​Ricci Flow for Shape Analysis and Surface Registration introduces the beautiful and profound Ricci flow theory in a discrete setting. By using basic tools in linear algebra and multivariate calculus, readers can deduce all the major theorems in surface​ Ricci flow by themselves. The authors adapt the Ricci flow theory to practical computational algorithms, apply Ricci flow for shape analysis and surface registration, and demonstrate the power of Ricci flow in many applications in medical imaging, computer graphics, computer vision and wireless sensor network. Due to minimal pre-requisites, this book is accessible to engineers and medical experts, including educators, researchers, students and industry engineers who have an interest in solving real problems related to shape analysis and surface registration.

This handbook gathers together the state of the art on mathematical models and algorithms for imaging and vision. Its emphasis lies on rigorous mathematical methods, which represent the optimal solutions to a class of imaging and vision problems, and on effective algorithms, which are necessary for the methods to be translated to practical use in various applications. Viewing discrete images as data sampled from functional surfaces enables the use of advanced tools from calculus, functions and calculus of variations, and nonlinear optimization, and provides the basis of high-resolution imaging through geometry and variational models. Besides, optimization naturally connects traditional model-driven approaches to the emerging data-driven approaches of machine and deep learning. No other framework can provide comparable accuracy and precision to imaging and vision. Written by leading researchers in imaging and vision, the chapters in this handbook all start with gentle introductions, which make this work accessible to graduate students. For newcomers to the field, the book provides a comprehensive and fast-track introduction to the content, to save time and get on with tackling new and emerging challenges. For researchers, exposure to the state of the art of research works leads to an overall view of the entire field so as to guide new research directions and avoid pitfalls in moving the field forward and looking into the next decades of imaging and information services. This work can greatly benefit graduate students, researchers, and practitioners in imaging and vision; applied mathematicians; medical imagers; engineers; and computer scientists.

The seven-volume set LNCS 12261, 12262, 12263, 12264, 12265, 12266, and 12267 constitutes the refereed proceedings of the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, held in Lima, Peru, in October 2020. The conference was held virtually due to the COVID-19 pandemic. The 542 revised full papers presented were carefully reviewed and selected from 1809 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: machine learning methodologies Part II: image reconstruction; prediction and diagnosis; cross-domain methods and reconstruction; domain adaptation; machine learning applications; generative adversarial networks Part III: CAI applications; image registration; instrumentation and surgical phase detection; navigation and visualization; ultrasound imaging; video image analysis Part IV: segmentation; shape models and landmark detection Part V: biological, optical, microscopic imaging; cell segmentation and stain normalization; histopathology image analysis; opthalmology Part VI: angiography and vessel analysis; breast imaging; colonoscopy; dermatology; fetal imaging; heart and lung imaging; musculoskeletal imaging Part VI: brain development and atlases; DWI and tractography; functional brain networks; neuroimaging; positron emission tomography

The three-volume set LNCS 7510, 7511, and 7512 constitutes the refereed proceedings of the 15th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2012, held in Nice, France, in October 2012. Based on rigorous peer reviews, the program committee carefully selected 252 revised papers from 781 submissions for presentation in three volumes. The second volume includes 82 papers organized in topical sections on cardiovascular imaging: planning, intervention and simulation; image registration; neuroimage analysis; diffusion weighted imaging; image segmentation; computer-assisted interventions and robotics; and image registration: new methods and results.

The book covers novel strategies of state of the art in engineering and clinical analysis and approaches for analyzing abdominal imaging, including lung, mediastinum, pleura, liver, kidney and gallbladder. In the last years the imaging techniques have experienced a tremendous improvement in the diagnosis and characterization of the pathologies that affect abdominal organs. In particular, the introduction of extremely fast CT scanners and high Magnetic field MR Systems allow imaging with an exquisite level of detail the anatomy and pathology of liver, kidney, pancreas, gallbladder as well as lung and mediastinum. Moreover, thanks to the development of powerful computer hardware and advanced mathematical algorithms the quantitative and automated\semi automated diagnosis of the pathology is becoming a reality. Medical image analysis plays an essential role in the medical imaging field, including computer-aided diagnosis, organ/lesion segmentation, image registration, and image-guided therapy. This book will cover all the imaging techniques, potential for applying such imaging clinically, and offer present and future applications as applied to the abdomen and thoracic imaging with the most world renowned scientists in these fields. The main aim of this book is to help advance scientific research within the broad field of abdominal imaging. This book focuses on major trends and challenges in this area, and it presents work aimed to identify new techniques and their use in medical imaging analysis for abdominal imaging. ​

This book constitutes the refereed proceedings of the Second International Workshop on Multimodal Brain Image Analysis, held in conjunction with MICCAI 2012, in Nice, France, in October 2012. The 19 revised full papers presented were carefully reviewed and selected from numerous submissions. The objective of this workshop is to forward the state of the art in analysis methodologies, algorithms, software systems, validation approaches, benchmark datasets, neuroscience, and clinical applications.

This book discusses the computational geometry, topology and physics of digital images and video frame sequences. This trio of computational approaches encompasses the study of shape complexes, optical vortex nerves and proximities embedded in triangulated video frames and single images, while computational geometry focuses on the geometric structures that infuse triangulated visual scenes. The book first addresses the topology of cellular complexes to provide a basis for an introductory study of the computational topology of visual scenes, exploring the fabric, shapes and structures typically found in visual scenes. The book then examines the inherent geometry and topology of visual scenes, and the fine structure of light and light caustics of visual scenes, which bring into play catastrophe theory and the appearance of light caustic folds and cusps. Following on from this, the book introduces optical vortex nerves in triangulated digital images. In this context, computational physics is synonymous with the study of the fine structure of light choreographed in video frames. This choreography appears as a sequence of snapshots of light reflected and refracted from surface shapes, providing a solid foundation for detecting, analyzing and classifying visual scene shapes.