Mathematics education in contrast has a variable and culturally based character, and this is certainly true of educational organization and practice. Educational research is both an applied social science and a multidisciplinary domain of theoretical scholarship.

Among organizations devoted to mathematics education, The International Commission on Mathematical Instruction (ICMI) is distinctive because of its close ties to the mathematics community. The great challenges now facing mathematics education around the world demand a deeper and more sensitive involvement of disciplinary mathematicians than we now have, both in the work of educational improvements and in research on the nature of teaching and learning.

This book constitutes the Proceedings of the Ninth International Conference on Mathematical Education (ICME9), which was held in Tokyo/Makuhari Japan, in July and August 2000. ICME9 brought together experts from 70 countries, working to understand the challenges of mathematics education including boundary crossing and collaboration, such as the need to reconcile language, epistemology, norms of evidence and, in general, all of the intellectual and attitudinal challenges that face multidisciplinary research and development.

The program for ICME9 reflects a truly international character and includes four distinguished regular lectures, 52 lectures, four national presentations and reports from current ICMI Studies and ICMI Affiliated Study Groups. The goal of the meeting was to offer presentations and learning on various aspects of mathematics educations; its research, experiences, materials, and information with special emphasis on achievements and trends thatarose in mathematics education during the period of 1996-2000, and that would make important contributions to mathematics education in the new century.

This book presents cutting-edge research and applications of deep learning in a broad range of medical imaging scenarios, such as computer-aided diagnosis, image segmentation, tissue recognition and classification, and other areas of medical and healthcare problems. Each of its chapters covers a topic in depth, ranging from medical image synthesis and techniques for muskuloskeletal analysis to diagnostic tools for breast lesions on digital mammograms and glaucoma on retinal fundus images. It also provides an overview of deep learning in medical image analysis and highlights issues and challenges encountered by researchers and clinicians, surveying and discussing practical approaches in general and in the context of specific problems. Academics, clinical and industry researchers, as well as young researchers and graduate students in medical imaging, computer-aided-diagnosis, biomedical engineering and computer vision will find this book a great reference and very useful learning resource.

In these meetings, which were held in honour of Professor Tosio Kato on his retirement, the focus was on the interplay of functional analysis and partial differential equations. Thus, the study of Schrodinger operators, from the viewpoints of evolution equations and spectral theory, is one major subject, while functional analytic studies of nonlinear PDEs, including Navier-Stokes, KdV and other equations, constitutes another main theme. Papers on these linear and nonlinear problems are linked through their methods and types of approach.

This book presents cutting-edge research and applications of deep learning in a broad range of medical imaging scenarios, such as computer-aided diagnosis, image segmentation, tissue recognition and classification, and other areas of medical and healthcare problems. Each of its chapters covers a topic in depth, ranging from medical image synthesis and techniques for muskuloskeletal analysis to diagnostic tools for breast lesions on digital mammograms and glaucoma on retinal fundus images. It also provides an overview of deep learning in medical image analysis and highlights issues and challenges encountered by researchers and clinicians, surveying and discussing practical approaches in general and in the context of specific problems. Academics, clinical and industry researchers, as well as young researchers and graduate students in medical imaging, computer-aided-diagnosis, biomedical engineering and computer vision will find this book a great reference and very useful learning resource.

This book constitutes the refereed proceedings of the 12th International Workshop on Breast Imaging, IWDM 2014, held in Gifu City, Japan, in June/July 2014. The 24 revised full papers and 73 revised poster papers presented together with 6 invited talks were carefully reviewed and selected from 122 submissions. The papers are organized in topical sections on screening outcomes, ultrasound, breast density, imaging physics, CAD, tomosynthesis and ICT and image processing.