Auto-Segmentation for Radiation Oncology, Yang, Jinzhong

Автор: Michael Heinrich Seegenschmiedt
Название: Radiotherapy for Non-Malignant Disorders
ISBN: 3642082920 ISBN-13(EAN): 9783642082924
Издательство: Springer
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Цена: 142830.00 T
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Описание: This volume is an unrivalled and comprehensive survey on the use of radiotherapy to treat non-malignant disorders. It documents the radiobiological and physical principles of treatment and the rationale underlying the use of radiotherapy.

Автор: Baum Richard P.
Название: Therapeutic Nuclear Medicine
ISBN: 3540367187 ISBN-13(EAN): 9783540367185
Издательство: Springer
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Цена: 186330.00 T
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Описание: The recent revolution in molecular biology offers exciting new opportunities for targeted radionuclide therapy.

Название: Intracranial and spinal radiotherapy
ISBN: 303064507X ISBN-13(EAN): 9783030645076
Издательство: Springer
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Цена: 69870.00 T
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Описание: Leading experts in the field explain treatment techniques in detail, highlighting key considerations in the use of external beam radiation therapy, intensity-modulated radiation therapy, particle therapy, radiosurgery, and stereotactic body radiation therapy.

Автор: Edward C. Halperin, David E. Wazer, Carlos A. Perez
Название: Perez & Brady`s principles and practice of radiation oncology. 7 ed
ISBN: 1496386795 ISBN-13(EAN): 9781496386793
Издательство: Lippincott Williams & Wilkins
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Цена: 290570.00 T
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Описание: Publisher's Note: Products purchased from 3rd Party sellers are not guaranteed by the Publisher for quality, authenticity, or access to any online entitlements included with the product.

For more than 30 years, Perez and Brady's Principles and Practice of Radiation Oncology has been the must-have standard reference for radiation oncologists and radiation oncology residents who need a comprehensive text covering both the biological and physical science aspects of this complex field as well as disease site-specific information on the integrated, multidisciplinary management of patients with cancer. The book has established itself as the discipline's "text-of-record," belonging on the shelf of all of those working in the field. The Seventh Edition continues this tradition of excellence with extensive updates throughout, many new chapters, and more than 1,400 full-color illustrations that highlight key concepts in tumor pathogenesis, diagnosis, and targeted radiation therapy.

• Comprehensive coverage of the current state of knowledge of cancer biology; medical radiation physics; clinical radiation oncology; and radiation oncology economics, ethics, and public policy.
• Regular, twice-yearly content updates available with the digital version of the text.
• Ideal for radiation oncologists, radiation oncology residents, radiation biologists, medical radiation physicists, oncologists, physicists-in-training, radiation dosimetrists, and nurses and physician assistants working in radiation oncology departments.
• New chapters include: Proton and Carbon Ion Beam Dosimetry and Treatment Planning; Stereotactic Radiation Therapy; Re-Irradiation; Error Avoidance; Undergraduate, Graduate, and Continuing Medical Education in Radiation Oncology; and a completely rewritten chapter on the economics of radiation oncology.
• Designed to provide a better understanding of the natural history of cancer, the physical and technological methods of radiation application, the effects of irradiation on normal tissues, and the most judicious ways in which radiation therapy can be employed in the treatment of patients with cancer, either as a single modality or as part of a multi-modality treatment program.
• All references printed in the book are now streamlined for quick access to further information.
• Site-specific chapters include relevant background information on each tumor--including epidemiology, pathology, diagnostic work-up, prognostic factors, treatment techniques, applications of surgery, chemotherapy, immunotherapy and biological therapy, end results, and more.
• Increased focus on new approaches and technologies with new and updated chapters.
• Greater emphasis on palliative and supportive care reflects the role of radiation treatment in non-curative roles.
• An international group of expert chapter authors keeps you well-informed.
• A completely revised first chapter is designed to provide an overview of the discipline of radiation oncology. This will be particularly useful for residents beginning training and medical students beginning a radiation oncology clinical clerkship. The chapter is supplemented with multiple sidebars to augment the reader's understanding of the field.

Название: Nanomaterials and Neoplasms
ISBN: 9814800392 ISBN-13(EAN): 9789814800396
Издательство: Taylor&Francis
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Цена: 197010.00 T
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Описание: Published in 2019, the main aim of this book is to offer a more industrial/clinical point of view to students and researchers, together with the knowledge of regulatory agencies.

Название: Auto-segmentation for radiation oncology
ISBN: 0367336006 ISBN-13(EAN): 9780367336004
Издательство: Taylor&Francis
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Цена: 117390.00 T
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Описание: This book provides a comprehensive introduction to current state-of-the-art auto-segmentation approaches used in radiation oncology for auto-delineation of organs-of-risk for thoracic radiation treatment planning.

Автор: Shusharina Nadya, Heinrich Mattias P., Huang Ruobing
Название: Segmentation, Classification, and Registration of Multi-Modality Medical Imaging Data: Miccai 2020 Challenges, ABCs 2020, L2r 2020, Tn-Scui 2020, Held
ISBN: 3030718263 ISBN-13(EAN): 9783030718268
Издательство: Springer
Цена: 46570.00 T
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Описание: ABCs - Anatomical Brain Barriers to Cancer Spread: Segmentation from CT and MR Images.- Cross-modality Brain Structures Image Segmentation for the Radiotherapy Target Definition and Plan Optimization.- Domain Knowledge Driven Multi-modal Segmentation of Anatomical Brain Barriers to Cancer Spread.- Ensembled ResUnet for Anatomical Brain Barriers Segmentation.- An Enhanced Coarse-to-_ne Framework for the segmentation of clinical target volume.- Automatic Segmentation of brain structures for treatment planning optimization and target volume definition.- A Bi-Directional, Multi-Modality Framework for Segmentation of Brain Structures.- L2R - Learn2Reg: Multitask and Multimodal 3D Medical Image Registration.- Large Deformation Image Registration with Anatomy-aware Laplacian Pyramid Networks.- Discrete Unsupervised 3D Registration Methods for the Learn2Reg Challenge.- Variable Fraunhofer MEVIS RegLib comprehensively applied to Learn2Reg Challenge.- Learning a deformable registration pyramid.- Deep learning based registration using spatial gradients and noisy segmentation labels.- Multi-step, Learning-based, Semi-supervised Image Registration Algorithm.- Using Elastix to register inhale/exhale intrasubject thorax CT: a unsupervised baseline to the task 2 of the Learn2Reg challenge.- TN-SCUI - Thyroid Nodule Segmentation and Classification in Ultrasound Images.- Cascade Unet and CH-Unet for thyroid nodule segmenation and benign and malignant classification.- Identifying Thyroid Nodules in Ultrasound Images through Segmentation-guided Discriminative Localization.- Cascaded Networks for Thyroid Nodule Diagnosis from Ultrasound Images.- Automatic Segmentation and Classification of Thyroid Nodules in Ultrasound Images with Convolutional Neural Networks.- LRTHR-Net: A Low-Resolution-to-High-Resolution Framework to Iteratively Refine the Segmentation of Thyroid Nodule in Ultrasound Images.- Coarse to Fine Ensemble Network for Thyroid Nodule Segmentation.

Автор: Heller Nicholas, Isensee Fabian, Trofimova Darya
Название: Kidney and Kidney Tumor Segmentation: MICCAI 2021 Challenge, KiTS 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021,
ISBN: 3030983846 ISBN-13(EAN): 9783030983840
Издательство: Springer
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Цена: 51230.00 T
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Описание: This book constitutes the Second International Challenge on Kidney and Kidney Tumor Segmentation, KiTS 2021, which was held in conjunction with the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021. The challenge took place virtually on September 27, 2021, due to the COVID-19 pandemic. The 21 contributions presented were carefully reviewed and selected from 29 submissions. This challenge aims to develop the best system for automatic semantic segmentation of renal tumors and surrounding anatomy.

Автор: Yan Chai Hum
Название: Segmentation of Hand Bone for Bone Age Assessment
ISBN: 9814451657 ISBN-13(EAN): 9789814451659
Издательство: Springer
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Цена: 65290.00 T
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Описание: The objective of this Brief is to provide a solution to the unsolved technical problem in segmentation for the automated bone age assessment system. It is followed by a novel fuzzy quadruple division scheme to optimize the central segmentation algorithm, and then an additional quality assurance scheme.

Автор: Ayman S. El-Baz; Rajendra Acharya U; Majid Mirmehd
Название: Multi Modality State-of-the-Art Medical Image Segmentation and Registration Methodologies
ISBN: 1489978135 ISBN-13(EAN): 9781489978134
Издательство: Springer
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Цена: 191550.00 T
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Описание: Advances in image-guided cancer surgery have enlarged the role of image segmentation and registration. This book reviews current methodologies, to help physicians delineate anatomical structures, enhance the accuracy of diagnosis and improve treatment planning.

Автор: Yefeng Zheng; Dorin Comaniciu
Название: Marginal Space Learning for Medical Image Analysis
ISBN: 1493955756 ISBN-13(EAN): 9781493955756
Издательство: Springer
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Цена: 74530.00 T
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Описание: Automatic detection and segmentation of anatomical structures in medical images are prerequisites to subsequent image measurements and disease quantification, and therefore have multiple clinical applications.

Автор: Ayman El-Baz, Jasjit S. Suri
Название: Level Set Method in Medical Imaging Segmentation
ISBN: 113855345X ISBN-13(EAN): 9781138553453
Издательство: Taylor&Francis
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Цена: 224570.00 T
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Описание: Level set methods are numerical techniques which offer remarkably powerful tools for understanding, analyzing, and computing interface motion in a host of settings. When used for medical imaging analysis and segmentation, the function assigns a label to each pixel or voxel and optimality is defined based on desired imaging properties. This often includes a detection step to extract specific objects via segmentation. This allows for the segmentation and analysis problem to be formulated and solved in a principled way based on well-established mathematical theories. Level set method is a great tool for modeling time varying medical images and enhancement of numerical computations.