%0 Journal Article
	%A Abder-Rahman Ali and  Adélaïde Albouy-Kissi and  Manuel Grand-Brochier and  Viviane Ladan-Marcus and  Christine Hoeffl and  Claude Marcus and  Antoine Vacavant and  Jean-Yves Boire
	%D 2015
	%J International Journal of Computer and Information Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 103, 2015
	%T Liver Lesion Extraction with Fuzzy Thresholding in Contrast Enhanced Ultrasound Images
	%U https://publications.waset.org/pdf/10002261
	%V 103
	%X In this paper, we present a new segmentation approach
for focal liver lesions in contrast enhanced ultrasound imaging. This
approach, based on a two-cluster Fuzzy C-Means methodology,
considers type-II fuzzy sets to handle uncertainty due to the image
modality (presence of speckle noise, low contrast, etc.), and to
calculate the optimum inter-cluster threshold. Fine boundaries are
detected by a local recursive merging of ambiguous pixels. The
method has been tested on a representative database. Compared to
both Otsu and type-I Fuzzy C-Means techniques, the proposed
method significantly reduces the segmentation errors.
	%P 1730 - 1734