3D fuzzy liver tumor segmentation

Authors:
Paweł Badura;Ewa Pietka
Affiliations:
Faculty of Biomedical Engineering, Silesian University of Technology, Gliwice, Poland;Faculty of Biomedical Engineering, Silesian University of Technology, Gliwice, Poland
Venue:
ITIB'12 Proceedings of the Third international conference on Information Technologies in Biomedicine
Year:
2012

Citing 2
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Scale-Space and Edge Detection Using Anisotropic Diffusion

IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Image Processing

Digital Image Processing

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Abstract

A semi-automated method for segmentation of liver nodules in Computed Tomography studies is described in this paper. The application is part of a liver cancer computer-aided diagnosis (CAD) system. Its main body consists of the three-dimensional anisotropic diffusion filtering and the adaptive region growing, supported by the fuzzy inference system. Such a workflow enables elimination of noise within the image data, enhances nodule region boundaries, and cuts ,,segmentation leaks". The outcome is interactively presented to the physician with a possibility left to make manual adjustments. The system has been evaluated using a database of 17 abdominal Computed Tomography studies including 30 various liver nodules outlined by the radiologist, yielding 77% effectiveness (23 cases).