Graph Learning in Medical Imaging

This book compiles the proceedings of the First International Workshop on Graph Learning in Medical Imaging, featuring 21 selected papers that explore innovative techniques in the field.

The book Graph Learning in Medical Imaging presents the refereed proceedings from the First International Workshop on Graph Learning in Medical Imaging (GLMI 2019), which took place in Shenzhen, China, during October 2019. This workshop was held in conjunction with the prestigious MICCAI 2019 conference, bringing together experts in the field to discuss innovative approaches and breakthroughs in medical imaging through graph learning techniques.

In total, 21 full papers were selected from a competitive pool of 42 submissions, showcasing rigorous research and original contributions to the field. The authors of these papers delve into significant trends and challenges associated with graph learning in medical imaging, exploring how these methodologies can enhance diagnostic accuracy and improve patient outcomes. The selected works reflect a diverse range of topics, from theoretical advancements to practical applications in various medical imaging modalities.

Graph Learning in Medical Imaging serves as a valuable resource for researchers, practitioners, and students alike, providing insights into cutting-edge techniques and their implications for the future of medical imaging. By compiling these proceedings, the book aims to foster collaboration and inspire further research in this rapidly evolving area, highlighting the importance of graph learning in enhancing the capabilities of medical imaging technologies.