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A curve evolution method for identifying weak edges with applications to the segmentation of magnetic resonance images of the knee

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5 Author(s)
Jincheng Pang ; Dept. of Electr. & Comput. Eng., Tufts Univ., Medford, MA, USA ; Miller, E. ; Driban, J. ; Tassinari, A.
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Motivated by the analysis of knee MRI data arising in the study of osteoarthritis, this paper presents a new active contour-based segmentation algorithm which combines external force field ideas and local region based methods in a consistent way. The approach not only has a large capture range as is common with curve evolution techniques based on static force fields such as the gradient vector flow (GVF) and vector field convolution (VFC) methods, but also can distinguish small details as local region based methods do. The feasibility of the new algorithm is demonstrated on both synthetic images as well as real knee MRI data where the goal is to identify the tibia and femur as part of a larger osteoarthritis image analysis problem.

Published in:

Biomedical Imaging: From Nano to Macro, 2011 IEEE International Symposium on

Date of Conference:

March 30 2011-April 2 2011