Title :
An Efficient Technique for Nuclei Segmentation Based on Ellipse Descriptor Analysis and Improved Seed Detection Algorithm
Author :
Hongming Xu ; Cheng Lu ; Mandal, Mrinal
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Alberta, Edmonton, AB, Canada
Abstract :
In this paper, we propose an efficient method for segmenting cell nuclei in the skin histopathological images. The proposed technique consists of four modules. First, it separates the nuclei regions from the background with an adaptive threshold technique. Next, an elliptical descriptor is used to detect the isolated nuclei with elliptical shapes. This descriptor classifies the nuclei regions based on two ellipticity parameters. Nuclei clumps and nuclei with irregular shapes are then localized by an improved seed detection technique based on voting in the eroded nuclei regions. Finally, undivided nuclei regions are segmented by a marked watershed algorithm. Experimental results on 114 different image patches indicate that the proposed technique provides a superior performance in nuclei detection and segmentation.
Keywords :
cellular biophysics; image segmentation; medical image processing; object detection; skin; adaptive threshold technique; cell nuclei segmentation; ellipse descriptor analysis; improved seed detection algorithm; marked watershed algorithm; nuclei clumps; skin histopathological images; Algorithm design and analysis; Clustering algorithms; Image segmentation; Informatics; Kernel; Shape; Skin; Ellipse descriptor; histopathological images; nuclei segmentation; seed detection; watershed algorithm;
Journal_Title :
Biomedical and Health Informatics, IEEE Journal of
DOI :
10.1109/JBHI.2013.2297030