Transformations of a 3D image reconstruction algorithm for data transfer and storage optimisation

Author(s):  
T. Van Achteren ◽  
M. Ade ◽  
R. Lauwereins ◽  
M. Proesmans ◽  
L. Van Gool ◽  
...  
Author(s):  
J.A. Cooper ◽  
S. Bhattacharyya ◽  
J.N. Turner ◽  
T.J. Holmes

We have been developing algorithms for 3D image reconstruction of biological specimens with absorbing stains. This is important because there are many absorbing stains which are widely used in conjunction with transmitted light brightfield (TLB) microscopy, yet most of the 3D microscopic imaging research has been directed toward fluorescence microscopy. For instance, horseradish peroxidase (HRP) is used widely in the neurosciences for its many advantages as a tracer and intracellular marker. It is readily injected into individual neurons, transported long distances, and fills both the dendritic and axonal fields, while it may double as an electron microscopy stain for correlative analysis. With such advantages, it is clear that absorbing stains will continue to be widely used. Their utility will furthermore broaden with 3D visualization and quantitation.The main principles behind our methodology are the following. Standard optical serial sectioning data collection is used. The iterative, constrained image reconstruction algorithm is designed to reconstruct the 3D optical density distribution .


2015 ◽  
Vol 74 (20) ◽  
pp. 1793-1801
Author(s):  
Sidi Mohammed Chouiti ◽  
Lotfi Merad ◽  
Sidi Mohammed Meriah ◽  
Xavier Raimundo

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