Doug has been having disturbing dreams about his friend, Alan, who had killed himself nearly thirty years earlier. While shopping at the annual flea market one summer day, Doug is drawn to a mirror in a plain wooden frame. He brings the mirror home and hangs it in his office, the perfect place for it as far as he´s concerned. One night while sitting in front of his word processor trying to find the inspiration he desperately needs to finish his latest story, Doug sees something out of the corner of his eye and it´s moving. He´s alone in the room, but when he looks in the antique mirror, there´s Alan, big as life looking back at him. Alan´s not in the room, but his image is in the mirror. What´s going on here? Find out what kind of conversation a ghost will engage you in when you least expect it, and how it might change your life. 1. Language: English. Narrator: Chip Wood. Audio sample: http://samples.audible.de/bk/acx0/009266/bk_acx0_009266_sample.mp3. Digital audiobook in aax.
An Image Darkly Forming:Women and Initiation Bani Shorter
The Image of Women in the Short Stories of Shashi Deshpande: Priscilla Yelamanchi
Image Transference and Retrieval Over Short Messaging Service: Muhammad Fahad Khan/ Fakhra Kashif/ Saira Beg
When Jeffrey Mitchell abducted eighteen-year-old Hanna Jones, he had every intention of killing her. But now, years later, as husband and wife they play games that have only losers. Dr. White and her husband share a similar past, but when these two couples collide, only one pair can come out on top. 1. Language: English. Narrator: Christopher Eicher. Audio sample: http://samples.audible.de/bk/acx0/002932/bk_acx0_002932_sample.mp3. Digital audiobook in aax.
Salman Rushdie´s Short Story Cycle East West: A Deconstruction of the Traditional Images of Orient and Occident and a Questioning of the Inviolable:1. Auflage Jörg Vogelmann
Salman Rushdie´s Short Story Cycle East West: A Deconstruction of the Traditional Images of Orient and Occident and a Questioning of the Inviolable:Akademische Schriftenreihe. 4. Auflage Jörg Vogelmann
This book introduces the classical and modern image reconstruction technologies. It covers topics in two-dimensional (2D) parallel-beam and fan-beam imaging, three-dimensional (3D) parallel ray, parallel plane, and cone-beam imaging. Both analytical and iterative methods are presented. The applications in X-ray CT, SPECT (single photon emission computed tomography), PET (positron emission tomography), and MRI (magnetic resonance imaging) are discussed. Contemporary research results in exact region-of-interest (ROI) reconstruction with truncated projections, Katsevich´s cone-beam filtered backprojection algorithm, and reconstruction with highly under-sampled data are included. The last chapter of the book is devoted to the techniques of using a fast analytical algorithm to reconstruct an image that is equivalent to an iterative reconstruction. These techniques are the author´s most recent research results. This book is intended for students, engineers, and researchers who are interested in medical image reconstruction. Written in a non-mathematical way, this book provides an easy access to modern mathematical methods in medical imaging. Table of Content:Chapter 1 Basic Principles of Tomography1.1 Tomography1.2 Projection1.3 Image Reconstruction1.4 Backprojection1.5 Mathematical ExpressionsProblemsReferencesChapter 2 Parallel-Beam Image Reconstruction2.1 Fourier Transform2.2 Central Slice Theorem2.3 Reconstruction Algorithms2.4 A Computer Simulation2.5 ROI Reconstruction with Truncated Projections2.6 Mathematical Expressions (The Fourier Transform and Convolution , The Hilbert Transform and the Finite Hilbert Transform , Proof of the Central Slice Theorem, Derivation of the Filtered Backprojection Algorithm , Expression of the Convolution Backprojection Algorithm, Expression of the Radon Inversion Formula ,Derivation of the Backprojection-then-Filtering AlgorithmProblemsReferencesChapter 3 Fan-Beam Image Reconstruction3.1 Fan-Beam Geometry and Point Spread Function3.2 Parallel-Beam to Fan-Beam Algorithm Conversion3.3 Short Scan3.4 Mathematical Expressions (Derivation of a Filtered Backprojection Fan-Beam Algorithm, A Fan-Beam Algorithm Using the Derivative and the Hilbert Transform)ProblemsReferencesChapter 4 Transmission and Emission Tomography4.1 X-Ray Computed Tomography4.2 Positron Emission Tomography and Single Photon Emission Computed Tomography4.3 Attenuation Correction for Emission Tomography4.4 Mathematical ExpressionsProblemsReferencesChapter 5 3D Image Reconstruction5.1 Parallel Line-Integral Data5.2 Parallel Plane-Integral Data5.3 Cone-Beam Data (Feldkamp´s Algorithm, Grangeat´s Algorithm, Katsevich´s Algorithm)5.4 Mathematical Expressions (Backprojection-then-Filtering for Parallel Line-Integral Data, Filtered Backprojection Algorithm for Parallel Line-Integral Data, 3D Radon Inversion Formula, 3D Backprojection-then-Filtering Algorithm for Radon Data, Feldkamp´s Algorithm, Tuy´s Relationship, Grangeat´s Relationship, Katsevich´s Algorithm)ProblemsReferencesChapter 6 Iterative Reconstruction6.1 Solving a System of Linear Equations6.2 Algebraic Reconstruction Technique6.3 Gradient Descent Algorithms6.4 Maximum-Likelihood Expectation-Maximization Algorithms6.5 Ordered-Subset Expectation-Maximization Algorithm6.6 Noise Handling (Analytical Methods, Iterative Methods, Iterative Methods)6.7 Noise Modeling as a Likelihood Function6.8 Including Prior Knowledge6.9 Mathematical Expressions (ART, Conjugate Gradient Algorithm, ML-EM, OS-EM, Green´s One-Step Late Algorithm, Matched and Unmatched Projector/Backprojector Pairs )6.10 Reconstruction Using Highly Undersampled Data with l0 MinimizationProblemsReferencesChapter 7 MRI Reconstruction7.1 The ´M´7.2 The ´R´7.3 The ´I´; (To Obtain z-Information, x-Information, y-Information)7.4 Mathematical ExpressionsProblemsReferencesIndexing
This two-volume set LNCS 11662 and 11663 constitutes the refereed proceedings of the 16th International Conference on Image Analysis and Recognition, ICIAR 2019, held in Waterloo, ON, Canada, in August 2019. The 58 full papers presented together with 24 short and 2 poster papers were carefully reviewed and selected from 142 submissions. The papers are organized in the following topical sections: Image Processing; Image Analysis; Signal Processing Techniques for Ultrasound Tissue Characterization and Imaging in Complex Biological Media; Advances in Deep Learning; Deep Learning on the Edge; Recognition; Applications; Medical Imaging and Analysis Using Deep Learning and Machine Intelligence; Image Analysis and Recognition for Automotive Industry; Adaptive Methods for Ultrasound Beamforming and Motion Estimation.