Abstract #1045

In-vivo delineation of fine structures in the human brain using high resolution deep learning-powered chi-separation

Sooyeon Ji¹, Juhyung Park¹, Hyeong-Geol Shin^2,3, Minjun Kim¹, and Jongho Lee¹

¹Department of Electrical Computer Engineering, Seoul National University, Seoul, Korea, Republic of, ²Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, United States, ³F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States

Synopsis

Keywords: Susceptibility, Data ProcessingFine structures in the human brain are delineated in the positive and negative susceptibility maps reconstructed in less than 25 min of scan time. The reconstruction pipeline consists of four deep learning networks, each of which performs multi-echo denoising, QSM reconstruction, χ-separation, and super-resolution. The reconstructed maps delineate two laminar structures within globus pallidus, the fibers of internal capsule, and nigrosome structures in the substantia nigra.

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