Update home authored by Saad Jbabdi's avatar Saad Jbabdi
......@@ -12,21 +12,26 @@ The app allows you to visualise diffusion data predicted by user-defined microst
# Models
- user defined acquisition parameters
- multiple micro-structural compartments based on the standard model:
DIVE implements a multi-compartment model based on the so-called [standard model](https://pubmed.ncbi.nlm.nih.gov/30321478). The compartments are as follows:
- Ball (Tensor with L1=L2=L3)
- Stick (Tensor with L2=L3=0)
- Zeppelin (Tensor with L2=L3)
- Tensor
- Cylinder (restricted diffusion)
- Sphere (restricted diffusion)
- dot (no diffusion)
- multiple compartments can be combined
- parameters of the models can be changed using interactive sliders
- A fibre orientation distribution function (ODF) can be defined for each combination of compartment
- including crossing fibres and dispersion
- user can add Gaussian/Rician noise to predicted signal
- data can be saved to file for further analysis
- Dot (no diffusion)
In addition to choosing amongst a number of compartment, the user can specify a fibre orientation distribution function (FOD), including crossing fibres and dispersion, which can be applied to any subset of the compartments.
DIVE also includes the following pre-baked models which can be used as a starting point:
- Ball \& Stick [(Behrens 2003)](https://pubmed.ncbi.nlm.nih.gov/14587019)
- NODDI: Neurite Orientation Dispersion and Density Imaging [(Zhang 2012)](https://pubmed.ncbi.nlm.nih.gov/22484410)
- VERDICT: Vascular Extracellular and Restricted Diffusion for Cytometry in Tumours [(Panagiotaki 2015)](https://pubmed.ncbi.nlm.nih.gov/25426656)
- SANDI: Soma And Neurite Density Imaging ([Palombo 2020)](https://pubmed.ncbi.nlm.nih.gov/32289460)
- MMWMD: Minimal Model for White Matter Diffusion [(Sepehrband 2016)](https://pubmed.ncbi.nlm.nih.gov/26748471)
# Panels
......@@ -41,21 +46,21 @@ The Orientation panel allows specification of a fibre orientation distribution (
- Visualisation panels
There are 4 visualisation panels:
1. Sensitivity to b-value
2. Sensitivity to diffusion time
3. Sensitivity to orientation
4. Sensitivity to parameter changes
V1. Sensitivity to b-value
V2. Sensitivity to diffusion time
V3. Sensitivity to orientation
V4. Sensitivity to parameter changes
Panels 1,2 and 4 show a figure for signal changes as a function of b-value, diffusion time, and model parameters respectively. They also show a figure for changes in commonly used tensor-based parameters (FA and MD). The signal plot by default is the spherical-mean technique (i.e. averaged signal over all 3D orientations), unless this is modified through the control panels (see below).
Visualisation panel 3 show the signal as a function of gradient orientation in two different ways: either as a function of the angle wrt an orientation specified in the control panels (below), or as a 3D glyph.
Visualisation panel 3 show the signal as a function of gradient orientation in two different ways: either as a function of the angle w.r.t. an orientation specified in the control panels (below), or as a 3D glyph.
- Control panels
Finally, there are 4 controls panels:
1. Acquisition: specify an acquisition scheme by either selecting amongst pre-defined ones or loading text files. Once a scheme is chosen, click on 'Display scatter' to see the predicted data.
2. Shells: modify the b-value/diffusion time/gradient amplitude/gradient duration. This affects all the signal plots except for those where b-value/diffusion time appear along the x-axis.
3. Noise: add noise to the scattered data. This only affects the scattered data following the acquisition scheme defined in panel (1), not the continuous signal predictions.
4. Axis: perform operations that affect the x and y axes of the plots. User can choose to apply one of predefined operations to the axes (e.g. to look at log-signal instead of signal), or can modify the reference orientation of the signal v angle plot (see visualisation panel 4)
C1. Acquisition: specify an acquisition scheme by either selecting amongst pre-defined ones or loading text files. Once a scheme is chosen, click on 'Display scatter' to see the predicted data. Click on 'Save scatter' to save the data into a CSV file.
C2. Shells: modify the b-value/diffusion time/gradient amplitude/gradient duration. This affects all the signal plots except for those where b-value/diffusion time appear along the x-axis.
C3. Noise: add noise to the scattered data. This only affects the scattered data following the acquisition scheme defined in panel (1), not the continuous signal predictions.
C4. Axis: perform operations that affect the x and y axes of the plots. User can choose to apply one of predefined operations to the axes (e.g. to look at log-signal instead of signal), or can modify the reference orientation of the signal v angle plot (see visualisation panel 4)
# History
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