Title :
Improvement of texture based image segmentation algorithm for HE stained tissue samples
Author :
Windisch, Gergely ; Kozlovszky, Miklos
Author_Institution :
John von Neumann Fac. of Inf., Obuda Univ., Budapest, Hungary
Abstract :
Superpixel algorithms are becoming a widely used method for many computer vision applications, and it could be used as a basis of image segmentation for digital microscopy images of HE stained tissue samples. Research results show that among the many superpixel methods SLIC yields the best results when it comes to boundary adherence accuracy for normal images. In an effort to find out if it can be used for segmenting tissue images we have devised a benchmark to measure the performance of SLIC and tried improving the performance by careful tuning of the parameters to better fit SLIC to our special image processing needs.
Keywords :
biological tissues; computer vision; image segmentation; image texture; iterative methods; medical image processing; HE stained tissue samples; SLIC; computer vision; digital microscopy image; image processing; simple linear iterative clustering; superpixel algorithm; texture based image segmentation; Accuracy; Clustering algorithms; Gold; Image segmentation; Informatics; Shape; Standards; SLIC; Superpixels; tissue sample segmentation;
Conference_Titel :
Computational Intelligence and Informatics (CINTI), 2013 IEEE 14th International Symposium on
Conference_Location :
Budapest
Print_ISBN :
978-1-4799-0194-4
DOI :
10.1109/CINTI.2013.6705205
