3D task‐transfer function representation of the signal transfer properties of low‐contrast lesions in FBP‐ and iterative‐reconstructed CT

2018 ◽  
Vol 45 (11) ◽  
pp. 4977-4985 ◽  
Author(s):  
Marthony Robins ◽  
Justin Solomon ◽  
Taylor Richards ◽  
Ehsan Samei
Keyword(s):  
Transfer Function ◽  
Signal Transfer ◽  
Function Representation ◽  
Low Contrast ◽  
Task Transfer ◽  
Transfer Properties

Correction of the contrast transfer function to determine the radial density distribution of frozen-hydrated tobacco mosaic virus

1992 ◽  
Vol 50 (1) ◽  
pp. 536-537
Author(s):  
Michael F. Smith ◽  
John P. Langmore
Keyword(s):  
Transfer Function ◽  
Phase Contrast ◽  
Heavy Atom ◽  
Biological Molecules ◽  
Frequency Compensation ◽  
Contrast Transfer Function ◽  
High Background ◽  
Low Contrast ◽  
Radial Density Distribution ◽  
Excellent Preservation

The purpose of image reconstruction is to determine the mass densities within molecules by analysis of the intensities within images. Cryo-EM offers this possibility by virtue of the excellent preservation of internal structure without heavy atom staining. Cryo-EM images, however, have low contrast because of the similarity between the density of biological material and the density of vitreous ice. The images also contain a high background of inelastic scattering. To overcome the low signal and high background, cryo-images are typically recorded 1-3 μm underfocus to maximize phase contrast. Under those conditions the image intensities bear little resemblance to the object, due to the dependence of the contrast transfer function (CTF) upon spatial frequency. Compensation (i.e., correction) for the CTF is theoretically possible, but implementation has been rare. Despite numerous studies of molecules in ice, there has never been a quantitative evaluation of compensated images of biological molecules of known structure.

A Compartmental Model of Linear Resonance and Signal Transfer in Dendrites

2012 ◽  
Vol 24 (12) ◽  
pp. 3126-3144 ◽  
Author(s):  
Alan Schoen ◽  
Ali Salehiomran ◽  
Matthew E. Larkum ◽  
Erik P. Cook
Keyword(s):  
Continuous Time ◽  
Compartmental Model ◽  
Signal Transfer ◽  
Experimental Conditions ◽  
Impedance Model ◽  
Membrane Impedance ◽  
Dendritic Membrane ◽  
Linear Resonance ◽  
Impedance Functions ◽  
Transfer Properties

Dendrites carry signals between synapses and the soma and play a central role in neural computation. Although they contain many nonlinear ion channels, their signal-transfer properties are linear under some experimental conditions. In experiments with continuous-time inputs, a resonant linear two-port model has been shown to provide a near-perfect fit to the dendrite-to-soma input-output relationship. In this study, we focused on this linear aspect of signal transfer using impedance functions that replace biophysical channel models in order to describe the electrical properties of the dendritic membrane. The membrane impedance model of dendrites preserves the accuracy of the two-port model with minimal computational complexity. Using this approach, we demonstrate two membrane impedance profiles of dendrites that reproduced the experimentally observed two-port results. These impedance profiles demonstrate that the two-port results are compatible with different computational schemes. In addition, our model highlights how dendritic resonance can minimize the location-dependent attenuation of signals at the resonant frequency. Thus, in this model, dendrites function as linear-resonant filters that carry signals between nonlinear computational units.

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