Контакты/Проезд  Доставка и Оплата Помощь/Возврат
История
  +7(495) 980-12-10
  пн-пт: 10-18 сб,вс: 11-18
  shop@logobook.ru
   
    Поиск книг                    Поиск по списку ISBN Расширенный поиск    
Найти
  Зарубежные издательства Российские издательства  
Авторы | Каталог книг | Издательства | Новинки | Учебная литература | Акции | Хиты | |
 

Machine Learning and Deep Learning Techniques for Medical Image Recognition, Soufiene, Ben Othman ; Chakraborty, Chinmay


Варианты приобретения
Цена: 19140.00р.
Кол-во:
Наличие: Поставка под заказ.  Есть в наличии на складе поставщика.
Склад Америка: Есть  
При оформлении заказа до: 2025-07-28
Ориентировочная дата поставки: Август-начало Сентября
При условии наличия книги у поставщика.

Добавить в корзину
в Мои желания

Автор: Soufiene, Ben Othman ; Chakraborty, Chinmay
Название:  Machine Learning and Deep Learning Techniques for Medical Image Recognition
ISBN: 9781032416168
Издательство: Taylor&Francis
Классификация:






ISBN-10: 1032416165
Обложка/Формат: Hardcover
Страницы: 258
Вес: 0.50 кг.
Дата издания: 12/01/2023
Серия: Advances in Smart Healthcare Technologies
Иллюстрации: 62 tables, black and white; 73 line drawings, black and white; 46 halftones, black and white; 119 illustrations, black and white
Размер: 234 x 156
Основная тема: Technology & Engineering | Biomedical ; Medical | Diagnosis
Ссылка на Издательство: Link
Рейтинг:
Поставляется из: Европейский союз


Linear Algebra and Learning from Data

Автор: Strang Gilbert
Название: Linear Algebra and Learning from Data
ISBN: 0692196382 ISBN-13(EAN): 9780692196380
Издательство: Cambridge Academ
Рейтинг:
Цена: 9978.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Linear algebra and the foundations of deep learning, together at last! From Professor Gilbert Strang, acclaimed author of Introduction to Linear Algebra, comes Linear Algebra and Learning from Data, the first textbook that teaches linear algebra together with deep learning and neural nets. This readable yet rigorous textbook contains a complete course in the linear algebra and related mathematics that students need to know to get to grips with learning from data. Included are: the four fundamental subspaces, singular value decompositions, special matrices, large matrix computation techniques, compressed sensing, probability and statistics, optimization, the architecture of neural nets, stochastic gradient descent and backpropagation.

Pattern Recognition and Machine Learning

Автор: Christopher M. Bishop
Название: Pattern Recognition and Machine Learning
ISBN: 1493938436 ISBN-13(EAN): 9781493938438
Издательство: Springer
Рейтинг:
Цена: 10480.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

Computational Techniques for Dental Image Analysis

Автор: K. Kamalanand, B. Thayumanavan, P. Mannar Jawahar
Название: Computational Techniques for Dental Image Analysis
ISBN: 1522562435 ISBN-13(EAN): 9781522562436
Издательство: Mare Nostrum (Eurospan)
Рейтинг:
Цена: 35402.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: With the technology innovations dentistry has witnessed in all its branches over the past three decades, the need for more precise diagnostic tools and advanced imaging methods has become mandatory across the industry. Recent advancements to imaging systems are playing an important role in efficient diagnoses, treatments, and surgeries.Computational Techniques for Dental Image Analysis provides innovative insights into computerized methods for automated analysis. The research presented within this publication explores pattern recognition, oral pathologies, and diagnostic processing. It is designed for dentists, professionals, medical educators, medical imaging technicians, researchers, oral surgeons, and students, and covers topics centered on easier assessment of complex cranio-facial tissues and the accurate diagnosis of various lesions at early stages.

Mathematics for Machine Learning

Автор: Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong
Название: Mathematics for Machine Learning
ISBN: 110845514X ISBN-13(EAN): 9781108455145
Издательство: Cambridge Academ
Рейтинг:
Цена: 6334.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This self-contained textbook introduces all the relevant mathematical concepts needed to understand and use machine learning methods, with a minimum of prerequisites. Topics include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics.

Patch-Based Techniques in Medical Imaging

Автор: Wu
Название: Patch-Based Techniques in Medical Imaging
ISBN: 3319471171 ISBN-13(EAN): 9783319471174
Издательство: Springer
Рейтинг:
Цена: 5870.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: The main aim of the Patch-MI 2016 workshop is to promote methodological advances within the medical imaging field, with various applications in image segmentation, image denoising, image super-resolution, computer-aided diagnosis, image registration, abnormality detection, and image synthesis.

Machine Learning in Medical Imaging

Автор: Qian Wang; Yinghuan Shi; Heung-Il Suk; Kenji Suzuk
Название: Machine Learning in Medical Imaging
ISBN: 3319673882 ISBN-13(EAN): 9783319673882
Издательство: Springer
Рейтинг:
Цена: 9083.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book constitutes the refereed proceedings of the 8th International Workshop on Machine Learning in Medical Imaging, MLMI 2017, held in conjunction with MICCAI 2017, in Quebec City, QC, Canada, in September 2017. The main aim of this workshop is to help advance scientific research within the broad field of machine learning in medical imaging.

Machine Learning for Medical Image Reconstruction

Автор: Florian Knoll; Andreas Maier; Daniel Rueckert
Название: Machine Learning for Medical Image Reconstruction
ISBN: 3030001288 ISBN-13(EAN): 9783030001285
Издательство: Springer
Рейтинг:
Цена: 6986.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book constitutes the refereed proceedings of the First International Workshop on Machine Learning for Medical Reconstruction, MLMIR 2018, held in conjunction with MICCAI 2018, in Granada, Spain, in September 2018.The 17 full papers presented were carefully reviewed and selected from 21 submissions. The papers are organized in the following topical sections: deep learning for magnetic resonance imaging; deep learning for computed tomography, and deep learning for general image reconstruction.

Machine Learning Techniques for Gait Biometric Recognition

Автор: James Eric Mason; Issa Traor?; Isaac Woungang
Название: Machine Learning Techniques for Gait Biometric Recognition
ISBN: 331929086X ISBN-13(EAN): 9783319290867
Издательство: Springer
Рейтинг:
Цена: 13974.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Introduction.- Background.- Experimental Design and Dataset.- Feature Extraction.-Normalization.- Classification.- Measured Performance.- Experimental Analysis.- Conclusion.

Patch-Based Techniques in Medical Imaging

Автор: Guorong Wu; Brent C. Munsell; Yiqiang Zhan; Wenjia
Название: Patch-Based Techniques in Medical Imaging
ISBN: 3319674331 ISBN-13(EAN): 9783319674339
Издательство: Springer
Рейтинг:
Цена: 6986.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book constitutes the refereed proceedings of the Third International Workshop on Patch-Based Techniques in Medical Images, Patch-MI 2017, which was held in conjunction with MICCAI 2017, in Quebec City, QC, Canada, in September 2017. The 18 regular papers presented in this volume were carefully reviewed and selected from 26 submissions.

Patch-Based Techniques in Medical Imaging

Автор: Guorong Wu; Pierrick Coup?; Yiqiang Zhan; Brent Mu
Название: Patch-Based Techniques in Medical Imaging
ISBN: 3319281933 ISBN-13(EAN): 9783319281933
Издательство: Springer
Рейтинг:
Цена: 6708.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание:

A Multi-level Canonical Correlation Analysis Scheme for Standard-dose PET Image Estimation.- Image Super-Resolution by Supervised Adaption of Patchwise Self-Similarity from High-Resolution Image.- Automatic Hippocampus Labeling Using the Hierarchy of Sub-Region Random Forests.- Isointense Infant Brain Segmentation by Stacked Kernel Canonical Correlation Analysis.- Improving Accuracy of Automatic Hippocampus Segmentation in Routine MRI by Features Learned from Ultra-high Field MRI.- Dual-Layer l1-Graph Embedding for Semi-Supervised Image Labeling.- Automatic Liver Tumor Segmentation in Follow-up CT Studies Using Convolutional Neural Network.- Block-based Statistics for Robust Non-Parametric Morphometry.- Automatic Collimation Detection in Digital Radiographs with the Directed Hough Transform and Learning-based Edge Detection.- Efficient Lung Cancer Cell Detection with Deep Convolutional Neural Network.- An Effective Approach for Robust Lung Cancer Cell Detection.- Laplacian Shape Editing with Local Patch Based Force Field for Interactive Segmentation.- Hippocampus Segmentation through Distance Field Fusion.- Learning a Spatiotemporal Dictionary for Magnetic Resonance Fingerprinting with Compress Sensing.- Fast Regions-of-Interest Detection in Whole Slide Histopathology Images.- Reliability Guided Forward and Backward Patch-based Method for Multi-atlas Segmentation.- Correlating Tumour Histology and ex vivo MRI Using Dense Modality-Independent Patch-Based Descriptor.- Multi-Atlas Segmentation using Patch-Based Joint Label Fusion with Non-Negative Least Squares Regression.- A Spatially Constrained Deep Learning Framework for Detection of Epithelial Tumor Nuclei in Cancer Histology Images.- 3D MRI Denoising using Rough Set Theory and Kernel Embedding Method.- A Novel Cell Orientation Congruence Descriptor for Superpixel based Epithelium Segmentation in Endometrial Histology Images.- Patch-based Segmentation from MP2RAGE Images: Comparison to Conventional Techniques.- Multi-Atlas and Multi-Modal Hippocampus Segmentation for Infant MR Brain Images by Propagating Anatomical Labels on Hypergraph.- Prediction of Infant MRI Appearance and Anatomical Structure Evolution using Sparse Patch-based Metamorphosis Learning Framework.- Efficient Multi-Scale Patch-based Segmentation.

Medical Computer Vision: Recognition Techniques and Applications in Medical Imaging

Автор: Bjoern Menze; Georg Langs; Le Lu; Albert Montillo;
Название: Medical Computer Vision: Recognition Techniques and Applications in Medical Imaging
ISBN: 3642366198 ISBN-13(EAN): 9783642366192
Издательство: Springer
Рейтинг:
Цена: 6986.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book constitutes the thoroughly refereed workshop proceedings of the Second International Workshop on Medical Computer Vision, MCV 2012, held in Nice, France, October 2012 in conjunction with the 15th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2012.

Patch-Based Techniques in Medical Imaging

Автор: Wenjia Bai; Gerard Sanroma; Guorong Wu; Brent C. M
Название: Patch-Based Techniques in Medical Imaging
ISBN: 3030004996 ISBN-13(EAN): 9783030004996
Издательство: Springer
Рейтинг:
Цена: 6986.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book constitutes the refereed proceedings of the 4th International Workshop on Patch-Based Techniques in Medical Images, Patch-MI 2018, held in conjunction with MICCAI 2018, in Granada, Spain, in September 2018.The 15 full papers presented were carefully reviewed and selected from 17 submissions. The papers are organized in the following topical sections: Image Denoising? Image Registration and Matching, Image Classification and Detection, Brain Image Analysis, and Retinal Image Analysis.


ООО "Логосфера " Тел:+7(495) 980-12-10 www.logobook.ru
   В Контакте     В Контакте Мед  Мобильная версия