S. Kaisar Alam – författare

Tissue Elasticity Imaging: Volume One: Theory and Methods offers an extensive treatment of the fundamentals and applications of this groundbreaking diagnostic modality. The book introduces elasticity imaging, its history, the fundamental physics, and the different elasticity imaging methods, along with their implementation details, problems and artefacts. It is an essential resource for all researchers and practitioners interested in any elasticity imaging modality. As many diseases, including cancers, alter tissue mechanical properties, it is not always possible for conventional methods to detect changes, but with elasticity images that are produced by slow tissue deformation or low-frequency vibration, these changes can be displayed.

Offers the first comprehensive reference on elasticity imaging Discusses the fundamentals of technology and their limitations and solutions, along with advanced methods and future directions Addresses the technologies and applications useful to both researchers and clinical practitioners Includes an online reference section regularly updated with advances in technology and applications

Tissue Elasticity Imaging: Volume Two: Clinical Applications offers an extensive treatment of the fundamentals and applications of this groundbreaking diagnostic modality. Techniques and results are presented for the assessment of breast, prostate, heart, liver and thyroid tissues. For each application, details are provided on how to perform each technique, along with methods of interpretation, diagnostic criteria, quality assurance, challenges and case studies. This book is an essential resource for all researchers and practitioners (including scientists, radiologists, urologists, fellows and residents) interested in any elasticity imaging modality.

As many diseases, including cancers, alter tissue mechanical properties, it is not always possible for conventional methods to detect changes, but with elasticity images that are produced by slow tissue deformation or low-frequency vibration, these changes can be displayed.

Offers the first comprehensive reference on elasticity imaging Discusses the fundamentals of technology and their limitations and solutions, along with advanced methods and future directions Addresses the technologies and applications useful to both researchers and clinical practitioners Includes an online reference section regularly updated with advances in technology and applications

Tissue Elasticity Imaging: Volume One: Theory and Methods offers an extensive treatment of the fundamentals and applications of this groundbreaking diagnostic modality. The book introduces elasticity imaging, its history, the fundamental physics, and the different elasticity imaging methods, along with their implementation details, problems and artefacts. It is an essential resource for all researchers and practitioners interested in any elasticity imaging modality. As many diseases, including cancers, alter tissue mechanical properties, it is not always possible for conventional methods to detect changes, but with elasticity images that are produced by slow tissue deformation or low-frequency vibration, these changes can be displayed.- Offers the first comprehensive reference on elasticity imaging- Discusses the fundamentals of technology and their limitations and solutions, along with advanced methods and future directions- Addresses the technologies and applications useful to both researchers and clinical practitioners- Includes an online reference section regularly updated with advances in technology and applications

Tissue Elasticity Imaging: Volume Two: Clinical Applications offers an extensive treatment of the fundamentals and applications of this groundbreaking diagnostic modality. Techniques and results are presented for the assessment of breast, prostate, heart, liver and thyroid tissues. For each application, details are provided on how to perform each technique, along with methods of interpretation, diagnostic criteria, quality assurance, challenges and case studies. This book is an essential resource for all researchers and practitioners (including scientists, radiologists, urologists, fellows and residents) interested in any elasticity imaging modality.As many diseases, including cancers, alter tissue mechanical properties, it is not always possible for conventional methods to detect changes, but with elasticity images that are produced by slow tissue deformation or low-frequency vibration, these changes can be displayed.- Offers the first comprehensive reference on elasticity imaging- Discusses the fundamentals of technology and their limitations and solutions, along with advanced methods and future directions- Addresses the technologies and applications useful to both researchers and clinical practitioners- Includes an online reference section regularly updated with advances in technology and applications

This class-tested textbook is designed for a semester-long graduate or senior undergraduate course on Computational Health Informatics. The focus of the book is on computational techniques that are widely used in health data analysis and health informatics and it integrates computer science and clinical perspectives. This book prepares computer science students for careers in computational health informatics and medical data analysis.Features Integrates computer science and clinical perspectives Describes various statistical and artificial intelligence techniques, including machine learning techniques such as clustering of temporal data, regression analysis, neural networks, HMM, decision trees, SVM, and data mining, all of which are techniques used widely used in health-data analysis Describes computational techniques such as multidimensional and multimedia data representation and retrieval, ontology, patient-data deidentification, temporal data analysis, heterogeneous databases, medical image analysis and transmission, biosignal analysis, pervasive healthcare, automated text-analysis, health-vocabulary knowledgebases and medical information-exchange Includes bioinformatics and pharmacokinetics techniques and their applications to vaccine and drug development

This class-tested textbook is designed for a semester-long graduate or senior undergraduate course on Computational Health Informatics. The focus of the book is on computational techniques that are widely used in health data analysis and health informatics and it integrates computer science and clinical perspectives. This book prepares computer science students for careers in computational health informatics and medical data analysis.

Features

Integrates computer science and clinical perspectives

Describes various statistical and artificial intelligence techniques, including machine learning techniques such as clustering of temporal data, regression analysis, neural networks, HMM, decision trees, SVM, and data mining, all of which are techniques used widely used in health-data analysis

Describes computational techniques such as multidimensional and multimedia data representation and retrieval, ontology, patient-data deidentification, temporal data analysis, heterogeneous databases, medical image analysis and transmission, biosignal analysis, pervasive healthcare, automated text-analysis, health-vocabulary knowledgebases and medical information-exchange

Includes bioinformatics and pharmacokinetics techniques and their applications to vaccine and drug development

This class-tested textbook is designed for a semester-long graduate or senior undergraduate course on Computational Health Informatics. The focus of the book is on computational techniques that are widely used in health data analysis and health informatics and it integrates computer science and clinical perspectives. This book prepares computer science students for careers in computational health informatics and medical data analysis.

Features

Integrates computer science and clinical perspectives

Describes various statistical and artificial intelligence techniques, including machine learning techniques such as clustering of temporal data, regression analysis, neural networks, HMM, decision trees, SVM, and data mining, all of which are techniques used widely used in health-data analysis

Describes computational techniques such as multidimensional and multimedia data representation and retrieval, ontology, patient-data deidentification, temporal data analysis, heterogeneous databases, medical image analysis and transmission, biosignal analysis, pervasive healthcare, automated text-analysis, health-vocabulary knowledgebases and medical information-exchange

Includes bioinformatics and pharmacokinetics techniques and their applications to vaccine and drug development