Title :
Biomedical Image Segmentation Based on Shape Stability
Author :
Li, Zhong ; Najarian, Kayvan
Author_Institution :
Univ. of North Carolina at Charlotte, Charlotte
fDate :
Sept. 16 2007-Oct. 19 2007
Abstract :
Biomedical image segmentation remains a challenging task mainly due to the weak edges and unevenly distributed color intensity of the objects and background. We present a novel unsupervised segmentation method to extract nuclei region from background. Our method, called shape stability algorithm, is a multiscale local adaptive threshold method. A modified weighted filter which serves as preprocessing method is also introduced. The presented algorithm is applied for segmentation of a number of Pap Smear images as well as bone marrow cell images. The results indicate the successful performance of the presented segmentation algorithm in segmentation of both Pap Smear and bone marrow samples.
Keywords :
feature extraction; image segmentation; medical image processing; biomedical image segmentation; bone marrow cell images; modified weighted filter; multiscale local adaptive threshold method; nuclei region; pap smear images; shape stability; unsupervised segmentation method; Biomedical imaging; Bones; Cities and towns; Computer science; Filters; Humans; Image segmentation; Shape; Stability; Visual system; Biomedical image processing; Image segmentation;
Conference_Titel :
Image Processing, 2007. ICIP 2007. IEEE International Conference on
Conference_Location :
San Antonio, TX
Print_ISBN :
978-1-4244-1437-6
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2007.4379576