pulmonary lobes and nodules in chest CT images
Publication year
2015Author(s)
Publisher
[S.l. : s.n.]
ISBN
9789462598409
Number of pages
152 p.
Annotation
Radboud Universiteit Nijmegen, 25 november 2015
Promotores : Ginneken, B. van, Hahn, H.K.
Co-promotores : Rikxoort, E.M. van, Kuhnigk Fraunhofer, J.M.
Publication type
Dissertation

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Organization
Medical Imaging
Subject
Radboudumc 9: Rare cancers RIHS: Radboud Institute for Health SciencesAbstract
Lung diseases such as lung cancer and chronic obstructive pulmonary disease (COPD) are a main cause of mortality and morbidity. Early detection and determining the right therapy can improve the chances of cure. Although the human eye is very good at qualitatively judging diseases, quantification of disease status and progression is much better done by computers. To be able to perform any automatic quantification, delineation (i.e. segmentation) of the structures of interest in an image is a prerequisite.
Lassen has developed algorithms for automatic and interactive segmentation of pulmonary lobes and nodules in CT scans. In challenges and on large sets of publicly available data, the good performance of the methods could be demonstrated. The results were comparable to complete manual segmentations by experts, but with two advantages. First, the proposed approaches are fast and require none or only little user interaction. Second, using the proposed automated methods improves the reproducibility and prevents varying results by different clinicians.
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- Academic publications [202736]
- Dissertations [12239]
- Electronic publications [100853]
- Faculty of Medical Sciences [79998]
- Open Access publications [69573]
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