Throughout the greater part of the twentieth century, both in the analytic and continental traditions, metaphysics was deemed to be passe. The last few decades, however, have witnessed a remarkable growth of interest among analytic philosophers in various traditional metaphysical topics, such as modality, truth, causality, etc. which resulted in the emergence of various forms of analytic metaphysics. The new forms of metaphysics differ from its traditional forms mostly in their methodology (we may notice various applications of contemporary formal logical techniques) and in the range of proposed solutions to particular problems. Besides these and other differences, however, there are also many similarities and there are even some who intentionally develop traditional metaphysical themes using the contemporary analytical methods. All these developments call for detailed exploration, which is the general goal of the present publication Metaphysics: Aristotelian, Scholastic, Analytic. The publication is the fruit of the conference which took place in Prague in 2010 and which had for its aim to bring together those willing to explore relations between the traditional and contemporary concerns, both from among the leading analytic philosophers working in metaphysics and the historians of philosophy devoted to the study of the metaphysical tradition. The specific focus of the conference was a re-examination of topics such as categories, metaphysical structure, substance and accident, existence, modalities, and predication."

Biomedical Image Synthesis and Simulation: Methods and Applications presents the basic concepts and applications in image-based simulation and synthesis used in medical and biomedical imaging. The first part of the book introduces and describes the simulation and synthesis methods that were developed and successfully used within the last twenty years, from parametric to deep generative models. The second part gives examples of successful applications of these methods. Both parts together form a book that gives the reader insight into the technical background of image synthesis and how it is used, in the particular disciplines of medical and biomedical imaging. The book ends with several perspectives on the best practices to adopt when validating image synthesis approaches, the crucial role that uncertainty quantification plays in medical image synthesis, and research directions that should be worth exploring in the future.

This book constitutes the refereed proceedings of the 7th International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2022, held in conjunction with MICCAI 2022, in Singapore, Singapore in September 2022.

This book constitutes the refereed proceedings of the 6th International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2021, held in conjunction with MICCAI 2021, in Strasbourg, France, in September 2021.*The 14 full papers presented were carefully reviewed and selected from 18 submissions. The contributions span the following broad categories in alignment with the initial call-for-papers: methods based on generative models or adversarial learning for MRI/CT/ microscopy image synthesis, and several applications of image synthesis and simulation for data augmentation, image enhancement, or segmentation. *The workshop was held virtually.

This book constitutes the refereed proceedings of the 5th International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020. The 19 full papers presented were carefully reviewed and selected from 27 submissions. The contributions span the following broad categories in alignment with the initial call-for-papers: methods based on generative models or adversarial learning for MRI/CT/PET/microscopy image synthesis, and several applications of image synthesis and simulation for data augmentation, image enhancement or segmentation.

This book constitutes the refereed proceedings of the 4th International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019.The 16 full papers presented were carefully reviewed and selected from 21 submissions. The contributions span the following broad categories in alignment with the initial call-for-papers: methods based on generative models or adversarial learning for MRI/CT/PET/microscopy image synthesis, image super resolution, and several applications of image synthesis and simulation for data augmentation, segmentation or lesion detection.