Paper
24 June 1998 Computer-aided diagnosis of pulmonary nodules based on shape analysis using thin-section CT images
Yoshiki Kawata, Noboru Niki, Hironobu Ohmatsu, Ryutaro Kakinuma, Kenji Eguchi, Masahiro Kaneko, Noriyuki Moriyama
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Abstract
Characterization of pulmonary nodules plays a significant role in the differential diagnosis of lung cancer. This paper presents a method to characterize the internal structure of small pulmonary nodules through curvature-based descriptor using thin-section CT images. The present work is a first step toward the segmentation of the 3D nodule images by using a 3D deformable surfaces approach. Second, a curvature-based representation of the pulmonary nodule is derived. Based on this representation, the pulmonary nodules are globally characterized through the shape spectra. This quantification emphasizes the difference between benign and malignant pulmonary nodules surroundings. Experiments on true 3D nodule images demonstrate good performance of our curvature based analysis technique.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yoshiki Kawata, Noboru Niki, Hironobu Ohmatsu, Ryutaro Kakinuma, Kenji Eguchi, Masahiro Kaneko, and Noriyuki Moriyama "Computer-aided diagnosis of pulmonary nodules based on shape analysis using thin-section CT images", Proc. SPIE 3338, Medical Imaging 1998: Image Processing, (24 June 1998); https://doi.org/10.1117/12.310833
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Cited by 1 scholarly publication.
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KEYWORDS
3D image processing

Lung

Image segmentation

Tin

Computed tomography

Chest

3D modeling

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