Epithelial Cell Segmentation in Histological Images of Testicular Tissue Using Graph-Cut
2013 (English)In: Image Analysis and Processing – ICIAP 2013: Part II, 2013, 201-208 p.Conference paper (Refereed)
Computerized image processing has provided us with valuable tools for analyzing histology images. However, histology images are complex, and the algorithm which is developed for a data set may not work for a new and unseen data set. The preparation procedure of the tissue before imaging can significantly affect the resulting image. Even for the same staining method, factors like delayed fixation may alter the image quality. In this paper we face the challenging problem of designing a method that works on data sets with strongly varying quality. In environmental research, due to the distance between the site where the wild animals are caught and the laboratory, there is always a delay in fixation. Here we suggest a segmentation method based on the structural information of epithelium cell layer in testicular tissue. The cell nuclei are detected using the fast radial symmetry filter. A graph is constructed on top of the epithelial cells. Graph-cut optimization method is used to cut the links between cells of different tubules. The algorithm is tested on five different groups of animals. Group one is fixed immediately, three groups were left at room temperature for 18, 30 and 42 hours respectively, before fixation. Group five was frozen after 6 hours in room temperature and thawed. The suggested algorithm gives promising results for the whole data set.
Place, publisher, year, edition, pages
2013. 201-208 p.
, Lecture Notes in Computer Science, ISSN 0302-9743 ; 8157
Medical Image Processing
IdentifiersURN: urn:nbn:se:uu:diva-210299DOI: 10.1007/978-3-642-41184-7_21ISI: 000329811200021ISBN: 978-3-642-41183-0ISBN: 978-3-642-41184-7OAI: oai:DiVA.org:uu-210299DiVA: diva2:661891
17th International Conference on Image Analysis and Processing (ICIAP), Naples, Italy, September 9-13, 2013