title: Automatic detection of subsolid pulmonary nodules in thoracic computed tomography images.
abstract: Subsolid pulmonary nodules occur less often than solid pulmonary nodules, but show a much higher malignancy rate. Therefore, accurate detection of this type of pulmonary nodules is crucial. In this work, a computer-aided detection (CAD) system for subsolid nodules in computed tomography images is presented and evaluated on a large data set from a multi-center lung cancer screening trial. The paper describes the different components of the CAD system and presents experiments to optimize the performance of the proposed CAD system. A rich set of 128 features is defined for subsolid nodule candidates. In addition to previously used intensity, shape and texture features, a novel set of context features is introduced. Experiments show that these features significantly improve the classification performance. Optimization and training of the CAD system is performed on a large training set from one site of a lung cancer screening trial. Performance analysis on an independent test from another site of the trial shows that the proposed system reaches a sensitivity of 80% at an average of only 1.0 false positive detections per scan. A retrospective analysis of the output of the CAD system by an experienced thoracic radiologist shows that the CAD system is able to find subsolid nodules which were not contained in the screening database.
authors.affiliation: Diagnostic Image Analysis Group, Department of Radiology, Radboud University Medical Center, Nijmegen, The Netherlands; Fraunhofer MEVIS, Bremen, Germany. Electronic address: colin.jacobs@radboudumc.nl.
authors.forename: Colin
authors.initials: C
authors.lastname: Jacobs
authors.affiliation: Diagnostic Image Analysis Group, Department of Radiology, Radboud University Medical Center, Nijmegen, The Netherlands; Fraunhofer MEVIS, Bremen, Germany.
authors.forename: Eva M
authors.initials: EM
authors.lastname: van Rikxoort
authors.affiliation: MeVis Medical Solutions AG, Bremen, Germany.
authors.forename: Thorsten
authors.initials: T
authors.lastname: Twellmann
authors.affiliation: Department of Radiology, Utrecht University Medical Center, Utrecht, The Netherlands; Department of Radiology, Haarlemmer Kennemer Gasthuis, Haarlem, The Netherlands.
authors.forename: Ernst Th
authors.initials: ET
authors.lastname: Scholten
authors.affiliation: Department of Radiology, Utrecht University Medical Center, Utrecht, The Netherlands.
authors.forename: Pim A
authors.initials: PA
authors.lastname: de Jong
authors.affiliation: Fraunhofer MEVIS, Bremen, Germany.
authors.forename: Jan-Martin
authors.initials: JM
authors.lastname: Kuhnigk
authors.affiliation: Department of Radiology, University Medical Center Groningen, Groningen, The Netherlands.
authors.forename: Matthijs
authors.initials: M
authors.lastname: Oudkerk
authors.affiliation: Department of Public Health, Erasmus Medical Center, Rotterdam, The Netherlands.
authors.forename: Harry J
authors.initials: HJ
authors.lastname: de Koning
authors.affiliation: Department of Radiology, Radboud University Medical Center, Nijmegen, The Netherlands.
authors.forename: Mathias
authors.initials: M
authors.lastname: Prokop
authors.affiliation: Meander Medical Centre, Amersfoort, The Netherlands; Diagnostic Image Analysis Group, Department of Radiology, Radboud University Medical Center, Nijmegen, The Netherlands.
authors.forename: Cornelia
authors.initials: C
authors.lastname: Schaefer-Prokop
authors.affiliation: Diagnostic Image Analysis Group, Department of Radiology, Radboud University Medical Center, Nijmegen, The Netherlands; Fraunhofer MEVIS, Bremen, Germany.
authors.forename: Bram
authors.initials: B
authors.lastname: van Ginneken
mesh_terms: D000465:Algorithms; D055088:Early Detection of Cancer; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D010363:Pattern Recognition, Automated; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D003074:Solitary Pulmonary Nodule / Q000000981:diagnostic imaging*; D014057:Tomography, X-Ray Computed / Q000379:methods*
keywords: Computed tomography (CT); Computer aided detection (CAD); Lung cancer; Lung nodule; Subsolid nodule