Samartzis Philip (17 results)

Landscape 8vo, 191pp. Colour illustrations. A very good hardback copy. Contains 2 CDs.

Hard Cover. Dust Jacket Condition: None Issued. First Edition. Oblong 4to. original pictorial laminated boards; pp. 192, with illustrations + 2 CDs. Heavy item (1.25 kg), additional postage may be required for international delivery. A fine copy.

soft cover. Condition: Very Good. No Jacket. 1st edition. Illustrated with colour photographs, includes an audio CD. 26 cm. IX, 115 pages VG. Very good condition with light shelf wear to covers, top corner of title page clipped.

Pictorial Cover. Condition: Near Fine. 1st Edition. Full colour photographs throughout. Includes 2 CDs. Format: Oblong. 19 x 24.5 cm. 191 pp.

Condition: New.

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

Condition: As New. Unread book in perfect condition.

Condition: New.

Paperback. Condition: 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.

Paperback / softback. Condition: New. New copy - Usually dispatched within 4 working days.

Condition: As New. Unread book in perfect condition.

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

Condition: New. 2021. paperback. . . . . .

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

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

Paperback. Condition: 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. Condition: 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.…