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Abstract #0703

An Improved Probabilistic Atlas of the Dentate Nucleus Derived with QSM

Naying He1,2, Jason Langley3, Daniel E Huddleston4, Huawei Ling5, Hongmin Xu5, Chunlei Liu6, Yong Zhang7, Fuhua Yan8, and Xiaoping Hu9,10

1Radiology, Ruijin Hospital,Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China, 2Center for Advanced Neuroimaging, University of California, Riverside, Riverside, CA, United States, 3Center for Advanced NeuroImaging, University of California Riverside, Riverside, CA, United States, 4the department of Neurology, Emory School of Medicine, Atlanta, GA, United States, 5Radiology, Ruijin Hospital,Shanghai Jiao Tong University School of Medicine, 6Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, United States, 7MR Research, GE Healthcare, Shanghai, People's Republic of China, 8Radiology, Ruijin Hospital,Shanghai Jiao Tong University School of Medicine, shanghai, People's Republic of China, 9Center for Advanced Neuroimaging, University of California, Riverside, CA, United States, 10Bioengineering, University of California, Riverside, Riverside, CA, United States

Prior dentate nucleus (DN) atlases were derived using T1-, T2*- or susceptibility-weighted imaging. Accurate delineation of the DN boundary is difficult in these images. We present an atlas derived from quantitative susceptibility maps, which exhibit better contrast between DN and surrounding cerebellum tissue. An improved delineation of DN boundaries was achieved, resulting in increased maximum overlap in our DN atlas as compared to previously published results. We anticipate the atlas to be used in a variety of imaging applications ranging from functional imaging of DN to measuring DN iron deposition arising from disease.

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