View source for QuachFu

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= Background =



= Methods =
== Expectation Maximization ==
 

=== Probability Map ===
Subjects were 5 healthy volunteers.

=== 2D FFT ===
Data were obtained on a GE scanner. Et cetera.

=== Similarity Measure ===
The MR data was analyzed using [http://white.stanford.edu/newlm/index.php/MrVista mrVista] software tools. 

==== Thresholding ====
All data were slice-time corrected, motion corrected, and repeated scans were averaged together to create a single average scan for each subject. Et cetera.

= Results =

== Uncompressed Images ==
Some text. Some analysis. Some figures.

== JPEG Images ==


=== Equations===
If you want to use equations, you can use the same formats that are use on wikipedia. <br> 
''See wikimedia help on  [http://meta.wikimedia.org/wiki/Help:Displaying_a_formula formulas] for help.'' <br>
This example of equation use is copied and pasted from [http://en.wikipedia.org/wiki/Discrete_Fourier_transform wikipedia's article on the DFT]. 

The [[sequence]] of ''N'' [[complex number]]s ''x''<sub>0</sub>, ..., ''x''<sub>''N''−1</sub> is transformed into the  sequence of ''N'' complex numbers ''X''<sub>0</sub>, ..., ''X''<sub>''N''−1</sub> by the DFT according to the formula:

:<math>X_k = \sum_{n=0}^{N-1} x_n e^{-\frac{2 \pi i}{N} k n} \quad \quad k = 0, \dots, N-1</math>   
            
where i is the imaginary unit and <math>e^{\frac{2 \pi i}{N}}</math>  is a primitive N'th [[root of unity]]. (This expression can also be written in terms of a [[DFT matrix]]; when scaled appropriately it becomes a [[unitary matrix]] and the ''X''<sub>''k''</sub> can thus be viewed as coefficients of ''x'' in an [[orthonormal basis]].)

The transform is sometimes denoted by the symbol <math>\mathcal{F}</math>, as in <math>\mathbf{X} = \mathcal{F} \left \{ \mathbf{x} \right \} </math> or <math>\mathcal{F} \left ( \mathbf{x} \right )</math> or <math>\mathcal{F} \mathbf{x}</math>.  

The '''inverse discrete Fourier transform (IDFT)''' is given by 

:<math>x_n = \frac{1}{N} \sum_{k=0}^{N-1} X_k e^{\frac{2\pi i}{N} k n} \quad \quad n = 0,\dots,N-1.</math>

== Retinotopic models in group-averaged data projected back into native space ==
Some text. Some analysis. Some figures.


= Conclusions =

Here is where you say what your results mean.

= References - Resources and related work =

References

Software

= Appendix I - Code and Data =

==Code==
[[File:CodeFile.zip]]

==Data==
[[File:DataFile.zip | zip file with my data]]

= Appendix II - Work partition (if a group project) =
Brian and Bob gave the lectures. Jon mucked around on the wiki.