NDLI: A New Segmentation Method for Lung HRCT Images

Content Provider	IEEE Xplore Digital Library
Author	Garnavi, R. Baraani-Dastjerdi, A. Moghaddam, H.A. Giti, M. Rad, A.A.
Copyright Year	2005
Description	Author affiliation: University of Isfahan (Garnavi, R.)
Abstract	Image segmentation plays a crucial role in many medical imaging applications by automating or facilitating the delineation of anatomical structures and other regions of interest. The aim of this paper is to develop an accurate and reliable method for segmentation of lung HRCT images using a pixel-based approach. The proposed method combines traditional concepts, such as global-threshold segmentation, mathematical morphology, edge detection and noise reduction, with new ideas, such as performing geometrical computations to achieve the defined ROIs. Two different approaches are proposed and tested on 100 computed-tomography images. Noise tolerance of the algorithm is calculated considering several parameters and objective criteria. In addition, the image segmentation results were visually validated by radiologists.
Starting Page	52
Ending Page	52
File Size	504028
Page Count	1
File Format	PDF
ISBN	0769524672
DOI	10.1109/DICTA.2005.5
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-12-06
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	IEEE/CSP
Subject Keyword	Image segmentation Lungs Image edge detection Noise reduction Morphology Anatomical structure Medical diagnostic imaging Pixel Biomedical imaging Diseases
Content Type	Text
Resource Type	Article

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