Paper Info
Title
Segmentation of Bone with Region Based Active Contour Model in PD Weighted MR Images of Shoulder.
Abstract
Proton density (PD) weighted MR images present inhomogeneity problem, low signal to noise ratio (SNR) and cannot define bone borders clearly. Segmentation of PD weighted images is hampered with these properties of PD weighted images which even limit the visual inspection. The purpose of this study is to determine the effectiveness of segmentation of humeral head from axial PD MR images with active contour without edge (ACWE) model. We included 219 images from our original data set. We extended the use of speckle reducing anisotropic diffusion (SRAD) in PD MR images by estimation of standard deviation of noise (SDN) from ROI. To overcome the problem of initialization of the initial contour of these region based methods, the location of the initial contour was automatically determined with use of circular Hough transform. For comparison, signed pressure force (SPF), fuzzy C-means, and Gaussian mixture models were applied and segmentation results of all four methods were also compared with the manual segmentation results of an expert. Experimental results on our own database show promising results. This is the first study in the literature to segment normal and pathological humeral heads from PD weighted MR images.
Year
DOI
Venue
2015
10.1155/2015/754894
COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE
Field
DocType
Volume
Active contour model,Anisotropic diffusion,Computer vision,Speckle pattern,Computer science,Segmentation,Signal-to-noise ratio,Hough transform,Artificial intelligence,Initialization,Mixture model
Journal
2015
ISSN
Citations 
PageRank 
1748-670X
4
0.44
References 
Authors
22
3
Name
Order
Citations
PageRank
Aysun Sezer153.51
Hasan Basri Sezer252.50
Songul Albayrak3286.86