student profile: Mr David Henry


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Thesis work

Thesis title: Marker-free motion tracking for motion-compensated brain imaging

Supervisors: Andre KYME , Roger FULTON

Thesis abstract:

One of the key challenges in brain imaging studies across different modalities such as positron emission tomography (PET) and magnetic resonance imaging (MRI) is dealing with subject motion. Even small movements of the head during acquisition can have a noticeable impact on image quality and quantitative MR and PET derived measurements. In the clinical environment, motion is a common problem, especially in studies of children and patients with head trauma, dementia or movement disorders. To mitigate movement, restraints are routinely used, but do not eliminate motion. Anaesthesia is often used when scanning young children, but brings the risk of an adverse reaction and considerably increases the complexity and cost of performing a scan. Due to these factors, motion correction methods in PET and MRI have been developed, with the potential to provide better patient outcomes, and reduce timing and personnel costs.
Motion correction techniques all require accurate characterisation of head motion within the scanner. Optical cameras in conjunction with computer vision algorithms are potentially an effective way of doing this. In present implementations however, motion is recorded with motion tracking cameras that observe reflective markers attached rigidly to the subject. The attachment of these markers can hinder workflow, with detachment of the markers or non-rigid motion of the markers relative to the head also being very real possibilities. A markerless method for tracking motion within a scanner would solve these problems.
This work aims to develop a practical, accurate, markerless motion tracking methodology to estimate head motion based on tracking native features of the face, which could then be incorporated into routine preclinical and clinical procedures in an efficient and seamless manner.

Selected publications

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Journals

  • Lee, D., Lee, D., Henry, D., Park, H., Han, B., Woo, D. (2018). Minimisation of Signal Intensity Differences in Distortion Correction Approaches of Brain Magnetic Resonance Diffusion Tensor Imaging. European Radiology, 28(10), 4314-4323. [More Information]

Conferences

  • Henry, D., Yao, Y., Fulton, R., Kyme, A. (2018). An Optimized Feature Detector for Markerless Motion Tracking in Motion-Compensated Neuroimaging. 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC 2017), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]

2018

  • Henry, D., Yao, Y., Fulton, R., Kyme, A. (2018). An Optimized Feature Detector for Markerless Motion Tracking in Motion-Compensated Neuroimaging. 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC 2017), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
  • Lee, D., Lee, D., Henry, D., Park, H., Han, B., Woo, D. (2018). Minimisation of Signal Intensity Differences in Distortion Correction Approaches of Brain Magnetic Resonance Diffusion Tensor Imaging. European Radiology, 28(10), 4314-4323. [More Information]

Note: This profile is for a student at the University of Sydney. Views presented here are not necessarily those of the University.