Isbn: 9780323761116 - atlas of spinal imaging: phenotypes, measurements and classification systems (18 resultados)

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Paperback. Condición: new. Paperback. Atlas of Spinal Imaging Phenotypes: Classifications and Radiographic Measurements Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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paperback. Condición: New. 1st Edition. Special order direct from the distributor.

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Condición: New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.…

Paperback. Condición: Brand New. 1st edition. 262 pages. 9.00x7.50x1.00 inches. In Stock.

Condición: New. Redaktion: Philip K. LouieDr. Philip Louie recently joined the Spine Team at the Virginia Mason Neuroscience Institute. He received his Bachelors Degree in Business Administration as well as Molecular, Cellular, and Developmental Biology at the Uni.

Condición: New. 2021. paperback. . . . . . Books ship from the US and Ireland.

Paperback. Condición: new. Paperback. Atlas of Spinal Imaging Phenotypes: Classifications and Radiographic Measurements Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Spine-related pain is the world's leading disabling condition, affecting every population and a frequent reason for seeking medical consultation and obtaining imaging studies. Numerous spinal phenotypes (observations/traits) and their respective measurements performed on various spine imaging have been shown to directly correlate and predict clinical outcomes._Atlas of Spinal Imaging:_Phenotypes, Measurements and Classification Systems is a comprehensive visual resource that highlights various spinal phenotypes on imaging, describes their clinical and pathophysiological relevance, and discusses and illustrates their respective measurement techniques and classifications._Complies the knowledge and expertise of Dr. Dino_Samartzis, the_preeminent_global authority on spinal phenotypes who has discovered and proposed new phenotypes and classification_schemes;_Dr. Howard S. An, a leading expert in patient management and at the forefront of 3D imaging of various spinal phenotypes; and Dr. Philip Louie, a young surgeon who is involved in one of the largest machine learning initiatives of spinal phenotyping. \*Includes a Foreword by renowed spine surgeons Alexander Vaccaro and Max Aebi\* Helps readers better understanding spinal phenotypes and their imaging, and how today's knowledge will facilitate new targeted drug discovery, novel diagnostics and biomarker discovery, and outcome predictions. Features step-by-step instructions on performing the radiographic measurements with examples of normal and pathologic images to demonstrate the various presentations. Presents clinical correlation of the phenotypes as well as the radiographic measurements with landmark references. Includes validated classification systems that complement the phenotypes and radiographic measurements. Complies the knowledge and expertise of Dr. Dino Samartzis, the preeminent global authority on spinal phenotypes who has discovered and proposed new phenotypes and classification schemes; Dr. Howard S. An, a leading expert in patient management and at the forefront of 3D imaging of various spinal phenotypes; and Dr. Philip Louie, a prolific surgeon who is involved in one of the largest machine learning initiatives of spinal phenotyping. 282 pp. Englisch.…

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Spine-related pain is the world s leading disabling condition, affecting every population and a frequent reason for seeking medical consultation and obtaining imaging studies. Numerous spinal phenotypes (observations/traits) and their respective measurements performed on various spine imaging have been shown to directly correlate and predict clinical outcomes. Atlas of Spinal Imaging: Phenotypes, Measurements and Classification Systems is a comprehensive visual resource that highlights various spinal phenotypes on imaging, describes their clinical and pathophysiological relevance, and discusses and illustrates their respective measurement techniques and classifications. Complies the knowledge and expertise of Dr. Dino Samartzis, the preeminent global authority on spinal phenotypes who has discovered and proposed new phenotypes and classification schemes; Dr. Howard S. An, a leading expert in patient management and at the forefront of 3D imaging of various spinal phenotypes; and Dr. Philip Louie, a young surgeon who is involved in one of the largest machine learning initiatives of spinal phenotyping.\*Includes a Foreword by renowed spine surgeons Alexander Vaccaro and Max Aebi\*Helps readers better understanding spinal phenotypes and their imaging, and how today s knowledge will facilitate new targeted drug discovery, novel diagnostics and biomarker discovery, and outcome predictionsFeatures step-by-step instructions on performing the radiographic measurements with examples of normal and pathologic images to demonstrate the various presentationsPresents clinical correlation of the phenotypes as well as the radiographic measurements with landmark referencesIncludes validated classification systems that complement the phenotypes and radiographic measurementsComplies the knowledge and expertise of Dr. Dino Samartzis, the preeminent global authority on spinal phenotypes who has discovered and proposed new phenotypes and classification schemes; Dr. Howard S. An, a leading expert in patient management and at the forefront of 3D imaging of various spinal phenotypes; and Dr. Philip Louie, a prolific surgeon who is involved in one of the largest machine learning initiatives of spinal phenotyping.…