Valvular diseases may affect one or more of the cardiac valves, which may need to be replaced or restored for effective treatment. The surgical procedure can be guided by a patient-specific and dynamic model containing information complementary to the 2D/3D static images of the valves. To this end, in this study a novel automated model-free aortic valve segmentation method is presented, and its performance is evaluated against expert annotations over conventional contrast enhanced ECG-gated multislice CT data of the aortic valve at its closed position. Detailed evaluation of the proposed method in 19 real cases revealed an encouraging performance of 3D region growing over Hessian based approach but also demonstrated the complexity of the problem.
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We present a case with imaging artefacts on mammography and Magnetic Resonance Imaging (MRI) caused by iron oxide particles. After being diagnosed with the medullary cancer of the breast, the female patient had a breast conserving surgery on right breast. Iron oxide particleswere used for the detection of the sentinel lymph node during operation. On follow ups, a de novo density on mammography, which wasinitially thought to be a new tumour, was found. MR images proved that the lesion is an artefact caused by iron oxide accumulation. Ouraim in this case study is to underline and discuss the imaging artefacts caused by these particles and raise awareness.
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