This book constitutes the refeered proceedings of the 18th Interational Conference on Information Processing in Medical Imaging, IPMI 2003, held in UK, in July 2003. The 57 revised full papers presented were carefully reviewed and selected from submissions. The papers are organized in topical sections shape modeling, shape analysis, segmentation, color, performance characterization, registration and modeling similarity, registration and modeling deformation, cardiac motion, fMRI analysis, and diffusion imaging and tractography.
Each chapter in the book is an individual project and each project is constructed with step-by-step instructions, clearly explained code, and includes the necessary screenshots. You should have basic OpenCV and C/C++ programming experience before reading this book, as it is aimed at Computer Science graduates, researchers, and computer vision experts widening their expertise.
Active Contours deals with the analysis of moving images - a topic of growing importance within the computer graphics industry. In particular it is concerned with understanding, specifying and learning prior models of varying strength and applying them to dynamic contours. Its aim is to develop and analyse these modelling tools in depth and within a consistent framework.
The 6th International Conference on Medical Imaging and Computer-Assisted Intervention,MICCAI2003,washeldinMontr ́ eal,Qu ́ ebec,CanadaattheF- rmont Queen Elizabeth Hotel during November 15–18, 2003. This was the ?rst time the conference had been held in Canada. The proposal to host MICCAI 2003 originated from discussions within the Ontario Consortium for Ima- guided Therapy and Surgery, a multi-institutional research consortium that was supported by the Government of Ontario through the Ontario Ministry of E- erprise, Opportunity and Innovation. The objective of the conference was to o?er clinicians and scientists a - rum within which to exchange ideas in this exciting and rapidly growing ?eld. MICCAI 2003 encompassed the state of the art in computer-assisted interv- tions, medical robotics, and medical-image processing, attracting experts from numerous multidisciplinary professions that included clinicians and surgeons, computer scientists, medical physicists, and mechanical, electrical and biome- cal engineers. The quality and quantity of submitted papers were most impressive. For MICCAI 2003 we received a record 499 full submissions and 100 short c- munications. All full submissions, of 8 pages each, were reviewed by up to 5 reviewers, and the 2-page contributions were assessed by a small subcomm- tee of the Scienti?c Review Committee. All reviews were then considered by the MICCAI 2003 Program Committee, resulting in the acceptance of 206 full papers and 25 short communications. The normal mode of presentation at MICCAI 2003 was as a poster; in addition, 49 papers were chosen for oral presentation.
The four-volume set LNCS 7724--7727 constitutes the thoroughly refereed post-conference proceedings of the 11th Asian Conference on Computer Vision, ACCV 2012, held in Daejeon, Korea, in November 2012. The total of 226 contributions presented in these volumes was carefully reviewed and selected from 869 submissions. The papers are organized in topical sections on object detection, learning and matching; object recognition; feature, representation, and recognition; segmentation, grouping, and classification; image representation; image and video retrieval and medical image analysis; face and gesture analysis and recognition; optical flow and tracking; motion, tracking, and computational photography; video analysis and action recognition; shape reconstruction and optimization; shape from X and photometry; applications of computer vision; low-level vision and applications of computer vision.
Abstract Biological vision is a rather fascinating domain of research. Scientists of various origins like biology, medicine, neurophysiology, engineering, math ematics, etc. aim to understand the processes leading to visual perception process and at reproducing such systems. Understanding the environment is most of the time done through visual perception which appears to be one of the most fundamental sensory abilities in humans and therefore a significant amount of research effort has been dedicated towards modelling and repro ducing human visual abilities. Mathematical methods play a central role in this endeavour. Introduction David Marr's theory v^as a pioneering step tov^ards understanding visual percep tion. In his view human vision was based on a complete surface reconstruction of the environment that was then used to address visual subtasks. This approach was proven to be insufficient by neuro-biologists and complementary ideas from statistical pattern recognition and artificial intelligence were introduced to bet ter address the visual perception problem. In this framework visual perception is represented by a set of actions and rules connecting these actions. The emerg ing concept of active vision consists of a selective visual perception paradigm that is basically equivalent to recovering from the environment the minimal piece information required to address a particular task of interest.
This book constitutes the proceedings of the Workshop on Shape in Medical Imaging, ShapeMI 2018, held in conjunction with the 21st International Conference on Medical Image Computing, MICCAI 2018, in Granada, Spain, in September 2018. The 26 full papers and 2 short papers presented were carefully reviewed and selected for inclusion in this volume. The papers discuss novel approaches and applications in shape and geometry processing and their use in research and clinical studies and explore novel, cutting-edge theoretical methods and their usefulness for medical applications, e.g., from the fields of geometric learning or spectral shape analysis.
Recent years have seen dramatic progress in shape recognition algorithms applied to ever-growing image databases. They have been applied to image stitching, stereo vision, image mosaics, solid object recognition and video or web image retrieval. More fundamentally, the ability of humans and animals to detect and recognize shapes is one of the enigmas of perception. The book describes a complete method that starts from a query image and an image database and yields a list of the images in the database containing shapes present in the query image. A false alarm number is associated to each detection. Many experiments will show that familiar simple shapes or images can reliably be identified with false alarm numbers ranging from 10-5 to less than 10-300. Technically speaking, there are two main issues. The first is extracting invariant shape descriptors from digital images. Indeed, a shape can be seen from various angles and distances and in various lights.
