3D segmentation of non-isolated pulmonary nodules in high resolution CT images

Xiangwei Zhang; Geoffrey McLennan; Eric A. Hoffman; Milan Sonka

doi:10.1117/12.594938

29 April 2005 3D segmentation of non-isolated pulmonary nodules in high resolution CT images

Xiangwei Zhang, Geoffrey McLennan, Eric A. Hoffman, Milan Sonka

Proceedings Volume 5747, Medical Imaging 2005: Image Processing; (2005) https://doi.org/10.1117/12.594938
Event: Medical Imaging, 2005, San Diego, California, United States

Abstract

The purpose of this study is to develop a computer-aided diagnosis (CAD) system to segment small size non-isolated pulmonary nodules in high resolution helical CT scans. A new automated method of segmenting juxtapleural nodules was proposed, in which a quadric surface fitting procedure was used to create a boundary between a juxtapleural nodule and its neighboring pleural surface. Experiments on some real CT nodule data showed that this method was able to yield results that reflect the local shape of the pleural surface. Additionally, a scheme based on parametrically deformable geometric model was developed to deal with the problem of segmenting nodules attached to vessels. A vessel segment connected to a nodule was modeled using superquadrics with parametric deformations. The boundary between a vascularized nodule and the attached vessels can be recovered by finding the deformed superquadrics which approximates the vessels. Gradient descent scheme was utilized to optimize the parameters of the superquadrics. Simple experiments on synthetic data showed this scheme is promising.

Citation Download Citation

Xiangwei Zhang, Geoffrey McLennan, Eric A. Hoffman, and Milan Sonka "3D segmentation of non-isolated pulmonary nodules in high resolution CT images", Proc. SPIE 5747, Medical Imaging 2005: Image Processing, (29 April 2005); https://doi.org/10.1117/12.594938

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