Evaluation of a geometrical autofocus algorithm within the framework of Fast Factorized Back-Projection

2012 ◽  
Author(s):  
H. Hellsten ◽  
A. Åhlander ◽  
J. Torgrimsson ◽  
L.M.H. Ulander ◽  
P. Dammert
Keyword(s):  
Back Projection ◽  
Autofocus Algorithm

A linearity test for thick specimens imaged by HVEM over a 180° angular range

1991 ◽  
Vol 49 ◽  
pp. 552-553
Author(s):  
Yu Liu
Keyword(s):  
Phase Contrast ◽  
Three Dimensional ◽  
Angular Range ◽  
Two Dimensional ◽  
Back Projection ◽  
Line Integral ◽  
Exponential Law ◽  
Transmission Electron ◽  
Absorption Law ◽  
Linearity Test

The image obtained in a transmission electron microscope is the two-dimensional projection of a three-dimensional (3D) object. The 3D reconstruction of the object can be calculated from a series of projections by back-projection, but this algorithm assumes that the image is linearly related to a line integral of the object function. However, there are two kinds of contrast in electron microscopy, scattering and phase contrast, of which only the latter is linear with the optical density (OD) in the micrograph. Therefore the OD can be used as a measure of the projection only for thin specimens where phase contrast dominates the image. For thick specimens, where scattering contrast predominates, an exponential absorption law holds, and a logarithm of OD must be used. However, for large thicknesses, the simple exponential law might break down due to multiple and inelastic scattering.

PEMBELAJARAN SIMULASI PENCITRAAN CT DENGAN MENGGUNAKAN PRINSIP REKONSTRUKSI CITRA DALAM SOFTWARE MATLAB

2015 ◽  
Vol 8 (3) ◽  
pp. 161
Author(s):  
Samuel Gideon
Keyword(s):  
Image Reconstruction ◽  
Ct Imaging ◽  
The Body ◽  
Reconstruction Technique ◽  
Imaging Features ◽  
Back Projection ◽  
Cross Sectional ◽  
Low Contrast ◽  
Image Reconstruction Technique ◽  
Imaging Algorithms

This research was conducted as a learning alternatives for study of CT (computed tomograpghy) imaging using image reconstruction technique which are inversion matrix, back projection and filtered back projection. CT imaging can produce images of objects that do not overlap. Objects more easily distinguishable although given the relatively low contrast. The image is generated on CT imaging is the result of reconstruction of the original object. Matlab allows us to create and write imaging algorithms easily, easy to undersand and gives applied and exciting other imaging features. In this study, an example cross-sectional image recon-struction performed on the body of prostate tumors using. With these methods, medical prac-titioner (such as oncology clinician, radiographer and medical physicist) allows to simulate the reconstruction of CT images which almost resembles the actual CT visualization techniques.Keywords : computed tomography (CT), image reconstruction, Matlab

Weighted Minimum Entropy Autofocus Algorithm for ISAR Imaging

2011 ◽  
Vol 33 (8) ◽  
pp. 1809-1815
Author(s):  
Gang Xu ◽  
Lei Yang ◽  
Lei Zhang ◽  
Ya-chao Li ◽  
Meng-dao Xing
Keyword(s):  
Minimum Entropy ◽  
Isar Imaging ◽  
Autofocus Algorithm

Gender from Latin to Romance

2018 ◽  
Author(s):  
Michele Loporcaro
Keyword(s):  
Grammatical Gender ◽  
Concurrent Systems ◽  
Fundamental Question ◽  
Romance Languages ◽  
Back Projection ◽  
Linguistic Typology ◽  
Romance Language ◽  
Dialect Variation ◽  
Main Culprit ◽  
Gender System

The book addresses grammatical gender in Romance, and its development from Latin. It works with the toolbox of current linguistic typology, and asks the fundamental question of how the Latin grammatical gender system gradually changed into those of the Romance languages. To answer this question, the book capitalizes on the pervasive dialect variation of which the better-known standard Romance languages only represent a fragment. Indeed, inspection of dialect variation across time and space forces one to dismiss the handbook account proclaiming that the neuter gender, contrasting with masculine and feminine in Latin, was eradicated from spoken Latin by late Empire times. Both Late Latin evidence and data from several modern dialects show that this never happened, and that the vulgate account proceeds from unwarranted back-projection of the data from modern languages like French and Italian. Rather, the neuter underwent transformations which are the main culprit for the differences in the gender system observed today between, say, Romanian, Sursilvan, Neapolitan, and Asturian, to cite just a few types of system which turn out to differ significantly. A precondition for establishing the database for diachronic investigation is a detailed description of many such systems, which reveals data whose interest transcends the diachronic issue under consideration: the book thus addresses systems where ‘husbands’ are feminine and others where ‘wives’ are masculine; discusses dialects where nouns overtly mark gender, but only in certain syntactic contexts; and proposes an analysis according to which one Romance language (Asturian) has split inherited grammatical gender into two concurrent systems.

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