6 June 2000 Tracking interval changes of pulmonary nodules using a sequence of three-dimensional thoracic images
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Abstract
We are developing a computerized approach to characterize pulmonary nodules through quantitative analysis between sequential 3-D thoracic images. In this approach the registration procedure of sequential 3-D pulmonary images consisted of two transformation steps: the rigid transformation step between two sequential 3-D thoracic CT images and the affine transformation step between two sequential region-of-interest (ROI) images including the pulmonary nodule. In both transformation step, the normalized mutual information was used as a voxel-based similarity measure. After the registration procedure, the 3-D pulmonary nodule image was segmented from the ROI image by a deformable surface method. The curvatures of each voxel in the nodule were computed directly from the gray-level 3-D image. Through curvatures a local description of the lesion was obtained by using shape index, curvedness, and CT value. Based on this local description of the nodule, the evolution of geometrical parameters was tracked through the time interval. Additionally, to characterize globally the evolution of the local description, the shape and the curvedness spectra were introduced. The interval changes of the lesion were traced in the feature spaces. The application results of our method to the sequence of 3-D thoracic images demonstrated that the interval changes of pulmonary nodules could be made visible.
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Yoshiki Kawata, Yoshiki Kawata, Noboru Niki, Noboru Niki, Hironobu Omatsu, Hironobu Omatsu, Masahiko Kusumoto, Masahiko Kusumoto, Ryutaro Kakinuma, Ryutaro Kakinuma, Kiyoshi Mori, Kiyoshi Mori, Hiroyuki Nishiyama, Hiroyuki Nishiyama, Kenji Eguchi, Kenji Eguchi, Masahiro Kaneko, Masahiro Kaneko, Noriyuki Moriyama, Noriyuki Moriyama, } "Tracking interval changes of pulmonary nodules using a sequence of three-dimensional thoracic images", Proc. SPIE 3979, Medical Imaging 2000: Image Processing, (6 June 2000); doi: 10.1117/12.387723; https://doi.org/10.1117/12.387723
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