Abstract
The problem of segmentation of Magnetic Resonance images into regions of uniform tissue density is posed as an optimization problem. A new objective function is defined and the resulting minimization problem is solved using Mean Field Annealing, a new technique which usually finds global minima in non-convex optimization problems, and performs particularly well on images. Noise sensitivity is evaluated by tests on synthetic images, and the technique is then applied to clinical images of a brain and a knee. The technique shows considerable promise as a method of quantitative change monitoring.
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© 1991 Springer-Verlag Berlin Heidelberg
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Snyder, W., Logenthiran, A., Santago, P., Link, K., Bilbro, G., Rajala, S. (1991). Segmentation of Magnetic Resonance images using mean field annealing. In: Colchester, A.C.F., Hawkes, D.J. (eds) Information Processing in Medical Imaging. IPMI 1991. Lecture Notes in Computer Science, vol 511. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0033755
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DOI: https://doi.org/10.1007/BFb0033755
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