EPFL – BIOPAdvanced Image Processing, MATLAB

20-22.04.2015O. Burri, R. Guiet, A. Seitz

Image Processing in MatlabSummary1. Opening Images imopen()

• Single Files• Series• Visualization

2. Filtering Images• Gray Level Filtering• Binary Filtering

3. Segmenting Images• Color Segmentation• Thresholding• Active Contours

4. Extracting Statistics• The regionprops() Function• Measuring Intensities Based On Mask• View, export results

5. MIJ• Using Fiji in Matlab

6. Some Nice Features• Large Image Processing• GUIDE

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The Image Processing Toolbox• Large

Improvements each year.

• We are using the R2015a version.

• Well Documented

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http://www.mathworks.com/help/images

http://www.mathworks.com/help/images/functionlist.html

Before Starting• Check your Matlab version

>> version

ans =

8.5.0.197613 (R2015a)

If you have a lower version, you may have to revise some of the code presented.

• Copy all the sample data to a local folder

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Images, Examples & Comments• notepad.cc is a shared notepad, where we will

post download links during the session.

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http://notepad.cc/biopadippassword: biop

Opening ImagesThe imread() function • Reads an image file into a Matlab Array

I = imread('rice.png');

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Extensive Documentation

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Displaying ImagesThe imshow(I) function • Displays the array I as a figure

Note that imshow() overwrites the current figure Call figure; before to make a new one.

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Useful Functions

figure, imshow(I) % Shows a new figure of I

close all % Closes all figures

clear all % Clears all variables in workspace

Note: Check the Function Help• Highlight a function and press F1

or Right-click and choose Help on Selection• Most Matlab functions come with examples

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Displaying ImagesThe imshow(I) function

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Useful Accompanying Functions

title('Some Title') % Sets the title of the figure

colormap map % Changes the lookup table (eg. jet)

axis on % Shows Axes

xlabel('X') % Name of the X axis

ylabel('Y') % Name of the Y axis

Displaying ImagesThe imshow(I) function

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I = imread('rice.png');imshow(I)axis ontitle('Image of rice.tif')colormap jetcolorbar

http://tiny.cc/adip-ml-open1

What About Stacks?• imread() only opens one image at a time BUT understands that

there can be several images in a single TIFF file• Need to use a loop, then sort through the dimensions…• RGB or 3 channel TIFFs can be opened directly

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% MultiChannel TIFF Stack in Time% Get Information on the imageinfo = imfinfo('mitosis5D.tif');

% Open the whole stackfor i=1:length(info)

K(:,:,i) = imread('mitosis5D.tif',i);end

% Open as 5D Array k=1;I=[];for fr=1:51 % 51 framesfor sl=1:5 % 5 slicesfor ch=1:2 % 2 channelsI(:,:,ch,sl,fr) = ...imread('mitosis5D.tif',k);k=k+1;

endend

endhttp://tiny.cc/adip-ml-open2

What About Stacks?Once you have a 3D Array, you can useimplay(I) to view it in a movie player.

Unfortunately implaydoes not respond to the colormap, etc.. functions.

You must configure the scale and lookup table within the tool manually

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Alternative: BioFormats• The same library used in

Fiji• Opens all sorts of

microscopy formats• Can parse metadata• Well Documented

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http://www.openmicroscopy.org/site/support/bio-formats5.1/developers/matlab-dev.html

http://tiny.cc/adip-ml-bf

FilteringThe basic tool is imfilter(I,h);

I is the image and h is the filter, which is created with fspecial(type)

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Exercise:Load FluorescentCells.tifand filter the DAPI signal

Filtering

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http://tiny.cc/adip-ml-filter

SegmentingThree Examples1. Threshold Based2. Active Contour Based3. K-Means Based

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Exercise:Threshold the Filtered DAPI channel from last exercise with graythresh. We will then try to refine the result using active contours.

Useful Functions

graythresh

im2bw

activecontour

Segmenting

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%% Active Contours% First threshold the image roughlymask = im2bw(I, level*0.50);figure, imshow(mask);title('Initial Contour Location');% Then use active contours on I with the mask image as a starting point for 100 iterations and a smoothing factor of 2.bw = activecontour(I,mask,100,'Chan-Vese',2);figure, imshow(bw);title('Segmented Image with Active Contours');

K-Means Segmentation

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%% K-Means on Color ImagescolIm = imread('HESample.jpg');% Image too big, resizecolIm = imresize(colIm, 0.25);% SmoothingcolImSmooth = imfilter(colIm,fspecial('gaussian', [3 3], 1.0));

disp(['Applying K-MEANS Clustering with 3 Colors...']);[pixel_labels, centers] = doKMeans(colImSmooth, 3);

% Displayfigure, imshow(colIm,[]), title('Color Image');figure, imshow(pixel_labels,[]), title('Image labeled by cluster index');

% Make a mask:% Pick dimmest center, this should be the nuclei, as they are dark[mi, id] = min(mean(centers,2));

mask = zeros(size(colIm,1),size(colIm,2));

%Do a watershed segmentationmask(pixel_labels == id) = 1;D = -bwdist(~mask);D(~mask) = -Inf;L = watershed(D);figure, imshow(label2rgb(L,'jet','w')), title('Watershed Segmentation on Nuclei');

http://tiny.cc/adip-ml-segment1

Extracting StatisticsThe regionprops() function

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'Area''BoundingBox''Centroid''ConvexArea''ConvexHull''ConvexImage''Eccentricity''EquivDiameter''EulerNumber''Extent''Extrema''FilledArea''FilledImage''Image''MajorAxisLength''MinorAxisLength''Orientation''Perimeter''PixelIdxList''PixelList''Solidity''SubarrayIdx'

'MaxIntensity''MeanIntensity''MinIntensity''PixelValues''WeightedCentroid'

Exercise:Segment the 3 Channel DAPI_EDU_H2B.tif image on the first channel and measure Intensities in channels 2 and 3

Extracting StatisticsThe regionprops() function

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% Get the statistics

stats =

regionprops('table',bw,'Centroid

',...

'Area',

'MajorAxisLength','MinorAxisLeng

th', 'Orientation')

http://tiny.cc/adip-ml-stats

Filtering Statistics

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Thresholded

After Filtering

Cleaned

Leftovers

http://tiny.cc/adip-ml-statfilter

MIJICan call ImageJ/Fiji from within MatlabJust need to include the Path to the 'scripts' folder

Instead of run(…) you can useMIJ.run('COMMAND', 'ARGUMENTS');

Mind the simple quotes!

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http://fiji.sc/Miji

% Adding path to Fijiaddpath('C:\Fiji.app\scripts');

http://tiny.cc/adip-ml-miji

Loads Of Tools• Visualizing Very Large Filesrsetwrite()

• Block Processingblockproc()

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http://tiny.cc/adip-ml-large

GUIDE• Building GUIs in Matlab

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http://tiny.cc/adip-ml-guide

Finished• Thank you for your time.

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