10% de desconto

Medical Image Recognition, Segmentation And Parsing eBook

Machine Learning And Multiple Object Approaches

de S. Kevin Zhou
idioma: inglês
Editor: ELSEVIER SCIENCE, dezembro de 2015 ‧
116,60€
10% DESCONTO CARTÃO
DISPONIBILIDADE IMEDIATA
Ebook para ADE
This book describes the technical problems and solutions for automatically recognizing and parsing a medical image into multiple objects, structures, or anatomies. It gives all the key methods, including state-of- the-art approaches based on machine learning, for recognizing or detecting, parsing or segmenting, a cohort of anatomical structures from a medical image.Written by top experts in Medical Imaging, this book is ideal for university researchers and industry practitioners in medical imaging who want a complete reference on key methods, algorithms and applications in medical image recognition, segmentation and parsing of multiple objects.Learn:- Research challenges and problems in medical image recognition, segmentation and parsing of multiple objects- Methods and theories for medical image recognition, segmentation and parsing of multiple objects- Efficient and effective machine learning solutions based on big datasets- Selected applications of medical image parsing using proven algorithms- Provides a comprehensive overview of state-of-the-art research on medical image recognition, segmentation, and parsing of multiple objects- Presents efficient and effective approaches based on machine learning paradigms to leverage the anatomical context in the medical images, best exemplified by large datasets- Includes algorithms for recognizing and parsing of known anatomies for practical applications

Medical Image Recognition, Segmentation And Parsing

Machine Learning And Multiple Object Approaches

de S. Kevin Zhou

Propriedade Descrição
ISBN: 9780128026762
Editor: ELSEVIER SCIENCE
Data de Lançamento: dezembro de 2015
Idioma: Inglês
Tipo de produto: eBook
Formato e Compatibilidade:
Classificação Temática: eBooks em Inglês > Medicina > Medicina Geral
EAN: 9780128026762
Acessibilidade: Ver características de acessibilidade indicadas pelo editor