Gradient-Domain Image Reconstruction Framework with Intensity-Range and Base-Structure Constraints

Author(s):  
Takashi Shibata ◽  
Masayuki Tanaka ◽  
Masatoshi Okutomi
2016 ◽  
Vol 35 (2) ◽  
pp. 263-273 ◽  
Author(s):  
M. Manzi ◽  
D. Vicini ◽  
M. Zwicker

2020 ◽  
Vol 39 (7) ◽  
pp. 193-203
Author(s):  
Zilin Xu ◽  
Qiang Sun ◽  
Lu Wang ◽  
Yanning Xu ◽  
Beibei Wang

2016 ◽  
Vol 24 (4) ◽  
pp. 627-638 ◽  
Author(s):  
Zhanli Hu ◽  
Qiegen Liu ◽  
Na Zhang ◽  
Yunwan Zhang ◽  
Xi Peng ◽  
...  

Author(s):  
R. A. Crowther

The reconstruction of a three-dimensional image of a specimen from a set of electron micrographs reduces, under certain assumptions about the imaging process in the microscope, to the mathematical problem of reconstructing a density distribution from a set of its plane projections.In the absence of noise we can formulate a purely geometrical criterion, which, for a general object, fixes the resolution attainable from a given finite number of views in terms of the size of the object. For simplicity we take the ideal case of projections collected by a series of m equally spaced tilts about a single axis.


Author(s):  
Santosh Bhattacharyya

Three dimensional microscopic structures play an important role in the understanding of various biological and physiological phenomena. Structural details of neurons, such as the density, caliber and volumes of dendrites, are important in understanding physiological and pathological functioning of nervous systems. Even so, many of the widely used stains in biology and neurophysiology are absorbing stains, such as horseradish peroxidase (HRP), and yet most of the iterative, constrained 3D optical image reconstruction research has concentrated on fluorescence microscopy. It is clear that iterative, constrained 3D image reconstruction methodologies are needed for transmitted light brightfield (TLB) imaging as well. One of the difficulties in doing so, in the past, has been in determining the point spread function of the system.We have been developing several variations of iterative, constrained image reconstruction algorithms for TLB imaging. Some of our early testing with one of them was reported previously. These algorithms are based on a linearized model of TLB imaging.


1998 ◽  
Vol 14 (3) ◽  
pp. 202-210 ◽  
Author(s):  
Suzanne Skiffington ◽  
Ephrem Fernandez ◽  
Ken McFarland

This study extends previous attempts to assess emotion with single adjective descriptors, by examining semantic as well as cognitive, motivational, and intensity features of emotions. The focus was on seven negative emotions common to several emotion typologies: anger, fear, sadness, shame, pity, jealousy, and contempt. For each of these emotions, seven items were generated corresponding to cognitive appraisal about the self, cognitive appraisal about the environment, action tendency, action fantasy, synonym, antonym, and intensity range of the emotion, respectively. A pilot study established that 48 of the 49 items were linked predominantly to the specific emotions as predicted. The main data set comprising 700 subjects' ratings of relatedness between items and emotions was subjected to a series of factor analyses, which revealed that 44 of the 49 items loaded on the emotion constructs as predicted. A final factor analysis of these items uncovered seven factors accounting for 39% of the variance. These emergent factors corresponded to the hypothesized emotion constructs, with the exception of anger and fear, which were somewhat confounded. These findings lay the groundwork for the construction of an instrument to assess emotions multicomponentially.


2005 ◽  
Vol 25 (1_suppl) ◽  
pp. S678-S678
Author(s):  
Yasuhiro Akazawa ◽  
Yasuhiro Katsura ◽  
Ryohei Matsuura ◽  
Piao Rishu ◽  
Ansar M D Ashik ◽  
...  

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