Share Email Print

Proceedings Paper

Pulmonary nodule segmentation in thoracic 3D CT images integrating boundary and region information
Author(s): Yoshiki Kawata; Noboru Niki; Hironobu Ohamatsu; Masahiko Kusumoto; Ryutaro Kakinuma; Kiyoshi Mori; Hiroyuki Nishiyama; Kenji Eguchi; Masahiro Kaneko; Noriyuki Moriyama
Format Member Price Non-Member Price
PDF $17.00 $21.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Accurately segmenting and quantifying pulmonary nodules structure is a key issue in three-dimensional (3-D) computer-aided diagnosis (CAD) schemes. This paper presents a segmentation approach of pulmonary nodules in thoracic 3-D images. This approach consists of two processes such as a pre-process for removing vessels attached and a surface deformation process. The pre-process is performed by 3-D gray-scale morphological operations. The surface deformation model used here integrates boundary and region information to deal with inappropriate position or size of an initial surface. This approach is derived through a 3-D extension of the geodesic active region model developed by Paragios and Deriche. First, in order to measure differences between the nodule and other regions a statistical analysis of the observed intensity is performed. Based on this analysis, the boundary and region information are represented by boundary and region likelihood, respectively. Second, an objective function is defined by integrating boundary and region-based segmentation modules. This integration aims at seeking surfaces that provide high boundary likelihood and high posterior segmentation probability. Finally, the deformable surface model is obtained by minimizing the objective function and, is implemented by a level set approach. We demonstrate an advantage of the proposed segmentation approach in comparison with the conventional deformable surface model using a practical 3-D pulmonary image.

Paper Details

Date Published: 15 May 2003
PDF: 11 pages
Proc. SPIE 5032, Medical Imaging 2003: Image Processing, (15 May 2003); doi: 10.1117/12.480664
Show Author Affiliations
Yoshiki Kawata, Univ. of Tokushima (Japan)
Noboru Niki, Univ. of Tokushima (Japan)
Hironobu Ohamatsu, National Cancer Ctr. Hospital East (Japan)
Masahiko Kusumoto, National Cancer Ctr. Hospital (Japan)
Ryutaro Kakinuma, National Cancer Ctr. Hospital East (Japan)
Kiyoshi Mori, National Tochigi Cancer Ctr. (Japan)
Hiroyuki Nishiyama, Social Health Insurance Medical Ctr. (Japan)
Kenji Eguchi, Univ. of Tokai (Japan)
Masahiro Kaneko, National Cancer Ctr. Hospital (Japan)
Noriyuki Moriyama, National Cancer Ctr. Hospital (Japan)

Published in SPIE Proceedings Vol. 5032:
Medical Imaging 2003: Image Processing
Milan Sonka; J. Michael Fitzpatrick, Editor(s)

© SPIE. Terms of Use
Back to Top