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Abstract #3150

Knowledge-Based Tractography Using Path Finding by Dynamic Programing

Muwei Li1, J. Tilak Ratnanather2, Yajing Zhang1, Hangyi Jiang1, Kenichi Oishi1, Michael I. Miller2, Susumu Mori1

1The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States; 2Center for Imaging Science, Johns Hopkins University, Baltimore, MD, United States

A knowledge-guided path-finding approach is proposed in this study. Combined with the automated brain segmentation, this approach can automatically generate 106 tracts based on our anatomical knowledge.This tool can be used to investigate tract-specific white matter anatomical states in various brain disorders.

Keywords

accuracy adults anatomical anatomy applied architecture atlas audience automated automatically available avoided benefit brain bundles certify clinicians combination combined combining comprehensive connected cross crossing dataset defined difficult diffusion disorders distance dynamic effectively enrich ensures error examination expect experimental faithfully false fibers finding finds five gaining generate generated guidance guide guided guiding healthy help highly improved in vivo incorporated insights inter investigate isotropic johns knowledge known lateral macroscopic major maps matrix medicine miller negative nominal partial participated path pathologies planar planning population positive predictions probabilistic probable programing programming projection projections radiological radiology reconstruct reconstructed reconstruction recovery reduce removal remove removed removing reproducibility researchers resolution retest reveal robustness scanned scanner school science segmentation segmented sense shot sixty slice slices space spin spinal stored streamline structure structures subject subjects surgery target tensor thesis tool tracking tract tracts trajectory transverse twenty twice understanding useful validation variability various volume warping white young