title: Performance evaluation of simple linear iterative clustering algorithm on medical image processing.
abstract: Simple Linear Iterative Clustering (SLIC) algorithm is increasingly applied to different kinds of image processing because of its excellent perceptually meaningful characteristics. In order to better meet the needs of medical image processing and provide technical reference for SLIC on the application of medical image segmentation, two indicators of boundary accuracy and superpixel uniformity are introduced with other indicators to systematically analyze the performance of SLIC algorithm, compared with Normalized cuts and Turbopixels algorithm. The extensive experimental results show that SLIC is faster and less sensitive to the image type and the setting superpixel number than other similar algorithms such as Turbopixels and Normalized cuts algorithms. And it also has a great benefit to the boundary recall, the robustness of fuzzy boundary, the setting superpixel size and the segmentation performance on medical image segmentation.
authors.affiliation: College of Science and Technology, Shandong University of Traditional Chinese Medicine, Jinan 250355, China.
authors.forename: Jinyu
authors.initials: J
authors.lastname: Cong
authors.affiliation: College of Science and Technology, Shandong University of Traditional Chinese Medicine, Jinan 250355, China.
authors.forename: Benzheng
authors.initials: B
authors.lastname: Wei
authors.affiliation: School of Computer Science and Technology, Shandong University, Jinan 250100, China.
authors.forename: Yilong
authors.initials: Y
authors.lastname: Yin
authors.affiliation: School of Computer Science and Technology, Shandong University, Jinan 250100, China.
authors.forename: Xiaoming
authors.initials: X
authors.lastname: Xi
authors.affiliation: School of Medicine, University of Pennsylvania, Philadelphia 19104, USA.
authors.forename: Yuanjie
authors.initials: Y
authors.lastname: Zheng
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D016014:Linear Models; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted
keywords: Medical image; SLIC; image segmentation; performance evaluation; superpixels