Package {midi}

Title: Microstructure Information from Diffusion Imaging
Version: 0.2.0
Description: An implementation of a taxonomy of models of restricted diffusion in biological tissues parametrized by the tissue geometry (axis, diameter, density, etc.). This is primarily used in the context of diffusion magnetic resonance (MR) imaging to model the MR signal attenuation in the presence of diffusion gradients. The goal is to provide tools to simulate the MR signal attenuation predicted by these models under different experimental conditions. The package feeds a companion 'shiny' app available at https://midi-pastrami.apps.math.cnrs.fr that serves as a graphical interface to the models and tools provided by the package. Models currently available are the ones in Neuman (1974) <doi:10.1063/1.1680931>, Van Gelderen et al. (1994) <doi:10.1006/jmrb.1994.1038>, Stanisz et al. (1997) <doi:10.1002/mrm.1910370115>, Soderman & Jonsson (1995) <doi:10.1006/jmra.1995.0014> and Callaghan (1995) <doi:10.1006/jmra.1995.1055>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (≥ 3.5)
URL: https://github.com/tractoverse/midi, https://tractoverse.github.io/midi/
BugReports: https://github.com/tractoverse/midi/issues
Imports: cli, ggplot2, plotly, purrr, R6, rlang, withr
Suggests: testthat (≥ 3.0.0)
Config/testthat/edition: 3
Config/roxygen2/version: 8.0.0
Config/roxygen2/markdown: TRUE
NeedsCompilation: no
Packaged: 2026-07-05 19:31:43 UTC; stamm-a
Author: Aymeric Stamm ORCID iD [aut, cre]
Maintainer: Aymeric Stamm <aymeric.stamm@cnrs.fr>
Repository: CRAN
Date/Publication: 2026-07-05 19:40:02 UTC

midi: Microstructure Information from Diffusion Imaging

Description

An implementation of a taxonomy of models of restricted diffusion in biological tissues parametrized by the tissue geometry (axis, diameter, density, etc.). This is primarily used in the context of diffusion magnetic resonance (MR) imaging to model the MR signal attenuation in the presence of diffusion gradients. The goal is to provide tools to simulate the MR signal attenuation predicted by these models under different experimental conditions. The package feeds a companion 'shiny' app available at https://midi-pastrami.apps.math.cnrs.fr that serves as a graphical interface to the models and tools provided by the package. Models currently available are the ones in Neuman (1974) doi:10.1063/1.1680931, Van Gelderen et al. (1994) doi:10.1006/jmrb.1994.1038, Stanisz et al. (1997) doi:10.1002/mrm.1910370115, Soderman & Jonsson (1995) doi:10.1006/jmra.1995.0014 and Callaghan (1995) doi:10.1006/jmra.1995.1055.

Author(s)

Maintainer: Aymeric Stamm aymeric.stamm@cnrs.fr (ORCID)

Authors:

See Also

Useful links:

Base compartment class

Description

The base class for compartment models.

Methods

Public methods

BaseCompartment$get_signal()

Computes the signal attenuation predicted by the model.

Usage
BaseCompartment$get_signal(
  small_delta,
  big_delta,
  G,
  direction = c(0, 0, 1),
  echo_time = NULL,
  n_max = 20L,
  m_max = 50L
)
Arguments
small_delta

A numeric value specifying the duration of the gradient pulse in milliseconds.

big_delta

A numeric value specifying the duration between the gradient pulses in milliseconds.

G

A numeric value specifying the strength of the gradient in mT.\mum^{-1}.

direction

A numeric vector specifying the direction of the gradient. Defaults to c(0, 0, 1).

echo_time

A numeric value specifying the echo time in milliseconds.

n_max

An integer value specifying the maximum order of the Bessel function. Defaults to 20L.

m_max

An integer value specifying the maximum number of extrema for the Bessel function. Defaults to 50L.

Returns

A numeric value storing the predicted signal attenuation.

Examples
freeComp <- FreeCompartment$new()
freeComp$get_signal(small_delta = 30, big_delta = 30, G = 0.040)

sphereComp <- SphereCompartment$new()
sphereComp$get_signal(small_delta = 30, big_delta = 30, G = 0.040)

sodermanComp <- SodermanCompartment$new()
sodermanComp$get_signal(small_delta = 30, big_delta = 30, G = 0.040)

staniszComp <- StaniszCompartment$new()
staniszComp$get_signal(small_delta = 30, big_delta = 30, G = 0.040)

neumanComp <- NeumanCompartment$new()
neumanComp$get_signal(
  small_delta = 30, big_delta = 30, G = 0.040,
  echo_time = 40
)

callaghanComp <- CallaghanCompartment$new()
callaghanComp$get_signal(small_delta = 30, big_delta = 30, G = 0.040)

vanGelderenComp <- VanGelderenCompartment$new()
vanGelderenComp$get_signal(small_delta = 30, big_delta = 30, G = 0.040)

BaseCompartment$get_parameter_names()

Returns the names of the compartment parameters

Usage
BaseCompartment$get_parameter_names()
Returns

A character vector storing the names of the compartment parameters.

Examples
freeComp <- FreeCompartment$new()
freeComp$get_parameter_names()

BaseCompartment$get_parameters()

Returns the values of the compartment parameters

Usage
BaseCompartment$get_parameters()
Returns

A numeric vector storing the values of the compartment parameters.

Examples
freeComp <- FreeCompartment$new()
freeComp$get_parameters()

BaseCompartment$clone()

The objects of this class are cloneable with this method.

Usage
BaseCompartment$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

Examples


## ------------------------------------------------
## Method `BaseCompartment$get_signal()`
## ------------------------------------------------

freeComp <- FreeCompartment$new()
freeComp$get_signal(small_delta = 30, big_delta = 30, G = 0.040)

sphereComp <- SphereCompartment$new()
sphereComp$get_signal(small_delta = 30, big_delta = 30, G = 0.040)

sodermanComp <- SodermanCompartment$new()
sodermanComp$get_signal(small_delta = 30, big_delta = 30, G = 0.040)

staniszComp <- StaniszCompartment$new()
staniszComp$get_signal(small_delta = 30, big_delta = 30, G = 0.040)

neumanComp <- NeumanCompartment$new()
neumanComp$get_signal(
  small_delta = 30, big_delta = 30, G = 0.040,
  echo_time = 40
)

callaghanComp <- CallaghanCompartment$new()
callaghanComp$get_signal(small_delta = 30, big_delta = 30, G = 0.040)

vanGelderenComp <- VanGelderenCompartment$new()
vanGelderenComp$get_signal(small_delta = 30, big_delta = 30, G = 0.040)

## ------------------------------------------------
## Method `BaseCompartment$get_parameter_names()`
## ------------------------------------------------

freeComp <- FreeCompartment$new()
freeComp$get_parameter_names()

## ------------------------------------------------
## Method `BaseCompartment$get_parameters()`
## ------------------------------------------------

freeComp <- FreeCompartment$new()
freeComp$get_parameters()

Base distribution class

Description

This class defines the base distribution class from which all other distributions inherit. It provides a common interface for fitting the distribution to data and generating random samples.

Methods

Public methods

BaseDistribution$fit()

Fit the distribution to the data.

Usage
BaseDistribution$fit(x)
Arguments
x

A numeric vector of data to fit the distribution to.

Returns

Internally sets the parameters of the distribution. Returns nothing.

BaseDistribution$random()

Generate random samples from the distribution.

Usage
BaseDistribution$random(n)
Arguments
n

An integer specifying the number of samples to generate.

Returns

A numeric vector of size n containing the random samples.

BaseDistribution$get_mean()

Compute the mean of the distribution.

Usage
BaseDistribution$get_mean()
Returns

A numeric value storing the mean of the distribution.

BaseDistribution$get_variance()

Compute the variance of the distribution.

Usage
BaseDistribution$get_variance()
Returns

A numeric value storing the variance of the distribution.

BaseDistribution$clone()

The objects of this class are cloneable with this method.

Usage
BaseDistribution$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

Callaghan's model for restricted diffusion in a cylinder

Description

A class to model restricted diffusion in a cylinder using the Callaghan's model.

Super classes

BaseCompartment -> CircularlyShapedCompartment -> CallaghanCompartment

Methods

Public methods

Inherited methods

CallaghanCompartment$clone()

The objects of this class are cloneable with this method.

Usage
CallaghanCompartment$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

References

Callaghan, P. T. (1995). Pulsed-gradient spin-echo NMR for planar, cylindrical, and spherical pores under conditions of wall relaxation. Journal of magnetic resonance, Series A, 113(1), 53-59.

Circularly-shaped compartment class

Description

A class to model restricted diffusion in a bounded medium described by a circular shape with a given radius.

Super class

BaseCompartment -> CircularlyShapedCompartment

Methods

Public methods

Inherited methods

CircularlyShapedCompartment$new()

Instantiates a new circular compartment.

Usage
CircularlyShapedCompartment$new(radius = NULL, diffusivity = NULL)
Arguments
radius

A numeric value specifying the radius of the sphere in \mum.

diffusivity

A numeric value specifying the diffusivity within the sphere in \mum^2.ms^{-1}.

Returns

An instance of the CircularlyShapedCompartment class.

CircularlyShapedCompartment$clone()

The objects of this class are cloneable with this method.

Usage
CircularlyShapedCompartment$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

Cylinder bundle compartment class

Description

A class to model restricted diffusion in a bundle of cylinders.

Super class

BaseCompartment -> CylinderBundleCompartment

Methods

Public methods

Inherited methods

CylinderBundleCompartment$new()

Instantiates a new cylinder bundle compartment.

Usage
CylinderBundleCompartment$new(
  cylinder_density,
  cylinder_compartments,
  axial_diffusivity = NULL,
  radial_diffusivity = NULL
)
Arguments
cylinder_density

A numeric value specifying the density of the cylinders in the voxel. Must be between 0 and 1.

cylinder_compartments

A list of instances of the CylinderCompartment class specifying the compartments within the bundle.

axial_diffusivity

A numeric value specifying the axial diffusivity in the space outside the cylinders in m^2.s^{-1}. If not provided, defaults to a tortuosity model reducing the intrinsic diffusivity depending on orientation dispersion. Defaults to NULL in which case the extracellular axial diffusivity is set via a tortuosity model based on the dispersion in orientation.

radial_diffusivity

A numeric value specifying the radial diffusivity in the space outside the cylinders in m^2.s^{-1}. Defaults to NULL in which case the extracellular radial diffusivity is set via a tortuosity model based on the intracellular density.

Returns

An instance of the CylinderBundleCompartment class.

CylinderBundleCompartment$clone()

The objects of this class are cloneable with this method.

Usage
CylinderBundleCompartment$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

Examples

withr::with_seed(1234, {
  cyls <- rcylinders(
    n = 100,
    axis_mean = c(0, 0, 1),
    radius_mean = 5,
    diffusivity_mean = 3,
    axis_concentration = 10,
    radius_sd = 1,
    diffusivity_sd = 0
  )
})

comp <- CylinderBundleCompartment$new(
  cylinder_density = 0.5,
  cylinder_compartments = cyls
)

comp$get_signal(
  small_delta = 30,
  big_delta = 30,
  G = 0.040,
  direction = c(0, 0, 1)
)

comp$get_parameters()

Cylinder compartment class

Description

A class to model restricted diffusion in a cylinder.

Super classes

BaseCompartment -> CircularlyShapedCompartment -> CylinderCompartment

Methods

Public methods

Inherited methods

CylinderCompartment$new()

Instantiates a new cylinder compartment.

Usage
CylinderCompartment$new(
  axis = c(0, 0, 1),
  restricted_compartment = VanGelderenCompartment$new()
)
Arguments
axis

A length-3 numeric vector specifying the axis of the cylinder.

restricted_compartment

An instance of the CircularlyShapedCompartment class specifying the restricted compartment within the sphere. Defaults to a Van Gelderen compartment.

Returns

An instance of the CylinderCompartment class.

CylinderCompartment$clone()

The objects of this class are cloneable with this method.

Usage
CylinderCompartment$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

Examples

cylComp <- CylinderCompartment$new()
cylComp$get_signal(small_delta = 30, big_delta = 30, G = 0.040)
cylComp$get_parameter_names()
cylComp$get_parameters()

Free compartment class

Description

A class to model free unconstrained diffusion.

Super class

BaseCompartment -> FreeCompartment

Methods

Public methods

Inherited methods

FreeCompartment$new()

Instantiates a new free compartment.

Usage
FreeCompartment$new(diffusivity = NULL)
Arguments
diffusivity

A numeric value specifying the diffusivity within the sphere in \mum^2.ms^{-1}. Defaults to NULL, in which case the default free diffusivity of 3 \mum^2.ms^{-1} is used.

Returns

An instance of the FreeCompartment class.

FreeCompartment$clone()

The objects of this class are cloneable with this method.

Usage
FreeCompartment$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

Gamma distribution class

Description

This class defines the gamma distribution. It provides methods for fitting the distribution to data and generating random samples.

Super class

BaseDistribution -> GammaDistribution

Methods

Public methods

Inherited methods

GammaDistribution$new()

Creates a new gamma distribution.

Usage
GammaDistribution$new(shape = 1, scale = 1)
Arguments
shape

A numeric value specifying the shape parameter of the gamma distribution. Defaults to 1.0.

scale

A numeric value specifying the scale parameter of the gamma distribution. Defaults to 1.0.

Returns

An instance of the gamma distribution as an object of class GammaDistribution.

GammaDistribution$get_shape()

Retrieves the shape parameter of the gamma distribution.

Usage
GammaDistribution$get_shape()
Returns

A numeric value storing the shape parameter of the gamma distribution.

GammaDistribution$get_scale()

Retrieves the scale parameter of the gamma distribution.

Usage
GammaDistribution$get_scale()
Returns

A numeric value storing the scale parameter of the gamma distribution.

GammaDistribution$clone()

The objects of this class are cloneable with this method.

Usage
GammaDistribution$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

Examples

gd <- GammaDistribution$new(
  shape = 1,
  scale = 5
)
gd$get_shape()
gd$get_scale()
gd$get_mean()
gd$get_variance()
gd$random(10)
gd$fit(gd$random(100))
gd$get_shape()
gd$get_scale()

Neuman's model for restricted diffusion in a cylinder

Description

A class to model restricted diffusion in a cylinder using the Neuman's model.

Super classes

BaseCompartment -> CircularlyShapedCompartment -> NeumanCompartment

Methods

Public methods

Inherited methods

NeumanCompartment$clone()

The objects of this class are cloneable with this method.

Usage
NeumanCompartment$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

References

Neuman, C. H. (1974). Spin echo of spins diffusing in a bounded medium. The Journal of Chemical Physics, 60(11), 4508-4511.

Soderman's model for restricted diffusion in a cylinder

Description

A class to model restricted diffusion in a cylinder using the Soderman's model.

Super classes

BaseCompartment -> CircularlyShapedCompartment -> SodermanCompartment

Methods

Public methods

Inherited methods

SodermanCompartment$clone()

The objects of this class are cloneable with this method.

Usage
SodermanCompartment$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

References

Söderman, O., & Jönsson, B. (1995). Restricted diffusion in cylindrical geometry. Journal of Magnetic Resonance, Series A, 117(1), 94-97.

Sphere compartment class

Description

A class to model restricted diffusion in a sphere.

Super classes

BaseCompartment -> CircularlyShapedCompartment -> SphereCompartment

Methods

Public methods

Inherited methods

SphereCompartment$new()

Instantiates a new sphere compartment.

Usage
SphereCompartment$new(restricted_compartment = VanGelderenCompartment$new())
Arguments
restricted_compartment

An instance of the CircularlyShapedCompartment class specifying the restricted compartment within the sphere. Defaults to a Van Gelderen compartment.

Returns

An instance of the SphereCompartment class.

SphereCompartment$clone()

The objects of this class are cloneable with this method.

Usage
SphereCompartment$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

Examples

sphComp <- SphereCompartment$new()
sphComp$get_signal(small_delta = 30, big_delta = 30, G = 0.040)
sphComp$get_parameter_names()
sphComp$get_parameters()

Stanisz's model for restricted diffusion in a cylinder

Description

A class to model restricted diffusion in a cylinder using the Stanisz's model.

Super classes

BaseCompartment -> CircularlyShapedCompartment -> StaniszCompartment

Methods

Public methods

Inherited methods

StaniszCompartment$clone()

The objects of this class are cloneable with this method.

Usage
StaniszCompartment$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

References

Stanisz, G. J., Wright, G. A., Henkelman, R. M., & Szafer, A. (1997). An analytical model of restricted diffusion in bovine optic nerve. Magnetic Resonance in Medicine, 37(1), 103-111.

Van Gelderen's model for restricted diffusion in a cylinder

Description

A class to model restricted diffusion in a cylinder using the Van Gelderen's model.

Super classes

BaseCompartment -> CircularlyShapedCompartment -> VanGelderenCompartment

Methods

Public methods

Inherited methods

VanGelderenCompartment$clone()

The objects of this class are cloneable with this method.

Usage
VanGelderenCompartment$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

References

Vangelderen, P., DesPres, D., Vanzijl, P. C. M., & Moonen, C. T. W. (1994). Evaluation of restricted diffusion in cylinders. Phosphocreatine in rabbit leg muscle. Journal of Magnetic Resonance, Series B, 103(3), 255-260.

Watson distribution class

Description

This class defines the Watson distribution. It provides methods for fitting the distribution to data and generating random samples.

Super class

BaseDistribution -> WatsonDistribution

Methods

Public methods

Inherited methods

WatsonDistribution$new()

Creates a new Watson distribution.

Usage
WatsonDistribution$new(mu = c(0, 0, 1), kappa = 10)
Arguments
mu

A numeric vector of length 3 specifying the mean direction of the Watson distribution. Defaults to ⁠(0, 0, 1)⁠.

kappa

A numeric value specifying the concentration parameter of the Watson distribution. Defaults to 10.0.

Returns

An instance of the Watson distribution as an object of class WatsonDistribution.

WatsonDistribution$get_axis()

Retrieves the mean axis of the Watson distribution.

Usage
WatsonDistribution$get_axis()
Returns

A numeric vector of length 3 storing the mean axis of the Watson distribution.

WatsonDistribution$get_concentration()

Retrieves the concentration parameter of the Watson distribution.

Usage
WatsonDistribution$get_concentration()
Returns

A numeric value storing the concentration parameter of the Watson distribution.

WatsonDistribution$clone()

The objects of this class are cloneable with this method.

Usage
WatsonDistribution$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

Examples

wd <- WatsonDistribution$new(
  mu = c(0, 0, 1),
  kappa = 10
)
wd$get_axis()
wd$get_concentration()
wd$random(10)
wd$fit(wd$random(100))
wd$get_axis()
wd$get_concentration()

Plots a cross section of a cylinder bundle using ggplot2

Description

Plots a cross section of a cylinder bundle from an object of class bundle as generated by simulate_bundle() using ggplot2.

Usage

## S3 method for class 'bundle'
autoplot(object, grid_size = 100L, ...)

Arguments

object

An object of class bundle as generated by simulate_bundle().

grid_size

An integer value specifying the number of points on which the unit circle should be discretized to draw the spheres. Defaults to 100L.

...

Additional arguments to be passed to the ggplot2::autoplot() method.

Value

A ggplot2::ggplot() object.

Examples

density <- 0.5
voxel_size <- 5 # micrometers
withr::with_seed(1234, {
  out <- simulate_bundle(density, voxel_size)
})
ggplot2::autoplot(out)

B-Value Calculation

Description

A function to calculate the b-value for a given set of experimental parameters.

Usage

bvalue(small_delta, big_delta, G)

Arguments

small_delta

A numeric value specifying the duration of the gradient pulse in ms.

big_delta

A numeric value specifying the duration between the gradient pulses in ms.

G

A numeric value specifying the strength of the gradient in \muT/\mum.

Value

A numeric value storing the predicted b-value in ms/\mum^2.

Examples

bvalue(small_delta = 30, big_delta = 30, G = 0.040)

Plots a cross section of a cylinder bundle

Description

Plots a cross section of a cylinder bundle

Usage

## S3 method for class 'bundle'
plot(x, grid_size = 100L, ...)

Arguments

x

An object of class bundle as generated by simulate_bundle().

grid_size

An integer value specifying the number of points on which the unit circle should be discretized to draw the spheres. Defaults to 100L.

...

Additional arguments to be passed to the ggplot2::autoplot() method.

Value

Nothing.

Examples

density <- 0.5
voxel_size <- 5 # micrometers
withr::with_seed(1234, {
  out <- simulate_bundle(density, voxel_size)
})
plot(out)

Plots a 3D representation of a cylinder bundle using plotly

Description

Plots a 3D representation of a cylinder bundle from an object of class bundle as generated by simulate_bundle() using plotly.

Usage

plot3d(b, show_linear_mesh = FALSE)

Arguments

b

An object of class bundle as generated by simulate_bundle().

show_linear_mesh

A logical value indicating whether the linear mesh of each cylinder should be displayed. Defaults to FALSE for computational efficiency.

Value

An HTML widget of class plotly::plotly storing the 3D visualization of the cylinder bundle.

Examples

density <- 0.5
voxel_size <- 5 # micrometers
withr::with_seed(1234, {
  out <- simulate_bundle(density, voxel_size)
})
plot3d(out)

Sample cylinder compartments

Description

This function samples n cylinder compartments with given axis, radius and diffusivity distributions.

Usage

rcylinders(
  n,
  axis_mean,
  radius_mean,
  diffusivity_mean,
  axis_concentration = Inf,
  radius_sd = 0,
  diffusivity_sd = 0,
  restricted_model = c("Callaghan", "Neuman", "Soderman", "Stanisz", "Van Gelderen")
)

Arguments

n

An integer value specifying the number of compartments to sample.

axis_mean

A numeric value specifying the mean of the axis distribution.

radius_mean

A numeric value specifying the mean of the radius distribution.

diffusivity_mean

A numeric value specifying the mean of the diffusivity distribution.

axis_concentration

A numeric value specifying the concentration of the axis distribution. Defaults to Inf in which case the axis is fixed to the mean value.

radius_sd

A numeric value specifying the standard deviation of the radius distribution. Defaults to 0 in which case the radius is fixed to the mean value.

diffusivity_sd

A numeric value specifying the standard deviation of the diffusivity distribution. Defaults to 0 in which case the diffusivity is fixed to the mean value.

restricted_model

A character vector specifying the restricted diffusion model to use. Defaults to callaghan. Possible values are callaghan, neuman, soderman, stanisz, and vangelderen.

Details

The axis distribution is given by a mean and a concentration parameter and the Dimroth-Watson distribution is used to sample values. The radius and diffusivity distributions are given by a mean and a standard deviation and the Gamma distribution is used to sample values. If the concentration parameter is set to Inf the axis is fixed to the mean value. If the standard deviation of the radius and diffusivity distributions are set to 0 the radius and diffusivity are fixed to the mean values. If all parameters are fixed, only one compartment is sampled.

Value

A list of n cylinder compartments of class CylinderCompartment.

Examples

# Sample 10 cylinder compartments with fixed axis, radius and diffusivity
# set.seed(42)
cyl_distr <- rcylinders(
  n = 10L,
  axis_mean = c(0, 0, 1),
  radius_mean = 5,
  diffusivity_mean = 3
)

Runs the MIDI Shiny web application

Description

This is a helper function to run the MIDI Shiny web application in the default web browser.

Usage

run_app()

Value

Nothing, but launches the Shiny app in the default web browser.

Examples


  run_app()

Generates a cross section of a cylinder bundle

Description

Generates a cross section of a cylinder bundle with a given density and voxel size. The cross section is generated by simulating a random distribution of cylinders and computing the intersection of the cylinders with a plane. The radii of the cylinders are drawn from a Gamma distribution fitted from data retrieved by histology in the genu of the corpus callosum (Aboitiz et al., 1992). The number of cylinders is determined by the density and the voxel size.

Usage

simulate_bundle(
  density = 0.5,
  voxel_size = 10,
  rel_tol = 0.001,
  verbose = FALSE
)

Arguments

density

A numeric value between 0 and 1 specifying the density of the cylinders in the voxel. Defaults to 0.5.

voxel_size

A numeric value specifying the size of the voxel in micro- meters. Defaults to 10.

rel_tol

A numeric value specifying the relative tolerance to reach the target volume defined as density * voxel_size^2. Defaults to 1e-3.

verbose

A logical value specifying whether to print messages. Defaults to FALSE.

Value

A list with the following components:

References

Aboitiz, F., Scheibel, A. B., Fisher, R. S., & Zaidel, E. (1992). Fiber composition of the human corpus callosum. Brain research, 598(1-2), 143-153.

Examples

density <- 0.5
voxel_size <- 5 # micrometers
withr::with_seed(1234, {
  out <- simulate_bundle(density, voxel_size)
})

# Actual density in the simulated substrate
sum(out$sections[, "r"]^2 * pi) / voxel_size^2