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With the advances of medical imaging, accurate diagnosis has been significantly enhanced, especially when utilizing cross-modality imaging for complicated diagnoses such as the spine and cardiovascular system. However, cross modality image processing poses a challenge due to large amount of data generated. Computer Tomography (CT) and Magnetic Resonance Imaging (MRI) images, for example, have great capacity for screening, diagnosis, treatment and prevention of cardiac and spinal diseases. Gated cardiac MRI (Magnetic Resonance Imaging) or CT (Computed Tomography) sequences, for example, recorded from a complete cardiac cycle, contain 1500-5000 two dimensional images. The tools to handle these images are insufficient to best use the time of specialists such as radiologists and surgeons. . Development of an intelligent system to facilitate cross modality diagnosis and clinical monitoring will greatly increase specialist productivity and increase the information learned from each set of patient scans.
Manas Sharma
Victoria Hospital Imaging Associates
Life Sciences
Health and Related Sciences & Technology
Western University
Accelerate
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