Computer Vision Techniques for the Diagnosis of Skin Cancer, Jacob Scharcanski; M. Emre Celebi

Автор: Helmut Madjar
Название: The Practice of Breast Ultrasound: Techniques, Findings, Differential Diagnosis
ISBN: 3131243422 ISBN-13(EAN): 9783131243423
Издательство: Thieme Verlagsgruppe
Цена: 17919.00 р. 25599.00 -30%
Наличие на складе: Есть (1 шт.)
Описание: The second edition of The Practice of Breast Ultrasound is an indispensable reference for the latest techniques in detecting common breast pathologies. New in this edition are guidelines for quality control and an expanded chapter on 3D scanning. More than 7 high-quality images, including new 1 images, demonstrate concepts of pathology and facilitate comprehension of diagnostic techniques. The book is organized into three main sections enabling radiologists, residents, and sonographers with various levels of expertise to rapidly locate topics of interest. Basic Course: Provides an introduction to the fundamental principles of breast ultrasound, equipment selection, and standard protocols for the examination Reviews sonographic anatomy of the breast and axilla Describes approaches to interpreting and managing common benign and malignant lesions Includes a new chapter dedicated to the American College of Radiology's Breast Imaging Reporting and Data System (BI-RADS®) that presents the lexicon and categories for feature analysis and quality assurance Intermediate Course: Presents guidelines on how to use feature analysis in analyzing lesion findings Discusses the complementary roles of ultrasound, mammography, and the clinical evaluation Addresses a different pathological condition in each chapter Features high-quality images as well as diagnostic checklists that apply the BI-RADS® feature categories of shape, margins, boundaries, echo patterns, and effects on the surrounding tissue, enabling the clinician to perceive patterns associated with specific abnormalities and to arrive at interpretations that lead to appropriate patient management plans Advanced Course: Presents the latest information about image-guided intervention for diagnosis, preoperative breast cancer staging, post-treatment follow-up, and advanced or investigational ultrasound technologies, such as 3D/4D ultrasound, real-time compound scanning, harmonics, wide field-of-view, Doppler techniques, and elastography

Автор: Parker J J
Название: Algorithms for Image Processing and Computer Vision
ISBN: 0470643854 ISBN-13(EAN): 9780470643853
Издательство: Wiley
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Цена: 12514.00 р.
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Описание: Programmers, scientists, and engineers are always in need of newer techniques and algorithms to manipulate and interpret images. Algorithms for Image Processing and Computer Vision is an accessible collection of algorithms for common image processing applications that simplifies complicated mathematical calculations.

Автор: Srikanta Patnaik; Yeon-Mo Yang
Название: Soft Computing Techniques in Vision Science
ISBN: 3642444407 ISBN-13(EAN): 9783642444401
Издательство: Springer
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Цена: 21661.00 р.
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Описание: Covering the latest research on soft computing techniques in the emerging field of vision science, this publication features contributions from leading experts and covers a range of topics including frequent pattern mining and 4D stereo camera systems.

Автор: Inoue
Название: Cancer Staging Diagnosis with PET/CT
ISBN: 1461400333 ISBN-13(EAN): 9781461400332
Издательство: Springer
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Цена: 15372.00 р.
Наличие на складе: Поставка под заказ.

Описание: Cancer Staging Diagnosis with PET/CT is a concise guide to the clinical use of PET/CT imaging in cancer staging diagnosis. PET/CT is currently the prevailing modality for visualizing the distribution of radionuclide tracers in patients to diagnose malignant tumors. This unique book organizes common malignant tumors by histologic subtype, with clinical case examples of each accompanied by high-resolution figures and information on image interpretation and clinical discussion points. Chapters are organized into major sections of anatomic regions based on the TNM classification of malignant tumors, including brain, head & neck, chest, gastrointestinal, genitourinary, breast, gynecological, bone/soft tissues, pediatrics, and hematology.

Автор: David Forsyth; Philip Torr; Andrew Zisserman
Название: Computer Vision - ECCV 2008
ISBN: 3540886818 ISBN-13(EAN): 9783540886815
Издательство: Springer
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Цена: 16070.00 р.
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Описание: Constitutes the refereed proceedings of the 10th European Conference on Computer Vision, ECCV 2008, held in Marseille, France, in October 2008. This book features sections on recognition, stereo, people and face recognition, object tracking, matching, learning and features, MRFs, segmentation, computational photography, and active reconstruction.

Автор: Leibe
Название: Computer Vision – ECCV 2016
ISBN: 3319464868 ISBN-13(EAN): 9783319464862
Издательство: Springer
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Цена: 13696.00 р.
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Описание: The eight-volume set comprising LNCS volumes 9905-9912 constitutes the refereed proceedings of the 14th European Conference on Computer Vision, ECCV 2016, held in Amsterdam, The Netherlands, in October 2016. The papers cover all aspects of computer vision and pattern recognition such as 3D computer vision; low-level vision and image processing;

Автор: Mongi A. Abidi; Andrei V. Gribok; Joonki Paik
Название: Optimization Techniques in Computer Vision
ISBN: 3319463632 ISBN-13(EAN): 9783319463636
Издательство: Springer
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Цена: 18167.00 р.
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Описание: This book presents practical optimization techniques used in image processing and computer vision problems. Ill-posed problems are introduced and used as examples to show how each type of problem is related to typical image processing and computer vision problems. Unconstrained optimization gives the best solution based on numerical minimization of a single, scalar-valued objective function or cost function. Unconstrained optimization problems have been intensively studied, and many algorithms and tools have been developed to solve them. Most practical optimization problems, however, arise with a set of constraints. Typical examples of constraints include: (i) pre-specified pixel intensity range, (ii) smoothness or correlation with neighboring information, (iii) existence on a certain contour of lines or curves, and (iv) given statistical or spectral characteristics of the solution. Regularized optimization is a special method used to solve a class of constrained optimization problems. The term regularization refers to the transformation of an objective function with constraints into a different objective function, automatically reflecting constraints in the unconstrained minimization process. Because of its simplicity and efficiency, regularized optimization has many application areas, such as image restoration, image reconstruction, optical flow estimation, etc.