Mohammadreza Nazem-Zadeh1, Kourosh
Jafari-Khouzani2, Abbas Babajani-Fermi2, Siamak
Pourabdollah Nejad-Davarani1, Hamid Soltanian-Zadeh2,3,
Quan Jiang1
1Neurology, Henry Ford
Hospital, Detroit, MI, United States; 2Diagnostic Radiology, Henry
Ford Hospital, Detroit, MI, United States; 3Control &
Intelligent Processing Center of Excellence, School of Electrical &
Computer Engineering, University of Tehran, Tehran, Iran
Using High angular resolution diffusion imaging (HARDI), the fiber orientation distribution function (ODF) on the unit sphere is calculated and used to extract the principal diffusion directions (PDDs). Fast and accurate estimation of PDDs is a prerequisite for tracking algorithms that deal with fiber crossings. In this paper, a clustering approach to estimate PDDs is proposed which is an extension of fuzzy c-means clustering developed for orientation coordinates of points on a sphere. Experimental results illustrate that the proposed clustering algorithm is more accurate, more resistant to noise, and faster than the techniques currently being utilized.
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