Matlab course - Program

Matlab course - Program

• Today– Basic matrix operations– Basic visualization. Images and plots

• Thursday– Programming, scripts, more visualization

• Friday– Graphical user interfaces and advanced visualizaton

• Any suggestions wellcome, only today is fairly set

Matlab course - introduction

• Goals – Visualize data– Develop programs– GUIs– Read other peoples programs (eg. SPM)

• Hands on

Matlab as a language

• Vector/matrix based

• Many built in functions– Few lines of code will get you far– Extensive visualization capabilities

• Might run slower depending on task

Lets start

• Manipulating matrices and vectors– Basically needed for all programming tasks

everything

• Basic operations– Add noise to a simulated signal – an example

(hemodynamic response function)

Visualizing data

Plotting data

• The plot function– plot(y)– plot(x,y)

• X and Y can be matrices– plot() will plot the columns

• Use hold on to keep the old plot

Simulating the HRF

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ttth tn

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Buxton: Introduction to FMRI

hrtvectortor = hrt(timevector, tau, t0, n)

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Excercise• Part 1

– Generate a timevector, L=10 s, interval=0.1 s– Use the hrf() function to generate a hemodynamic response– Use plot to verify the output

• Part 2– Imagine that you want to display 3 different hrf functions in a plot.

Generate 3 functions and put them in a matrix columnwise. Use a single call to plot to view them

• Part 3– Use randn() to add noise to the curves. Use a std of XX– Plot again

Example hrf parameters:

timevec: from 0 to 20 secs

tau: 1.2

t0: 4 s

n: 3

Example noise parameters:

Use a std of 0.1 – 0.3 - 0.5

Images=matrices

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Imagescaling

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imagesc() + colorbar

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imagesc(data)

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Loading a dicom file

• Matrix=dicomread(’filename’);

• Matrix=double(Matrix);

• imagesc(Matrix)

colormap(cmap_name)

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hist(data(:),[bins])

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Logical comparisons

• Largevalues=matrix > 500– Can be true or false, 0 or 1

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Roipoly – will return a mask

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Exercise

• Load a dicom into a matrix

• Use hist()( to identify noise and see if there is ghosting using imagesc()

• ’Cut away’ the noise– Hint: use a comparison to make a noise mask

and then .*

• Use roipoly to mask away 1 hemisphere

Birgitte – how do we do stats on a mask?

Exercise

• Use mean() to get a mean of an ROI selected using roipoly

• Plot a histogram of your ROI

Saving work

• save workspacename

• save filename X saves only X.

• Save filenename X Y Z saves X, Y, and Z.

The online docs

• Very usefull

• Good links

• Good newsgroup

• Tomorrow: structures – the dir command