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We propose a new curvature-based method for correcting the segmented lung boundary. Our method consists of the following steps. First, the lungs are extracted from chest CT images by the automatic segmentation method. Second, the segmented lung contours are corrected by lung smoothing in each axial slice. Our scan line search provides an efficient contour(More)
We propose an automatic segmentation method for accurately identifying lung surfaces in chest CT images. Our method consists of three steps. First, lungs and airways are extracted by an inverse seeded region growing and connected component labeling. Second, trachea and large airways are delineated from the lungs by three-dimensional region growing. Third,(More)
We propose a novel method for the registration of 3D CT scans to 2D endoscopic images during the image-guided medialization laryngoplasty. This study aims to allow the surgeon to find the precise configuration of the implant and place it into the desired location by employing accurate registration methods of the 3D CT data to intra-operative patient and(More)
Surgeons use information from multiple sources when making surgical decisions. These include volumetric datasets (such as CT, PET, MRI, and their variants), 2D datasets (such as endoscopic videos), and vector-valued datasets (such as computer simulations). Presenting all the information to the user in an effective manner is a challenging problem. In this(More)
We propose an automatic segmentation and registration method that provides more efficient and robust matching of lung nodules in sequential chest computed tomography (CT) images. Our method consists of four steps. First, the lungs are extracted from chest CT images by the automatic segmentation method. Second, gross translational mismatch is corrected by(More)
PURPOSE This article proposes an accurate and fast deformable registration method between end-exhale and end-inhale CT scans that can handle large lung deformations and accelerate the registration process. METHODS The density correction method is applied to reduce the density difference between two CT scans due to respiration and gravity. The lungs are(More)
We propose a novel non-rigid registration method that computes the correspondences of two deformable surfaces using the cover tree. The aim is to find the correct correspondences without landmark selection and to reduce the computational complexity. The source surface S is initially aligned to the target surface T to generate a cover tree from the densely(More)
We propose a new method for correcting the segmented lung boundary in expiratory and inspiratory CT. First, the initial lung boundary is extracted by using density-based segmentation. Second, the scope for the boundary propagation is computed by generating and analyzing the gradient profiles with an adaptive length. The definition of the scope helps to(More)