NDLI: MGRG-morphological gradient based 3D region growing algorithm for airway tree segmentation in image guided intervention therapy

Content Provider	IEEE Xplore Digital Library
Author	Dezhi Gao Xin Gao Caifang Ni Tao Zhang
Copyright Year	2011
Description	Author affiliation: Department of medical imaging, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, CHINA, 215163 (Xin Gao) \|\| Department of interventional radiology, First Affiliated Hospital of Soochow University, Suzhou, CHINA, 215163 (Caifang Ni) \|\| Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, China, 130000 (Dezhi Gao; Tao Zhang)
Abstract	Accurate surgical planning and guidance plays an important role in successful implementation of image guided intervention. In interventional lung cancer diagnosis and treatments, precise segmentation of airway trees from lung CT images provides crucial visualization for preoperative planning and intraoperative guidance to avoid major trachea injury. While 3D region growing can segment main the parts of an airway tree (trachea, left and right main bronchus, as well as bronchi), the method fails at bronchiole segmentation and is not robust. Mathematical morphology is an anatomical detective. In this paper, we propose a morphological gradient based region growing (MGRG) algorithm to overcome the intensity inhomogeneity, and improve the robustness of 3D region growing on extraction of bronchioles. The MGRG algorithm is validated using lung CT images, and results show that it is able to segment bronchioles, and outperforms the traditional region growing method on airway tree segmentation.
Starting Page	76
Ending Page	79
File Size	2223063
Page Count	4
File Format	PDF
ISBN	9781457700767
e-ISBN	9781457700774
DOI	10.1109/ISBB.2011.6107649
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-11-03
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Computed tomography Lungs Atmospheric modeling Manuals Three dimensional displays Biomedical imaging
Content Type	Text
Resource Type	Article

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