Semi-supervised prostate cancer segmentation with multispectral MRI

Authors:
Yusuf Artan;Masoom A. Haider;Deanne L. Langei;Imam Samil Yetik
Affiliations:
Medical Imaging Research Center, Illinois Institute of Technology, Chicago, IL;Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital, Ontario, Canada;Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital, Ontario, Canada and Institute of Medical Science, University of Toronto, Ontario, Canada;Medical Imaging Research Center, Illinois Institute of Technology, Chicago, IL
Venue:
ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
Year:
2010

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Abstract

Prostate cancer is one of the leading causes of cancer related death for men in the United States. Recently, multispectral magnetic resonance imaging (MRI) has emerged as a promising noninvasive method for the localization of prostate cancer alternative to transrectal ultrasound (TRUS). This paper develops a semi-supervised method for prostate cancer localization using multispectral MRl. Patient-specific contrast can be utilized in this method for improved performance. We also propose to use an anisotropic filtering scheme to suppress the noise in the images. Using multispectral MR images, we demonstrate the effectiveness of this algorithm by testing it on real data sets and compare it to the results of a fully-automated method as well as to the earlier results. Both visual and quantitative comparisons are provided, illlustrating the success of the proposed method.