Title :
New tensorial morphological gradients in DTI image segmentation algorithm
Author :
Tao Lin ; Xiao-Yun Liu ; Xiang-Fen Zhang ; Yan Ma ; Zhe-Xing Liu
Author_Institution :
Coll. of Inf., Mech. & Electr. Eng., SHNU, Shanghai, China
Abstract :
Calculating morphological gradient is the key step of watershed algorithm. In this article, new tensorial similarity morphological gradient is defined based on the eight neighborhoods, and new tensor anisotropy morphological gradients are put forward, which are then used in the watershed segmentation framework to segment DTI image. The results of the segmentation experiments on the corpus callosum show that: Compared to other tensor anisotropy morphological gradients based watershed segmentation methods, the one based on newly proposed tensor anisotropy morphological gradients can more quickly and accurately position and depict the segmentation outline of the image, which can also better protect the edge information of the important region.
Keywords :
gradient methods; image segmentation; DTI image segmentation algorithm; calculating morphological gradient; corpus callosum; edge information; tensor anisotropy morphological gradients; tensorial morphological gradients; tensorial similarity morphological gradient; watershed algorithm; watershed segmentation framework; watershed segmentation methods; Anisotropic magnetoresistance; Biomedical imaging; Diffusion tensor imaging; Eigenvalues and eigenfunctions; Image edge detection; Image segmentation; Tensile stress; Corpus callosum; Diffusion tensor imaging; Morphological gradient; Tensor similarity; Watershed algorithm;
Conference_Titel :
Wavelet Active Media Technology and Information Processing (ICCWAMTIP), 2014 11th International Computer Conference on
Print_ISBN :
978-1-4799-7207-4
DOI :
10.1109/ICCWAMTIP.2014.7073414