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Several distinct medical imaging perspectives such as cutting-edge imaging methods, data analysis, better correlation with neurocognitive function, as well as detailed examples and summaries of disease monitoring, may help convey the methodological, technical, and developmental information of medical imaging principles and applications. The aim of this book is to provide beginners and experts in the medical imaging field with general pictures and detailed descriptions of imaging principles and clinical applications. With forefront applications and up-to-date analytical methods, this book will hopefully capture the interests of colleagues in the medical imaging research field. Precise illustrations and thorough reviews in many research topics such as neuroimaging quantification and correlation, as well as cancer diagnoses, are the advantages of this book.

Imaging systems.

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Quatrième de couverture : "Cet ouvrage reprend le contenu des 89es journées d'enseignement post-universitaire de l'hôpital Saint-Antoine. Depuis plus d'une quinzaine d'années, nous pratiquons cette formule d'enseignement faite de dossiers radiologiques volontairement non spécialisés, mais issus de l'ensemble des spécialités d'imagerie médicale. C'est la réussite de ces journées qui nous a incités à publier nos cas cliniques qui sont présentés sous la forme d'une brève histoire clinique, d'une iconographie significative et de quelques questions orientant la démarche diagnostique. Dans la réponse, est présenté un développement concernant la pathologie en question. Ce type d'ouvrage, peu courant en France, est extrêmement répandu Outre-Atlantique. Ce sont les classiques "Teaching files". Il s'agit effectivement de façon variée, attrayante et ludique, d'augmenter, de perfectionner ou de réviser ses connaissances."

Diagnostic Imaging

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Ultrasonic imaging.

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Ultrasonic imaging.

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Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis covers the most current advances on how to apply classification techniques to a wide variety of clinical applications that are appropriate for researchers and biomedical engineers in the areas of machine learning, deep learning, data analysis, data management and computer-aided diagnosis (CAD) systems design. The book covers several complex image classification problems using pattern recognition methods, including Artificial Neural Networks (ANN), Support Vector Machines (SVM), Bayesian Networks (BN) and deep learning. Further, numerous data mining techniques are discussed, as they have proven to be good classifiers for medical images. Examines the methodology of classification of medical images that covers the taxonomy of both supervised and unsupervised models, algorithms, applications and challenges Discusses recent advances in Artificial Neural Networks, machine learning, and deep learning in clinical applications Introduces several techniques for medical image processing and analysis for CAD systems design

Diagnostic imaging. --- Clinical imaging --- Imaging, Diagnostic --- Medical diagnostic imaging --- Medical imaging --- Noninvasive medical imaging --- Diagnosis, Noninvasive --- Imaging systems in medicine