Xiaoming Zheng – författare

This book provides an holistic picture of the application of research in radiography and focuses on multivariant methodological approaches and practices. It will provide readers insight into both contemporary and innovative methods within radiography research, backed up with evidence-based literature. This book may also be translated into other health disciplines as it introduces research to the reader by detailing terms that can often be confusing for students. These remain central in understanding the importance of research in radiography and how the generation of new knowledge is obtained. This will be supported with subsequent chapters concerning the literature, formation of research questions and detail the early beginnings of a research proposal. Chapters will include a wide range of topics, such as quantitative and qualitative methodologies and data collection tools pertinent to radiographic research, whilst discussing data analysis and need for rigor. The authors draw from our experiences, published outputs and clinical work, supported with alternate philosophies and methods used in diagnostic radiography. Each chapter will examine the multifaceted use and application of each ‘sub-theme’ pertinent to research in radiography, which is presented in a single text for students and, perhaps, practitioners. The targeted audience for this book is interdisciplinary but clearly focuses on those studying undergraduate radiography in response to the limited texts available. We also anticipate it to provide a useful tool for academics delivering undergraduate radiography programmes and those supporting postgraduate research. The key features will:

This book provides an holistic picture of the application of research in radiography and focuses on multivariant methodological approaches and practices. It will provide readers insight into both contemporary and innovative methods within radiography research, backed up with evidence-based literature. This book may also be translated into other health disciplines as it introduces research to the reader by detailing terms that can often be confusing for students. These remain central in understanding the importance of research in radiography and how the generation of new knowledge is obtained. This will be supported with subsequent chapters concerning the literature, formation of research questions and detail the early beginnings of a research proposal. Chapters will include a wide range of topics, such as quantitative and qualitative methodologies and data collection tools pertinent to radiographic research, whilst discussing data analysis and need for rigor. The authors draw from our experiences, published outputs and clinical work, supported with alternate philosophies and methods used in diagnostic radiography. Each chapter will examine the multifaceted use and application of each ‘sub-theme’ pertinent to research in radiography, which is presented in a single text for students and, perhaps, practitioners. The targeted audience for this book is interdisciplinary but clearly focuses on those studying undergraduate radiography in response to the limited texts available. We also anticipate it to provide a useful tool for academics delivering undergraduate radiography programmes and those supporting postgraduate research. The key features will:

This edited book focuses on the application of AI and data analytics within medical imaging with contributions focussing on general radiography, cross-sectional imaging, and breast imaging.

Artificial Intelligence and Data Analytics in Medical Imaging leverages the expertise of key practitioners, academics, and researchers who are recognised leaders in their respective fields. The chapters cover essential topics, including imaging modalities, radiotherapy, and future recommendations. The editors incorporate insights from recent publications and clinical practice, addressing how emerging technologies should be managed, implemented, and adapted in healthcare settings. Each chapter maintains a patient-centred focus while connecting to key literature in the field.

This book acts as a cornerstone for undergraduate students, but importantly signposts to other key texts within the field of medical imaging. Further, academics will also find this text useful as it aims to enrich scholarly learning, teaching, and assessment in healthcare programmes nationally and internationally.

This edited book focuses on the application of AI and data analytics within medical imaging with contributions focussing on general radiography, cross-sectional imaging, and breast imaging.

Artificial Intelligence and Data Analytics in Medical Imaging leverages the expertise of key practitioners, academics, and researchers who are recognised leaders in their respective fields. The chapters cover essential topics, including imaging modalities, radiotherapy, and future recommendations. The editors incorporate insights from recent publications and clinical practice, addressing how emerging technologies should be managed, implemented, and adapted in healthcare settings. Each chapter maintains a patient-centred focus while connecting to key literature in the field.

This book acts as a cornerstone for undergraduate students, but importantly signposts to other key texts within the field of medical imaging. Further, academics will also find this text useful as it aims to enrich scholarly learning, teaching, and assessment in healthcare programmes nationally and internationally.