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Inter-Scanner Harmonization of High Angular Resolution DW-MRI using Null Space Deep Learning by Nath, Vishwesh; Parvathaneni, Prasanna; Hansen, Colin B.; Hainline, Allison E.; Bermudez, Camilo; Remedios, Samuel; Blaber, Justin A.; Schilling, Kurt G.; Lyu, Ilwoo; Janve, Vaibhav; Gao, Yurui; Stepniewska, Iwona; Rogers, Baxter P.; Newton, Allen T.; Davis, L. Taylor; Luci, Jeff; Anderson, Adam W.; Landman, Bennett A. is a scholarly article available to read on EtoBox.

What is Inter-Scanner Harmonization of High Angular Resolution DW-MRI using Null Space Deep Learning about?

Diffusion-weighted magnetic resonance imaging (DW-MRI) allows for non-invasive imaging of the local fiber architecture of the human brain at a millimetric scale. Multiple classical approaches have been proposed to detect both single (e.g., tensors) and multiple (e.g., constrained spherical deconvolution, CSD) fiber population orientations per voxel. However, existing techniques generally exhibit low reproducibility across MRI scanners. Herein, we propose a data-driven tech-nique using a neural network design which exploits two categories of data. First, training data were acquired on three squirrel monkey brains using ex-vivo DW-MRI and histology of the brain. Second, repeated scans of human subjects were acquired on two different scanners to augment the learning of the network pro-posed. To use these data, we propose a new network architecture, the null space deep network (NSDN), to simultaneously learn on traditional observed/truth pairs (e.g., MRI-histology voxels) along with repeated observations without a known truth (e.g., scan-rescan MRI). The NSDN was tested on twenty percent of the histology voxels that were kept completely blind to the network. NSDN significantly improved

Author

Nath, Vishwesh; Parvathaneni, Prasanna; Hansen, Colin B.; Hainline, Allison E.; Bermudez, Camilo; Remedios, Samuel; Blaber, Justin A.; Schilling, Kurt G.; Lyu, Ilwoo; Janve, Vaibhav; Gao, Yurui; Stepniewska, Iwona; Rogers, Baxter P.; Newton, Allen T.; Davis, L. Taylor; Luci, Jeff; Anderson, Adam W.; Landman, Bennett A.

Published

2018

Language

EN