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Medical Image Recognition, Segmentation And Parsing eBook
Machine Learning And Multiple Object Approaches
idioma: inglês
Editor:
ELSEVIER SCIENCE, dezembro de 2015 ‧
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116,60€
10% DESCONTO
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DISPONIBILIDADE IMEDIATA
Ebook para ADE
SINOPSE
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
DETALHES
| 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
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Medicina
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Medicina Geral
|
| EAN: | 9780128026762 |
| Acessibilidade: | Ver características de acessibilidade indicadas pelo editor |
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