| Detecting white matter activity using conventional 3~Tesla fMRI : An evaluation of standard field strength and hemodynamic response functionPCHT Simon Fraser University, Fraser Health | Scientific Excellence - Advancing Knowledge | 2018-04-01 | |
| Developing brain vital signs: initial framework for monitoring brain function changes over time Fraser Health | Scientific Excellence - Advancing Knowledge | 2016-05-10 | Sujoy Ghosh-Hajra, Careesa Liu, Xiaowei Song, Shaun Fickling, Luke E Liu, Gabriela Pawlowski, Janelle K Jorgensen, Aynsley M Smith, Michal Schnaider-Beeri, Rudi Van Den Broek, Others |
| Long-term motor recovery after severe traumatic brain injury: beyond established limits Fraser Health | Scientific Excellence - Advancing Knowledge | 2016-09-21 | Ryan CN D'Arcy, D Stephen Lindsay, Xiaowei Song, Jodie R Gawryluk, Debbie Greene, Sujoy Ghosh-Hajra, Chantel Mayo, Lila Mandziuk, John Mathieson, Trevor Greene |
| DEVELOPING BRAIN VITAL SIGNS: INITIAL ASSESSMENTS ACROSS THE ADULT LIFE SPAN Fraser Health | Scientific Excellence - Advancing Knowledge | 2016-07-12 | Sujoy Ghosh-Hajra, Careesa Liu, Xiaowei Song, Shaun Fickling, Gabriela Pawlowski, Ryan CN D'Arcy |
| DEVELOPING AN ELECTROPHYSIOLOGICAL INDICATOR OF CONTEXTUAL ORIENTATION Fraser Health, Simon Fraser University | Scientific Excellence - Advancing Knowledge | 2016-07-12 | |
| BLINK-RELATED OSCILLATIONS AS POTENTIAL MEASURE OF DEFAULT MODE NETWORK (DMN) ACTIVITY IN ALZHEIMER’S DISEASE Fraser Health, Simon Fraser University | Scientific Excellence - Advancing Knowledge | 2016-07-12 | |
| Spontaneous Blinks Activate the Precuneus: Characterizing Blink-Related Oscillations Using Magnetoencephalography Fraser Health | Scientific Excellence - Advancing Knowledge | 2017-10-11 | Careesa Liu, Sujoy Ghosh-Hajra, Teresa PL Cheung, Xiaowei Song, Ryan CN D'Arcy |
| Brain vital signs demonstrate subconcussive impairment after a single season of ice hockey Fraser Health | Scientific Excellence - Advancing Knowledge | 2017-07-05 | Shaun D Fickling, Gabriela Pawlowski, Sujoy Ghosh-Hajra, Careesa Liu, Kyle Farrell, Janelle Jorgensen, Xiaowei Song, Aynsley M Smith, Ryan CN D'Arcy |
| Automation of CT-based haemorrhagic stroke assessment for improved clinical outcomes: study protocol and designHaemorrhagic stroke is of significant healthcare concern due to its association with high mortality and lasting impact on the survivors’ quality of life. Treatment decisions and clinical outcomes depend strongly on the size, spread and location of the haematoma. Non-contrast CT (NCCT) is the primary neuroimaging modality for haematoma assessment in haemorrhagic stroke diagnosis. Current procedures do not allow convenient NCCT-based haemorrhage volume calculation in clinical settings, while research-based approaches are yet to be tested for clinical utility; there is a demonstrated need for developing effective solutions. The project under review investigates the development of an automatic NCCT-based haematoma computation tool in support of accurate quantification of haematoma volumes.PCHT, AWNIH-DHC Simon Fraser University, Fraser Health | Scientific Excellence - Advancing Knowledge | 2021-05-24 | |
| A fast and fully-automated deep-learning approach for accurate hemorrhage segmentation and volume quantification in non-contrast whole-head CTThis research was aimed to develop novel methods that can improve precision and efficiency for hematoma segmentation and quantification in clinical applications for more effective stroke management. The three objectives are: 1) To develop an artificial intelligence method applying Convoluted Neural Network with Deep Supervision (CNN-DS), to fully automate segment and quantify ICH volume in CT images; 2) To evaluate the performance of the CNN-DS method in terms of accuracy and efficiency; 3) To compare the performance of this AI method to that of standard clinical evaluation and established machine learning (ML) based methods. Simon Fraser University, Fraser Health | Scientific Excellence - Advancing Knowledge | 2020-11-09 | |
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