Performance and clinical impact of machine learning based lung nodule detection using vessel suppression in melanoma patients

Article ID	Journal	Published Year	Pages	File Type
10097312	Clinical Imaging	2018	6 Pages	PDF

Abstract

Machine learning based vessel suppression led to the detection of significantly more lung nodules in melanoma patients. Radiological follow-up recommendations were altered in 30% of the patients. However, all lung nodules turned out to be non-malignant on follow-up.

Keywords

AJCC ROI SOP GGO Computer-aided detection computed tomography Tomography Melanoma Standard operating procedures Lung CAD Metastasis region of interest Neoplasm Hounsfield units American Joint Committee on Cancer Machine learning

Related Topics

Health Sciences Medicine and Dentistry Radiology and Imaging

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Performance and clinical impact of machine learning based lung nodule detection using vessel suppression in melanoma patients

Authors

Joel Aissa, Benedikt Michael Schaarschmidt, Janina Below, Oliver Th. Bethge, Judith Böven, Lino Morris Sawicki, Norman-Philipp Hoff, Patric Kröpil, Gerald Antoch, Johannes Boos,