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Please use this identifier to cite or link to this item: http://hdl.handle.net/1813/7358
Title: Segmentation of Pulmonary Nodule Images Using Total VariationMinimization
Authors: Coleman, Thomas F.
Li, Yuying
Mariano, Adrian
Keywords: computer science
technical report
Issue Date: Sep-1998
Publisher: Cornell University
Citation: http://techreports.library.cornell.edu:8081/Dienst/UI/1.0/Display/cul.cs/TR98-1704
Abstract: Total variation minimization has edge preserving and enhancing properties which make it suitable for image segmentation. We present Image Simplification, a new formulation and algo rithm for image segmentation. We illustrate the edge enhancing properties of total variation minimization in a discrete setting by giving exact solutions to the problem for piecewise constant functions in the presence of noise. In this case, edges can be exactly recovered if the noise is sufficiently small. After optimization, segmentation is completed using edge detection. We find that our image segmentation approach yields good results when applied to the segmentation of pulmonary nodules.
URI: http://hdl.handle.net/1813/7358
Appears in Collections:Computer Science Technical Reports

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