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Methods for detecting and localizing surgical instruments in laparoscopic images are an important element of advanced robotic and computer-assisted interventions. Robotic joint encoders and sensors integrated or mounted on the instrument can provide information about the tool’s position, but this often has inaccuracy when transferred to the surgeon’s point of view. Vision sensors are currently a promising...
Intensity inhomogeneity is an important phenomenon affecting magnetic resonance imaging, which can greatly affect computational image analysis. Bias correction algorithms are commonly used, but are imperfect, leaving residual inhomogeneity that will usually differ in serial images of the same subject. This differential bias can have a detrimental effect on further processing, such as registration...
Segmenting the human brain from magnetic resonance images is a challenging task due to the convoluted shape of the cortex, noise, intensity non-uniformity and partial volume effects. We propose a new way to overcome part of the bias-variance tradeoff existent in any segmentation technique by locally varying the behaviour of the model. We developed a novel metric based on the Laplacian of the geodesic...
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