Publications by authors named "R P Custer"

Increased waste clearance in the brain is thought to occur most readily during late-stage sleep (stage N3). Sleep deprivation disrupts time spent in deeper sleep stages, fragmenting the clearance process. Here, we have utilized the publicly available Stockholm Sleepy Brain Study to investigate whether various sleep-related measures are associated with changes in perivascular space (PVS) volume fraction following a late-night short-sleep experiment.

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Purpose: To develop a weakly supervised 3D perivascular spaces (PVS) segmentation model that combines the filter-based image processing algorithm and the convolutional neural network.

Methods: We present a weakly supervised learning method for PVS segmentation by combing a rule-based image processing approach Frangi filter with a canonical deep learning algorithm Unet using conditional random field theory. The weighted cross entropy loss function and the training patch selection were implemented for the optimization and to alleviate the class imbalance issue.

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Background: Traumatic brain injury (TBI) can alter brain structure and lead to onset of persistent neuropsychological symptoms. This study investigates the relationship between brain injury and psychological distress after mild TBI using multimodal magnetic resonance imaging.

Methods: A total of 89 patients with mild TBI from the TRACK-TBI (Transforming Research and Clinical Knowledge in Traumatic Brain Injury) pilot study were included.

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The recent Food and Drug Administration approval of 7 T MR imaging scanners for clinical use has introduced the possibility to study the brain not only in physiologic but also in pathologic conditions at ultrahigh field (UHF). Because UHF MR imaging offers higher signal-to-noise ratio and spatial resolution compared with lower field clinical scanners, the benefits of UHF MR imaging are particularly evident for imaging small anatomic structures, such as the cerebral perivascular spaces (PVS). In this article, the authors describe the application of UHF MR imaging for the investigation of PVS.

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