Landmark Based Image Analysis PDF Download
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Author | : Karl Rohr |
Publisher | : Springer Science & Business Media |
Total Pages | : 314 |
Release | : 2013-03-14 |
Genre | : Computers |
ISBN | : 9401597871 |
Download Landmark-Based Image Analysis Book in PDF, ePub and Kindle
Landmarks are preferred image features for a variety of computer vision tasks such as image mensuration, registration, camera calibration, motion analysis, 3D scene reconstruction, and object recognition. Main advantages of using landmarks are robustness w. r. t. lightning conditions and other radiometric vari ations as well as the ability to cope with large displacements in registration or motion analysis tasks. Also, landmark-based approaches are in general com putationally efficient, particularly when using point landmarks. Note, that the term landmark comprises both artificial and natural landmarks. Examples are comers or other characteristic points in video images, ground control points in aerial images, anatomical landmarks in medical images, prominent facial points used for biometric verification, markers at human joints used for motion capture in virtual reality applications, or in- and outdoor landmarks used for autonomous navigation of robots. This book covers the extraction oflandmarks from images as well as the use of these features for elastic image registration. Our emphasis is onmodel-based approaches, i. e. on the use of explicitly represented knowledge in image analy sis. We principally distinguish between geometric models describing the shape of objects (typically their contours) and intensity models, which directly repre sent the image intensities, i. e. ,the appearance of objects. Based on these classes of models we develop algorithms and methods for analyzing multimodality im ages such as traditional 20 video images or 3D medical tomographic images.
Author | : K. C. Santosh |
Publisher | : Springer |
Total Pages | : 543 |
Release | : 2019-07-15 |
Genre | : Computers |
ISBN | : 981139184X |
Download Recent Trends in Image Processing and Pattern Recognition Book in PDF, ePub and Kindle
This three-book set constitutes the refereed proceedings of the Second International Conference on Recent Trends in Image Processing and Pattern Recognition (RTIP2R) 2018, held in Solapur, India, in December 2018. The 173 revised full papers presented were carefully reviewed and selected from 374 submissions. The papers are organized in topical sections in the tree volumes. Part I: computer vision and pattern recognition; machine learning and applications; and image processing. Part II: healthcare and medical imaging; biometrics and applications. Part III: document image analysis; image analysis in agriculture; and data mining, information retrieval and applications.
Author | : S. Smys |
Publisher | : Springer Nature |
Total Pages | : 877 |
Release | : 2022-03-30 |
Genre | : Technology & Engineering |
ISBN | : 9811695733 |
Download Computational Vision and Bio-Inspired Computing Book in PDF, ePub and Kindle
This book includes selected papers from the 5th International Conference on Computational Vision and Bio Inspired Computing (ICCVBIC 2021), held in Coimbatore, India, during November 25–26, 2021. This book presents state-of-the-art research innovations in computational vision and bio-inspired techniques. The book reveals the theoretical and practical aspects of bio-inspired computing techniques, like machine learning, sensor-based models, evolutionary optimization and big data modeling and management that make use of effectual computing processes in the bio-inspired systems. It also contributes to the novel research that focuses on developing bio-inspired computing solutions for various domains, such as human–computer interaction, image processing, sensor-based single processing, recommender systems and facial recognition, which play an indispensable part in smart agriculture, smart city, biomedical and business intelligence applications.
Author | : Tapan K. Gandhi |
Publisher | : Academic Press |
Total Pages | : 308 |
Release | : 2020-08-11 |
Genre | : Computers |
ISBN | : 0128192968 |
Download Advanced Machine Vision Paradigms for Medical Image Analysis Book in PDF, ePub and Kindle
Computer vision and machine intelligence paradigms are prominent in the domain of medical image applications, including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics. Medical image analysis and understanding are daunting tasks owing to the massive influx of multi-modal medical image data generated during routine clinal practice. Advanced computer vision and machine intelligence approaches have been employed in recent years in the field of image processing and computer vision. However, due to the unstructured nature of medical imaging data and the volume of data produced during routine clinical processes, the applicability of these meta-heuristic algorithms remains to be investigated. Advanced Machine Vision Paradigms for Medical Image Analysis presents an overview of how medical imaging data can be analyzed to provide better diagnosis and treatment of disease. Computer vision techniques can explore texture, shape, contour and prior knowledge along with contextual information, from image sequence and 3D/4D information which helps with better human understanding. Many powerful tools have been developed through image segmentation, machine learning, pattern classification, tracking, and reconstruction to surface much needed quantitative information not easily available through the analysis of trained human specialists. The aim of the book is for medical imaging professionals to acquire and interpret the data, and for computer vision professionals to learn how to provide enhanced medical information by using computer vision techniques. The ultimate objective is to benefit patients without adding to already high healthcare costs. Explores major emerging trends in technology which are supporting the current advancement of medical image analysis with the help of computational intelligence Highlights the advancement of conventional approaches in the field of medical image processing Investigates novel techniques and reviews the state-of-the-art in the areas of machine learning, computer vision, soft computing techniques, as well as their applications in medical image analysis
Author | : Alexander Blair Powers |
Publisher | : |
Total Pages | : 0 |
Release | : 2021 |
Genre | : Diagnostic imaging |
ISBN | : |
Download Anatomical Landmark Detection Leveraging Implicit and Explicit Information Sharing Techniques Book in PDF, ePub and Kindle
Anatomical landmark detection is an essential step in various medical imaging processes, including morphological analysis, inter-/intra-subject registration, and, fundamentally, anatomy orientation. Deep reinforcement learning (DRL) has shown promise in replacing heuristic methods and classical image processing approaches to landmark detection. In this work, we propose multiple extensions of a multi-agent deep q-network approach to anatomical landmark detection. We first improve the localization of high confidence primary landmarks by searching in the physical space coordinate system of the image rather than voxel space. Second, when detecting a large number of landmarks, we decompose the detection process into two stages to compensate for the memory limitations induced by detecting a large number of landmarks.
Author | : Kevin Lynch |
Publisher | : MIT Press |
Total Pages | : 212 |
Release | : 1964-06-15 |
Genre | : Architecture |
ISBN | : 9780262620017 |
Download The Image of the City Book in PDF, ePub and Kindle
The classic work on the evaluation of city form. What does the city's form actually mean to the people who live there? What can the city planner do to make the city's image more vivid and memorable to the city dweller? To answer these questions, Mr. Lynch, supported by studies of Los Angeles, Boston, and Jersey City, formulates a new criterion—imageability—and shows its potential value as a guide for the building and rebuilding of cities. The wide scope of this study leads to an original and vital method for the evaluation of city form. The architect, the planner, and certainly the city dweller will all want to read this book.
Author | : Binh Pham |
Publisher | : |
Total Pages | : 234 |
Release | : 1999 |
Genre | : Medical |
ISBN | : |
Download New Approaches in Medical Image Analysis Book in PDF, ePub and Kindle
Author | : Richard Baldock |
Publisher | : OUP Oxford |
Total Pages | : 322 |
Release | : 1999-12-09 |
Genre | : Science |
ISBN | : 0191565814 |
Download Image Processing and Analysis Book in PDF, ePub and Kindle
A wide range of books on image processing and analysis provide comprehensive descriptions of mathematics and algorithms for image processing practitioners, or introductory material for engineering students. This volume is different in addressing the topic from the point of view of the "user". Standard algorithms, procedures and rules of thumb are explained in the context of successful application to biological or medical images. Early chapters cover the basic topics of image acquisition, processing, analysis and pattern recognition. Much of the explanation is in the form of protocols, which should equip the user in the biological or earth sciences with the background for informed use of image processing software, and sufficient knowledge to write their own programmes if they feel moved to do so. More advanced techniques in the use of explicit models and analysis of 3D images are covered in later chapters, also with reference to specific applications. The coverage of these is not exhaustive, but may inspire the reader to consider applying image analysis to problems beyond those tackled by commercial packages.
Author | : Yutaka Takeuchi |
Publisher | : |
Total Pages | : 16 |
Release | : 1998 |
Genre | : Computer vision |
ISBN | : |
Download Evaluation of Image-based Landmark Recognition Techniques Book in PDF, ePub and Kindle
Abstract: "Recognizing landmarks in sequences of images is a challenging problem for a number of reasons. First of all, the appearance of any given landmark varies substantially from one observation to the next. In addition to variations due to different aspects, an illumination change, external clutter, and changing geometry of the imaging devices are other factors affecting the variability of the observed landmarks. Finally, it is typically difficult to make use of accurate 3D information in landmark recognition applications. For those reasons, it is not possible to use many of the object recognition techniques based on strong geometric models. The alternative is to use image-based techniques in which landmarks are represented by collections of images which capture the 'typical' appearance of the object. The information most relevant to recognition is extracted from the collection of raw images and used as the model for recognition. This process is often referred to as 'visual learning.' Models of landmarks are acquired from image sequences and later recognized for vehicle localization in urban environments. In the acquisition phase, a vehicle drives and collects images of an unknown area. The algorithm organizes these images into groups with similar image features. The feature distribution for each group describes a landmark. In the recognition phase, while navigating through the same general area, the vehicle collects new images. The algorithm classifies these images into one of the learned groups, thus recognizing a landmark. Unlike computationally intensive model-based approaches that build models from known objects observed in isolation, our image-based approach automatically learns the most salient landmarks in complex environments. It delivers a robust performance under a wide range of lighting and imaging angle variations."
Author | : David Wilson |
Publisher | : Springer Science & Business Media |
Total Pages | : 583 |
Release | : 2007-04-25 |
Genre | : Medical |
ISBN | : 0306486083 |
Download Handbook of Biomedical Image Analysis Book in PDF, ePub and Kindle
Our goal is to develop automated methods for the segmentation of thr- dimensional biomedical images. Here, we describe the segmentation of c- focal microscopy images of bee brains (20 individuals) by registration to one or several atlas images. Registration is performed by a highly parallel imp- mentation of an entropy-based nonrigid registration algorithm using B-spline transformations. We present and evaluate different methods to solve the cor- spondence problem in atlas based registration. An image can be segmented by registering it to an individual atlas, an average atlas, or multiple atlases. When registering to multiple atlases, combining the individual segmentations into a ?nalsegmentationcanbeachievedbyatlasselection,ormulticlassi?erdecision fusion. Wedescribeallthesemethodsandevaluatethesegmentationaccuracies that they achieve by performing experiments with electronic phantoms as well as by comparing their outputs to a manual gold standard. The present work is focused on the mathematical and computational t- ory behind a technique for deformable image registration termed Hyperelastic Warping, and demonstration of the technique via applications in image regist- tion and strain measurement. The approach combines well-established prin- ples of nonlinear continuum mechanics with forces derived directly from thr- dimensional image data to achieve registration. The general approach does not require the de?nition of landmarks, ?ducials, or surfaces, although it can - commodate these if available. Representative problems demonstrate the robust and ?exible nature of the approach. Three-dimensional registration methods are introduced for registering MRI volumes of the pelvis and prostate. The chapter ?rst reviews the applications, xi xii Preface challenges, and previous methods of image registration in the prostate.