%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