Title :
A 3D segmentation framework for an accurate extraction of the spongy and cortical bones from the MRI data
Author :
Moghadas, Seyed Mehdi ; Won-Sook Lee
Author_Institution :
Sch. of Electr. Eng. & Comput. Sci., Univ. of Ottawa, Ottawa, ON, Canada
Abstract :
In this paper we proposed a new framework for obtaining the spongy and cortical bones from the MRI data. The method focuses on the accurate extraction of the edges of the target tissues, which is the main drawback of the previous works. This framework first limits the searching area for the bone voxels from the whole data to a small strip around the edges of the cortical and spongy bones then applies a very accurate segmentation on the searching area using the newly developed deformable kernel Fuzzy C-Means (DKFCM) algorithm, which is proposed in this paper. Comparing the results of this work with previous segmentation methods on a testing dataset consisting of 10,485,760 voxels demonstrates the superiority of the proposed method especially on the edges of the spongy and cortical bone.
Keywords :
biomedical MRI; bone; edge detection; feature extraction; fuzzy set theory; image segmentation; medical image processing; 3D segmentation framework; DKFCM; MRI data; accurate extraction; bone voxels; cortical bones; deformable kernel Fuzzy C-Means algorithm; edge extraction; spongy bones; tissues; Bones; Conferences; Image edge detection; Image segmentation; Kernel; Magnetic resonance imaging; Noise; Cortical bone; Fuzzy C-Means; MRI; Segmentation; Spongy bone;
Conference_Titel :
Bioinformatics and Biomedicine (BIBM), 2013 IEEE International Conference on
Conference_Location :
Shanghai
DOI :
10.1109/BIBM.2013.6732583