Biologists Imaging Wish List
EPFL – BIOP
Advanced Image Processing, MATLAB
20-22.04.2015
O. Burri, R. Guiet, A. Seitz
Image Processing in Matlab
Summary
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Opening Images imopen()
Single Files
Series
Visualization
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Filtering Images
Gray Level Filtering
Binary Filtering
Segmenting Images
Color Segmentation
Thresholding
Active Contours
Extracting Statistics
MIJ
The regionprops() Function
Measuring Intensities Based On Mask
View, export results
Using Fiji in Matlab
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
http://www.mathworks.com/help/images
http://www.mathworks.com/help/images/functionlist.html
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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.
http://notepad.cc/biopadip
password: biop
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Opening Images
The 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 Images
The 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.
Useful Functions
figure, imshow(I) % Shows a new figure of I
close all
% Closes all figures
clear all
% Clears all variables in workspace
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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 Images
The imshow(I) function
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
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Displaying Images
The imshow(I) function
I = imread('rice.png');
imshow(I)
axis on
title('Image of rice.tif')
colormap jet
colorbar
http://tiny.cc/adip-ml-open1
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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
% MultiChannel TIFF Stack in Time
% Get Information on the image
info = imfinfo('mitosis5D.tif');
% Open the whole stack
for i=1:length(info)
K(:,:,i) =
imread('mitosis5D.tif',i);
end
http://tiny.cc/adip-ml-open2
% Open as 5D Array
k=1;
I=[];
for fr=1:51 % 51 frames
for sl=1:5 % 5 slices
for ch=1:2 % 2 channels
I(:,:,ch,sl,fr) = ...
imread('mitosis5D.tif',k);
k=k+1;
end
end
end
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What About Stacks?
Once you have a 3D Array,
you can use
implay(I) to view it in
a movie player.
Unfortunately implay
does 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
http://tiny.cc/adip-ml-bf
http://www.openmicroscopy.org/site/support/bio-formats5.1/developers/matlab-dev.html
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Filtering
The basic tool is
imfilter(I,h);
I is the image and h is
the filter, which is
created with
fspecial(type)
Exercise:
Load FluorescentCells.tif
and filter the DAPI signal
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Filtering
http://tiny.cc/adip-ml-filter
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Segmenting
Three Examples
1. Threshold Based
2. Active Contour Based
3. K-Means Based
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
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Segmenting
%% Active Contours
% First threshold the image roughly
mask = 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');
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K-Means Segmentation
%% K-Means on Color Images
colIm = imread('HESample.jpg');
% Image too big, resize
colIm = imresize(colIm, 0.25);
% Smoothing
colImSmooth = imfilter(colIm,fspecial('gaussian', [3 3], 1.0));
disp(['Applying K-MEANS Clustering with 3 Colors...']);
[pixel_labels, centers] = doKMeans(colImSmooth, 3);
% Display
figure, 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 segmentation
mask(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
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Extracting Statistics
The regionprops() function
Exercise:
Segment the 3 Channel
DAPI_EDU_H2B.tif image on
the first channel and
measure Intensities in
channels 2 and 3
'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'
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Extracting Statistics
The regionprops() function
% Get the statistics
stats =
regionprops('table',bw,'Centroid
',...
'Area',
'MajorAxisLength','MinorAxisLeng
th', 'Orientation')
http://tiny.cc/adip-ml-stats
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Filtering Statistics
Thresholded
Cleaned
After Filtering
Leftovers
http://tiny.cc/adip-ml-statfilter
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MIJI
Can call ImageJ/Fiji from within Matlab
Just need to include the Path to the 'scripts' folder
% Adding path to Fiji
addpath('C:\Fiji.app\scripts');
Instead of run(…) you can use
MIJ.run('COMMAND', 'ARGUMENTS');
Mind the simple quotes!
http://tiny.cc/adip-ml-miji
http://fiji.sc/Miji
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Loads Of Tools
• Visualizing Very Large Files
rsetwrite()
• Block Processing
blockproc()
http://tiny.cc/adip-ml-large
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GUIDE
• Building GUIs in Matlab
http://tiny.cc/adip-ml-guide
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Finished
• Thank you for your time.
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