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  5. Segmentation of Pulmonary Nodule Images Using Total Variation Minimization

Segmentation of Pulmonary Nodule Images Using Total Variation Minimization

File(s)
2003-284.pdf (430.1 KB)
Permanent Link(s)
https://hdl.handle.net/1813/5458
Collections
Cornell Theory Center Technical Reports
Author
Coleman, Thomas F.
Li, Yuying
Mariano, Adriano
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 algorithm 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.

Date Issued
2003-01-22
Publisher
Cornell University
Keywords
theory center
Previously Published as
http://techreports.library.cornell.edu:8081/Dienst/UI/1.0/Display/cul.tc/2003-284
Type
technical report

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