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Titlebook: Medical Content-Based Retrieval for Clinical Decision Support; Second MICCAI Intern Henning Müller,Hayit Greenspan,Tanveer Syeda-Mahmo Conf

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René Donner,Sebastian Haas,Andreas Burner,Markus Holzer,Horst Bischof,Georg Langsurers now supply open design MRI systems that operate predominately at field strengths below 0.5 T. Issues regarding field strength remain controversial and largely unresolved. This includes diagnostic yield, imaging sequences, manufacturer variation, diagnostic accuracy, adequacy of image quality,
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1980s [1]. The poor tolerance profile of these metallic ions was, however, mentioned as a critical factor, and it was therefore unclear whether administering paramagnetic substances such as ions of the transitional elements and lanthanides or nitroxyl compounds would be feasible for clinical diagno
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Histology Image Indexing Using a Non-negative Semantic Embeddings semantic. Evaluation of the proposed method is carried out by comparing it with other strategies, showing a remarkable image search improvement since the proposed approach effectively exploits the image semantic relationships.
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A Discriminative Distance Learning–Based CBIR Framework for Characterization of Indeterminate Liver on the quality and relevance of the retrieval results has been measured and is discussed for three different set–ups. A comparison study with the commonly used canonical Euclidean distance is presented and discussed as well.
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Computer–Aided Diagnosis of Pigmented Skin Dermoscopic Imagesor and texture information, as well as local and global parameters that try to reflect structures used in medical diagnosis. The learning and classification stage is performed using SVM with polynomial kernels. The classification delivered accuracy of 98.57% with a true positive rate of 0.991% and a false positive rate of 0.019%.
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