Images In Series

fMRI is a very popular method for researchers and clinicians to image human brain activity in response to given mental tasks. This book presents a comprehensive review of the methods for computing activity maps, while providing an intuitive and mathematical outline of how each method works. The approaches include statistical parametric maps (SPM), hemodynamic response modeling and deconvolution, Bayesian, Fourier and nonparametric methods. The newest activity maps provide information on regional connectivity and include principal and independent component analysis, crisp and fuzzy clustering, structural equation modeling, and dynamic causal modeling. Preprocessing and experimental design issues are discussed with references made to the software available for implementing the various methods. Aimed at graduate students and researchers, it will appeal to anyone with an interest in fMRI and who is looking to expand their perspectives of this technique.

This is the resource you've been waiting for. Tailored specifically to those in "party plan" direct selling businesses, Social Media for Direct Selling Representatives is the first volume in a series of books to help you accelerate your business using social media marketing as a vibrant part of your overall marketing plan. Based on 18 years' experience in the field and working with companies, this book was written by someone with the technical expertise to know what works, and the industry knowledge to explain it in a way that makes sense.

This book constitutes the refereed proceedings of the 15th International Conference on Image Analysis and Processing, ICIAP 2009, held in Vietri sul Mare, Italy, in September 2009. The 107 revised full papers presented together with 3 invited papers were carefully reviewed and selected from 168 submissions. The papers are organized in topical sections on computer graphics and image processing, low and middle level processing, 2D and 3D segmentation, feature extraction and image analysis, object detection and recognition, video analysis and processing, pattern analysis and classification, learning, graphs and trees, applications, shape analysis, face analysis, medical imaging, and image analysis and pattern recognition.

An insightful look at the arguments for and against universal adoption of a vegan diet and lifestyle. As concern grows over the environmental costs and ethical implications of intensive factory farming, an increasing number of people are embracing diets and lifestyles free from animal products. Should We All Be Vegan? gives a fluid and engaging account of the evolution of veganism. Over the course of four easily digestible chapters, food writer Molly Watson reveals the truth about veganism’s impact on our health, the planet, and the global economy. Chapters like “The Evolution of Veganism” and “Why Go Vegan Today?” examine the development of veganism from the earliest meat-free human diets to the rise in mainstream adoption of a plant-based diet and lifestyle today; “The Challenges of Veganism” surveys the nutritional and societal pitfalls of a vegan lifestyle; and, lastly “A Vegan Planet” envisions possible futures for veganism and their impact on the earth. Watson evaluates every angle of the debate on veganism in this primer, reviewing the evidence for its effects on health and assessing the ethics, environmental impact, and feasibility of adopting a vegan lifestyle worldwide.

Several recent papers underline methodological points that limit the validity of published results in imaging studies in the life sciences and especially the neurosciences (Carp, 2012; Ingre, 2012; Button et al., 2013; Ioannidis, 2014). At least three main points are identified that lead to biased conclusions in research findings: endemic low statistical power and, selective outcome and selective analysis reporting. Because of this, and in view of the lack of replication studies, false discoveries or solutions persist. To overcome the poor reliability of research findings, several actions should be promoted including conducting large cohort studies, data sharing and data reanalysis. The construction of large-scale online databases should be facilitated, as they may contribute to the definition of a “collective mind” (Fox et al., 2014) facilitating open collaborative work or “crowd science” (Franzoni and Sauermann, 2014). Although technology alone cannot change scientists’ practices (Wicherts et al., 2011; Wallis et al., 2013, Poldrack and Gorgolewski 2014; Roche et al. 2014), technical solutions should be identified which support a more “open science” approach. Also, the analysis of the data plays an important role. For the analysis of large datasets, image processing pipelines should be constructed based on the best algorithms available and their performance should be objectively compared to diffuse the more relevant solutions. Also, provenance of processed data should be ensured (MacKenzie-Graham et al., 2008). In population imaging this would mean providing effective tools for data sharing and analysis without increasing the burden on researchers. This subject is the main objective of this research topic (RT), cross-listed between the specialty section “Computer Image Analysis” of Frontiers in ICT and Frontiers in Neuroinformatics. Firstly, it gathers works on innovative solutions for the management of large imaging datasets possibly distributed in various centers. The paper of Danso et al. describes their experience with the integration of neuroimaging data coming from several stroke imaging research projects. They detail how the initial NeuroGrid core metadata schema was gradually extended for capturing all information required for future metaanalysis while ensuring semantic interoperability for future integration with other biomedical ontologies. With a similar preoccupation of interoperability, Shanoir relies on the OntoNeuroLog ontology (Temal et al., 2008; Gibaud et al., 2011; Batrancourt et al., 2015), a semantic model that formally described entities and relations in medical imaging, neuropsychological and behavioral assessment domains. The mechanism of “Study Card” allows to seamlessly populate metadata aligned with the ontology, avoiding fastidious manual entrance and the automatic control of the conformity of imported data with a predefined study protocol. The ambitious objective with the BIOMIST platform is to provide an environment managing the entire cycle of neuroimaging data from acquisition to analysis ensuring full provenance information of any derived data. Interestingly, it is conceived based on the product lifecycle management approach used in industry for managing products (here neuroimaging data) from inception to manufacturing. Shanoir and BIOMIST share in part the same OntoNeuroLog ontology facilitating their interoperability. ArchiMed is a data management system locally integrated for 5 years in a clinical environment. Not restricted to Neuroimaging, ArchiMed deals with multi-modal and multi-organs imaging data with specific considerations for data long-term conservation and confidentiality in accordance with the French legislation. Shanoir and ArchiMed are integrated into FLI-IAM1, the national French IT infrastructure for in vivo imaging.

Consistently rated as the best overall introduction to computer-based image processing, The Image Processing Handbook covers two-dimensional (2D) and three-dimensional (3D) imaging techniques, image printing and storage methods, image processing algorithms, image and feature measurement, quantitative image measurement analysis, and more. Incorporating image processing and analysis examples at all scales, from nano- to astro-, this Seventh Edition: Features a greater range of computationally intensive algorithms than previous versions Provides better organization, more quantitative results, and new material on recent developments Includes completely rewritten chapters on 3D imaging and a thoroughly revamped chapter on statistical analysis Contains more than 1700 references to theory, methods, and applications in a wide variety of disciplines Presents 500+ entirely new figures and images, with more than two-thirds appearing in color The Image Processing Handbook, Seventh Edition delivers an accessible and up-to-date treatment of image processing, offering broad coverage and comparison of algorithms, approaches, and outcomes.

Convergent Journalism: An Introduction is the pioneering textbook on practicing journalism in the 21st century, now in its third edition, offering chapters by industry experts covering key components for today’s convergenced media landscape. Each chapter of this book is written by an expert in the field, offering practical and key skills for the different aspects that make up the practice of journalism today. This new edition, written from the ground up, shifts the discussion toward a model of responsible and audience-centric journalism and demonstrates the ways journalists can use new media tools as both senders and receivers. The bedrock tenets of journalism remain at the core of this book, including information dissemination, storytelling, and audience engagement. This book offers readers: • A number of pedagogical features to improve learning and retention, including examples, exercises, breakout boxes and more • Coverage of additional topics such as issues of law and ethics in digital media, and also writing for mobile platforms and social media • Individual chapters written by subject experts, giving readers the necessary know-how for converged media by proven leaders in the field Students looking for the practical skills and ethical background necessary for producing journalism in the contemporary media landscape will find this book an invaluable resource. It is perfect for students in courses such as Convergent Journalism, Digital Media, Online Journalism, and Multimedia Journalism.

Describes the deblurring algorithms and techniques collectively known as spectral filtering methods, in which the singular value decomposition, or a similar decomposition with spectral properties, is used to introduce the necessary regularization or filtering in the reconstructed image. The concise MATLAB® implementations described in the book provide a template of techniques that can be used to restore blurred images from many applications.