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Computational methods support and enhance the physician’s ability to utilize these imaging techniques for diagnosis, non-invasive treatment, and intervention in clinical practice. Spine imaging via computed tomography, magnetic resonance imaging, and other radiologic imaging modalities, is essential for noninvasively visualizing and assessing spinal pathology. This book is instrumental to building a bridge between scientists and clinicians in the field of spine imaging by introducing state-of-the-art computational methods in the context of clinical applications. This work will be of interest to researchers, students, and manufacturers in the fields of artificial intelligence, bioengineering, biomechanics, computational mechanics, computational vision, computer sciences, human motion, mathematics, medical imaging, medicine, pattern recognition and physics This volume treats topics such as, anatomic and functional shape representation and matching shape-based medical image segmentation shape registration statistical shape analysis shape deformation shape-based abnormity detection shape tracking and longitudinal shape analysis machine learning for shape modeling and analysis shape-based computer-aided-diagnosis shape-based medical navigation benchmark and validation of shape representation, analysis and modeling algorithms. First book to cover this topic in the field so comprehensively Detailed attention is given to sub-topics too Medical imaging is a topic that affects many and has wide applications This book contains thirteen contributions from invited experts of international recognition addressing important issues in shape analysis in medical image analysis, including techniques for image segmentation, registration, modelling and classification, and applications in biology, as well as in cardiac, brain, spine, chest, lung and clinical practice.

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