DocumentCode :
3649796
Title :
Analyzing Tubular Tissue in Histopathological Thin Sections
Author :
A. Fakhrzadeh;E. Sporndly-Nees;L. Holm;C. L. Luengo Hendriks
Author_Institution :
Center for Image Anal., Swedish Univ. of Agric. Sci., Uppsala, Sweden
fYear :
2012
Firstpage :
1
Lastpage :
6
Abstract :
We propose a method for automatic segmentation of tubules in the stained thin sections of various tissue types. Tubules consist of one or more layers of cells surrounding a cavity. The segmented tubules can be used to study the morphology of the tissue. Some research has been done to automatically estimate the density of tubules. To the best of our knowledge, no one has been able to, fully automatically, segment the whole tubule. Usually the border between tubules is subtle and appears broken in a straight-forward segmentation. Here we suggest delineating these borders using the geodesic distance transform. We apply this method on images of Periodic Acid Shiffs (PAS) stained thin sections of testicular tissue, delineating 89% of the tubules correctly.
Keywords :
"Image segmentation","Level set","Image color analysis","Transforms","Morphology","Glands","Image edge detection"
Publisher :
ieee
Conference_Titel :
Digital Image Computing Techniques and Applications (DICTA), 2012 International Conference on
Print_ISBN :
978-1-4673-2180-8
Type :
conf
DOI :
10.1109/DICTA.2012.6411735
Filename :
6411735
Link To Document :
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