neurospin.registration.iconic_registration

Module: neurospin.registration.iconic_registration

Inheritance diagram for nipy.neurospin.registration.iconic_registration:

Intensity-based matching.

Questions: alexis.roche@gmail.com

Class

IconicRegistration

class nipy.neurospin.registration.iconic_registration.IconicRegistration(source, target, bins=256)

Bases: object

__init__(source, target, bins=256)

A class to reprensent a generic intensity-based image registration algorithm.

eval(T)

explore(T0, *args)

Evaluate the similarity at the transformations specified by sequences of parameter values.

For instance:

explore(T0, (0, [-1,0,1]), (4, [-2.,2]))

interp

optimize(start, method='powell', **kwargs)

set_source_fov(spacing=[, 1, 1, 1], corner=[, 0, 0, 0], shape=None, fixed_npoints=None)

similarity

voxel_transform(T)

T is the 4x4 transformation between the real coordinate systems The corresponding voxel transformation is: Tv = Tt^-1 * T * Ts

Functions

nipy.neurospin.registration.iconic_registration.clamp(x, bins=256)

Clamp array values that fall within a given mask in the range [0..bins-1] and reset masked values to -1.

Parameters:

x : ndarray

The input array

bins : number

Desired number of bins

Returns:

y : ndarray

Clamped array

bins : number

Adjusted number of bins

nipy.neurospin.registration.iconic_registration.subsample(data, npoints)

Tune spacing factors so that the number of voxels in the output block matches a given number.

Parameters:

data : ndarray or sequence

Data image to subsample

npoints : number

Target number of voxels (negative values will be ignored)

Returns:

spacing: ndarray :

Spacing factors