Lung Nodule Segmentation Using Mathematical Morphology

Ming Zhi Qu; Gui Rong Weng

doi:10.4028/www.scientific.net/AMM.58-60.1378

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 58-60Lung Nodule Segmentation Using Mathematical...

Lung Nodule Segmentation Using Mathematical Morphology

Abstract:

Contemporary computed tomography (CT) technology offers the better potential of screening for the early detection of lung cancer than the traditional x-ray chest radiographs. In order to help improve radiologists’ diagnostic performance and efficiency, many researchers propose to develop computer-aided detection and diagnosis (CAD) system for the detection and characterization of lung nodules depicted on CT images and to evaluate its potentially clinical utility in assisting radiologists. Based on review of computer-aided detection and diagnosis of lung nodules using CT at home and abroad in recent years, this paper presented a new algorithm that achieves an automated way for applying multi-scale nodule enhancement, mathematical morphology and morphological Segmentation.

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Periodical:

Applied Mechanics and Materials (Volumes 58-60)

Pages:

1378-1383

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.58-60.1378

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Online since:

June 2011

Authors:

Ming Zhi Qu, Gui Rong Weng

Keywords:

Computer Aided Design (CAD), Lung Nodule, Mathematical Morphology

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