Our interests lie at the interface of Engineering and Life Sciences and the implementation of signal processing, statistics, mathematics and physics, to provide the next generation of diagnostic and novel therapeutic techniques. We are interested in the use of optical, acoustic and X-Ray technologies to illuminate a broad spectrum of mechanisms, which span from molecular imaging of the cell to quantitative anatomical imaging and in-vivo dosimetry
Computer Vision enhanced Advanced Cone Beam CT for Intraoperative Guidance.
Using our expertise with 4D-CT and a machine learning approach to motion modelling to improve current image-guided bronchoscopy guidance
Computer Vision assisted Collision Avoidance for Radiation Therapy.
Computer vision combined with a novel skin-mesh model allows patient specific ‘avatars’ to detect and track patient positioning in real-time 3D during treatment.
Computer vision assisted alignment for stereotactic body radiation therapy (SBRT).
We are developing a skeletal-pose computer vision model that correlates an external (skin mesh) with an internal (biomechanical) anatomy, thereby aligning the patient-specific model to a patient’s CT imaging.