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2 changes: 1 addition & 1 deletion content/08_ICA_Based_Denoising.md
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# Denoising Data with ICA

ICA classification methods like `tedana` will produce two important outputs: component time series and component classifications.
The component classifications will indicate whether each componet is "good" (accepted) or "bad" (rejected).
The component classifications will indicate whether each component is "good" (accepted) or "bad" (rejected).
To remove noise from your data, you can regress the "bad" components out of it, though there are multiple methods to accomplish this.

Let's start by loading the necessary data.
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32 changes: 27 additions & 5 deletions content/Acquiring_Multi_Echo_Data.md
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Expand Up @@ -87,8 +87,7 @@ used as an input to many functions in the tedana workflow.

There are many ways to calculate T2* maps, with some using multi-echo acquisitions.
We are not presenting an expansive review of this literature here,
but [Cohen-Adad et al. (2012)](https://doi.org/10.1016/j.neuroimage.2012.01.053)
and [Ruuth et al. (2019)](https://doi.org/10.1016/j.ejro.2018.12.006) are good places to start
but {cite:t}`cohen2012t2` and {cite:t}`ruuth2019comparison` are good places to start
learning more about this topic.

## Acquisition parameter recommendations
Expand All @@ -107,8 +106,8 @@ TE one would use for single-echo T2* weighted fMRI.

```{note}
This is in contrast to the **dual echo** denoising method which uses a very early (~5ms)
first echo in order to clean data. For more information on this method, see
[Bright and Murphy (2013)](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3518782/).
first echo in order to clean data.
For more information on this method, see {cite:t}`bright2013removing`.
```

More than 3 echoes may be useful, because that would allow for more accurate
Expand All @@ -124,14 +123,37 @@ We suggest new multi-echo fMRI users examine the :ref:`spreadsheet of publicatio
multi-echo fMRI to identify studies with similar acquisition priorities,
and use the parameters from those studies as a starting point.
More complete recommendations and guidelines are discussed in the
[appendix of Dipasquale et al. (2017)](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0173289).
appendix of {cite:t}`dipasquale2017comparing`.

```{note}
In order to increase the number of contrasts ("echoes") you may need to first increase the TR, shorten the
first TE and/or enable in-plane acceleration.
For typically used parameters see the **ME-fMRI parameters** section below.
```


## Additional considerations


### Complex reconstruction

It is possible to retain phase data when reconstructing multi-echo fMRI data.
The phase data may be leveraged for a number of useful denoising and processing methods,
including NORDIC {cite:p}`vizioli2021lowering;dowdle2021nordic;dowdle2023evaluating`
and MEDIC dynamic distortion correction {cite:p}`van2023framewise`.

It's important to remember that retaining phase data for each echo will effectively double the
amount of data you end up with.
This can also cause problems with online reconstruction,
for example with Siemens machines running XA30.


### No-excitation-pulse noise volumes

In order to best use NORDIC,
researchers should acquire no-RF noise volumes at the end of their fMRI runs.


## ME-fMRI parameters

The following section highlights a selection of parameters collected from published papers that have
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103 changes: 50 additions & 53 deletions content/MR_Physics.md
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# MR Physics

Magnetic Resonance Imaging (MRI),
also known as Magnetic Resonance Tomography or Nuclear Magnetic Resonance Imaging,
is one of the non-invasive imaging techniques that have superior soft tissue contrasts and potential physiological and functional applications.
This type of radiation has not enough energy to remove an electron from an atom but just to excite it to a higher energy state.
Since the 1980s, MRI has been a mainstay of non-invasive diagnostic radiology because it does not expose the body to radiation.
It is frequently used in neuroimaging for the diagnosis and monitoring of diseases,
and it has not yet shown any adverse effects from exposure,
which is a major benefit over other imaging modalities.
MRI enables to perform dynamic studies due to its speed of acquisition.{cite:p}`hovet2018mri;berger2002does`

Magnetic Resonance Imaging (MRI), also known as Magnetic Resonance Tomography or Nuclear Magnetic Resonance Imaging,
is one of the non-invasive imaging techniques that have superior soft tissue contrasts and potential physiological
and functional applications. This type of radiation has not enough energy to remove an electron from an atom but
just to excite it to a higher energy state. Since the 1980s, MRI has been a mainstay of non-invasive diagnostic radiology
because it does not expose the body to radiation. It is frequently used in neuroimaging for the diagnosis and monitoring
of diseases, and it has not yet shown any adverse effects from exposure, which is a major benefit over other imaging
modalities. MRI enables to perform dynamic studies due to it's speed of acquisition. [1][2]

## Basic Physics

Any atomic nucleous with an odd numer of nucleons has spin different from zero and so, a magnetic moment (magnetic dipole).
Any atomic nucleus with an odd number of neutrons has spin different from zero and so,
a magnetic moment (magnetic dipole).
In the body, we can find several atoms with magnetic moment such as H, P, C, F, Na, which are sensitive to magnetic resonance.
Around 60% of the human body is made up of water that contains hydrogen, which is also present in proteins and lipids.
Around 60% of the human body is made up of water that contains hydrogen,
which is also present in proteins and lipids.
For this reason, hydrogen is the most widely used in MRI.


MRI bore contains a powerful magnet which generates an uniform magnetic field B0. Patiens are introduced in this magnetic field
and hydrogen atoms align to the magnetic field. According to Larmour's law, a magnetic dipole inside a magnetic field
precesses (spins) arround the magnetic field with a frequency proportional to the magnetic field strength. Hence, hydrogen atoms
precess arround the magnetic field generated by the MR with a frequency (Larmour frequency) that follows the equation:
MRI bore contains a powerful magnet which generates an uniform magnetic field B0.
Patiens are introduced in this magnetic field and hydrogen atoms align to the magnetic field.
According to Larmour's law, a magnetic dipole inside a magnetic field
precesses (spins) around the magnetic field with a frequency proportional to the magnetic field strength.
Hence, hydrogen atoms precess around the magnetic field generated by the MR with a frequency (Larmor frequency) that follows the equation:

w = γ B0

![](https://www.frontiersin.org/files/Articles/427144/frym-07-00023-HTML-r2/image_m/figure-2.jpg)
This precession can be parallel or antiparallel to B0. In the body the number of atoms that precess parallel is different to
the ones that precess antiparallel producing an small magnetic field which is proportional to B0 and also depends on the density
of hydrogen nuclei. So, the static magnetic field (B0) induces a slight magnetization of tissues.


Then, a radiofrequency pulse is emitted perpendicular to B0 with the same frequency that the spin precession frequency.Hydrogen atoms
abrosrb energy and spin out of equilibrium. Longitudinal magnetization (Mz) of protons in a parallel direction to B0 decreases, and a
transverse magnetization (Mx, My) appears.

Then, when the RF dissapears, the magnetic momentum gradually goes back to te minimum
energy position (magnetic relaxation) while releasing energy. This emited signals are measured into the k-space which is an array
of numbers representing spatial frequencies in the MR image. (Each k-space point contains spatial frequency and phase information
about every pixel in the final image). Fourier transforme is performed to the k-space to obtain the final image. By varying the
sequence of RF pulses applied & collected, different types of images are created.


### MRI Sequences

It's important to understand the meaning of **repetition time (TR)** and **echo time (TE)** in order to comprehend the main
MRI sequences. Time to Echo (TE) is the time between the delivery of the RF pulse and the receipt of the echo signal and
This precession can be parallel or antiparallel to B0.
In the body the number of atoms that precess parallel is different to
the ones that precess antiparallel producing an small magnetic field which is proportional to B0 and also depends on the density
of hydrogen nuclei.
So, the static magnetic field (B0) induces a slight magnetization of tissues.

Then, a radiofrequency pulse is emitted perpendicular to B0 with the same frequency that the spin precession frequency.
Hydrogen atoms abrorb energy and spin out of equilibrium.
Longitudinal magnetization (Mz) of protons in a parallel direction to B0 decreases,
and a transverse magnetization (Mx, My) appears.

Then, when the RF disappears,
the magnetic momentum gradually goes back to te minimum energy position (magnetic relaxation) while releasing energy.
These emitted signals are measured into the k-space,
which is an array of numbers representing spatial frequencies in the MR image.
(Each k-space point contains spatial frequency and phase information about every pixel in the final image).
Fourier transforme is performed to the k-space to obtain the final image.
By varying the sequence of RF pulses applied & collected, different types of images are created.


### MRI Sequences

It's important to understand the meaning of **repetition time (TR)** and **echo time (TE)** in order to comprehend the main MRI sequences.
Time to Echo (TE) is the time between the delivery of the RF pulse and the receipt of the echo signal and
the interval between subsequent pulse sequences delivered to the same slice is known as the repetition time (TR).

The most common sequences are T1-weighted and T2-weighted images. In neuroimaging, **T1-weighted** images are commonly used in anatomical
related studies, they are based on the study of the relaxation of the nuclei in the longitudinal component (Mz) of the magnetization
vector and are produced with short TR and TE.**T2-weighted** images are produced with longer TR and TE. They are based on study of the
variations of the component on the transverse plane of the magnetization during the relaxation, known as transverse relaxation (Mxy).

There are many sequences that can be used depending on the objective. T

## Multi-echo


## Bibliography

[MRI-powered biomedical devices](https://doi.org/10.1080/13645706.2017.1402188)

[Magnetic resonance imaging](https://doi.org/10.1136/bmj.324.7328.35 )

[nibib](https://www.nibib.nih.gov/science-education/science-topics/magnetic-resonance-imaging-mri)


The most common sequences are T1-weighted and T2-weighted images.
In neuroimaging, **T1-weighted** images are commonly used in anatomical related studies,
they are based on the study of the relaxation of the nuclei in the longitudinal component (Mz) of the magnetization
vector and are produced with short TR and TE.
**T2-weighted** images are produced with longer TR and TE.
They are based on study of the variations of the component on the transverse plane of the magnetization during the relaxation,
known as transverse relaxation (Mxy).

There are many sequences that can be used depending on the objective.
21 changes: 11 additions & 10 deletions content/Processing_Multi_Echo_Data.md
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## 3. Perform distortion correction, spatial normalization, smoothing, and any rescaling or filtering **after** denoising

Any step that will alter the relationship of signal magnitudes between echoes should occur after denoising and combining
of the echoes. For example, if echo is separately scaled by its mean signal over time, then resulting intensity gradients
and the subsequent calculation of voxelwise T2* values will be distorted or incorrect. An aggressive temporal filter
(e.g., a 0.1Hz low pass filter) or spatial smoothing could similarly distort the relationship between the echoes at each
time point.
of the echoes.
For example, if echo is separately scaled by its mean signal over time,
then resulting intensity gradients and the subsequent calculation of voxelwise T2* values will be distorted or incorrect.
An aggressive temporal filter (e.g., a 0.1Hz low pass filter)
or spatial smoothing could similarly distort the relationship between the echoes at each time point.

```{note}
We are assuming that spatial normalization and distortion correction, particularly non-linear normalization methods
with higher order interpolation functions, are likely to distort the relationship between echoes while rigid body
motion correction would linearly alter each echo in a similar manner. This assumption has not yet been empirically
tested and an affine normalzation with bilinear interpolation may not distort the relationship between echoes.
We are assuming that spatial normalization and distortion correction,
particularly non-linear normalization methods with higher order interpolation functions,
are likely to distort the relationship between echoes while rigid body motion correction would linearly alter each echo in a similar manner.
This assumption has not yet been empirically tested and an affine normalzation with bilinear interpolation may not distort the relationship between echoes.
Additionally, there are benefits to applying only one spatial transform to data rather than applying one spatial
transform for motion correction and a later transform for normalization and distortion correction. Our advice
against doing normalization and distortion correction is a conservative choice and we encourage additional
transform for motion correction and a later transform for normalization and distortion correction.
Our advice against doing normalization and distortion correction is a conservative choice and we encourage additional
research to better understand how these steps can be applied before denoising.
```
2 changes: 1 addition & 1 deletion content/Recommended_Reading.md
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{cite:t}`POSSE2012665` includes an historical overview of multi-echo acquisition and research.
{cite:t}`KUNDU201759` is a review of multi-echo denoising with a focus on the MEICA algorithm.
The appendix of {cite:t}`OLAFSSON201543` includes a good explanation of the math underlying MEICA denoising.
The appendix of {cite:t}`10.1371/journal.pone.0173289` includes some recommendations for multi-echo acquisition.
The appendix of {cite:t}`dipasquale2017comparing` includes some recommendations for multi-echo acquisition.
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