View source for Inter-slice Motion Correction for fMRI

== Objective ==
    * To perform inter-slice motion correction in fMR images using affine and non-rigid registration methods. 


== Progress ==
    * Implemented and tested b-Spline/affine registration with Mattes-MI and KL metrics. 
    * Coding completed. However, results are far from satisfactory.
    * Progress (maybe) stymied by "poor" resolution of data.
    * Progress (maybe) stymied by "not-so-viable" metrics (MI, etc.).

== Algorithms Used From ITK ==

=== Metrics ===

# Mean Squared - smooth, and for rigid registration, the minimum is fairly correct (physically)
# MI (Wells, Mattes) - very non-smooth - lot of discontinuities. For all motions, results are wrong (possibly because cannot identify a good minimum pt)
# KL-Divergence (Chung, Wells,'' et. al.'') - again very non-smooth. Cannot identify a good minimum point.

=== Transformations ===
# Rigid - works well for ms metric, not so correct for statistical metrics.
# Affine - works for ms metric, does not work for the statistical metrics.
# B-spline non-rigid - tested with ms and kl. Extremely poor results.

== Results ==

'''Original fMRI '''

[[Image:unreg.png]]

'''MS Metric with rigid transform'''

[[Image:ms_rigid.png]]


'''MS Metric with affine transform'''

[[Image:ms_aff.png]]

'''Mattes MI metric with rigid transform '''

[[Image:mattes_ridid.png]]

'''KL metric with rigid transform '''

[[Image:kl_rigid.png]]

'''SPM Registered '''

[[Image:spm_reg.png]]


=== Issues ===
* As can be seen any registration result looks more jagged (along the sagittal and coronal sections). 
* '''Low sampling rate and image noise - all the metrics are extremely non-smooth as a result.''' 
* '''Even the slightest change in initialization results in a large deviation in the registration result.
'''

== Open questions ==
    * Intensity normalization / histogram equalization - would these have any impact on inter-slice registration? Would they affect the computation of the joint-entropies for MI/KL metrics.
    * Should there be some regularization factor on the registration to limit the motion ?

== To Do ==

    * Right now, registration is done on a slice by slice basis. However, due to the low resolution of fMRI and the absence of gradients result in low registration accuracy. We are investigating using alternative image-to-image metrics like the KL divergence. We are also looking at simultaneously registering multiple slices.

== Key Investigators ==

    * Firdaus Janoos, Raghu Machiraju, Steve Pieper, Wendy Plesniak.

== Links ==