I'm using MATLAB R2012a to develop a GUI for manual medical image segmentation. In particular, I want this regions to train a classifier for automatic brain tissue classification.
The GUI I design contains 2 axes, with tags 'figureImage' and 'figureVOI', respectively. In the first one I want to display a single slice of a 3D MRI scan, and in the other one I want to show the mask associated to that slice. I allow the user to move between slices using a scroll bar.
I'm using a 3D matrix to represent the image ('image'), and a 3D matrix to represent the mask ('voi'), both of them in the handles structure. I initialize the 'voi' matrix with zeros when the GUI is loaded.
The code I applied when the user clics on the scroll bar is the next:
% update the number of the actual slice
handles.actualSlice = round(get(handles.sliceSelector, 'Value'));
% update the image and the mask
axes(handles.figureImage)
imshow(handles.image(:, :, handles.actualSlice));
axes(handles.figureVOI)
imshow(handles.voi(:, :, handles.actualSlice));
However, when I clic on the scroll bar, the GUI just scroll to cut nº 70 aprox., and then all then the GUI stops to update the axes. If I close the window and try to run the GUI again, and MATLAB shows me a system error.
I want to know what I'm doing bad, and if there is another way to do what I need to do. Thanks a lot! :)
This is fairly easy question. You may have have different axis names and axes positioned at different locations.Then you route your images to the respective axes depending on which ever you want to choose to work with as the axes and you can choose both at the same time. Hope this helps. Good luck.
Related
I have a GUI with two axes. The first one for original image while the second one is for interpolated image.
First in my code, I use imrect to select part of the original image and then I crop that part using imcrop . After that I display the cropped image in both axes.
What I want is to know how to zoom in the first axes (the original image) and it shows the same zooming the second axes ( interpolated image ) automatically.
Thanks a lot in advance.
It is not clear the relationship between the two actions you mention in your question:
using imrect and imcrop to work on the image
zooming on one axes and have the same zoom on the second
A possible solution to automatically apply the zoom made on the first axes to the second one could be using the linkaxes built-in function.
If in your GUI you have two axex with, respectively, tag axes1 and axes2, you can add the following statements in the GUI OpeningFcn
linkaxes([handles.axes1 handles.axes2])
This allows automatically applying the zoom you make on axes1 also to axes2.
Hope this helps.
I am struggling to find a good contour detection function that would count the number of contour in bw images that I have processed using some previous tools. As you can see, my profile picture is an example of such images,
,
In this image, ideally, I wish to have a function which counts four closed contour.
I don't mind if it also detects the really tiny contours in between, or the entire shape itself as extra contours. As long as it counts the medium sized ones, I can fix the rest by applying area threshold. My problem is that any function I have tried detects only one contour - the entire shape, as it cannot separate it to the su-conours which are connected to one another.
Any suggestions?
Here is my shot at this, although your question might get closed because it's off-topic, too broad or a possible duplicate. Anyhow I propose another way to count the number of contours. You could also do it using bwboundaries as was demonstrated in the link provided by #knedlsepp in the possible duplicate. Just for the sake of it here is another way.
The idea is to apply a morphological closure of your image and actually count the number of enclosed surfaces instead instead of contours. That might end up being the same thing but I think it's easier to visualize surfaces.
Since the shapes in your image look like circle (kind of...) the structuring element used to close the image is a disk. The size (here 5) is up to you but for the image you provided its fine. After that, use regionprops to locate image regions (here the blobs) and count them, which comes back to counting contours I guess. You can provide the Area parameter to filter out shapes based on their area. Here I ask the function to provide centroids to plot them.
Whole code:
clear
clc
close all
%// Read, threshold and clean up the image
Im = im2bw(imread('ImContour.png'));
Im = imclearborder(Im);
%// Apply disk structuring element to morphologically close the image.
%// Play around with the size to alter the output.
se = strel('disk',5);
Im_closed = imclose(Im,se);
%// Find centroids of circle-ish shapes. Youcan also get the area to filter
%// out those you don't want.
S = regionprops(~Im_closed,'Centroid','Area');
%// remove the outer border of the image (1st output of regioprops).
S(1) = [];
%// Make array with centroids and show them.
Centro = vertcat(S.Centroid);
imshow(Im)
hold on
scatter(Centro(:,1),Centro(:,2),40,'filled')
And the output:
So as you see the algorithm detected 5 regions, but try playing a bit with the parameters and you will see which ones to change to get the desired output of 4.
Have fun!
I have searched the internet for a solution to the question above but have had no luck up to now. I have been producing a number of 2D plots where the origin of (0,0 point) is represented by an image. I have made these by plotting the data on an image, where the image is all white apart from the desired symbol at the center point (so I can reshape it as needed). I then move the axis so they cross at the center point. This all works fine, but I now have to create a number of plots using ‘fill’ to place two shaded areas on the plot that overlap in the center. This causes the symbol to be difficult to see even using ‘alpha’.
I therefore have two options to get the desired effect, both requiring me to put an image on top of the figure after the data is plotted. These options are:
1) I place the image on top of the plot and apply alpha to it (May not look very good as it will mute the plot).
2) The better option would be to crop the image around the symbol and then position it on top of the plot so the image center is at the origin (I have no idea how to position the image this way).
Both methods need the image to be placed on top of the plot after the data is plotted. I have tried 'hold on' and calling 'figure(imagesc(Image))' neither work. I have Matlab 2012b but no toolboxes (so cannot use subimage etc.)
Thanks for any help you can give
You can set the transparency of individual pixels of an image using the 'AlphaData' option. So, you can plot the overlay as follows:
% plot your data normally
...
hold on
% assuming the overlay is a 11x11 image
image(-5:5,-5:5,image_matrix,'AlphaData',alpha_matrix);
image_matrix would obviously be the matrix with your image data stored in it, while alpha_matrix would be a matrix of the same size as image_matrix. Every pixel you want to show would have a value of 1, every pixel you want to hide (the white pixels) would be 0.
I want to create a 5 dimensional plotting in matlab. I have two files in my workspace. one is data(150*4). In this file, I have 150 data and each has 4 features. Since I want to classify them, I have another file called "labels" (150*1) that includes a label for each data in data files. In other words the label are the class of data and I have 3 class: 1,2,3
I want to plot this classification, but i can't...
Naris
You need to think about what kind of plot you want to see. 5 dimensions are difficult to visualize, unless of course, your hyper-dimensional monitor is working. Mine never came back from the repair shop. (That should teach me for sending it out.)
Seriously, 5 dimensional data really can be difficult to visualize. The usual solution is to plot points in a 2-d space (the screen coordinates of a figure, for example. This is what plot essentially does.) Then use various attributes of the points plotted to show the other three dimensions. This is what Chernoff faces do for you. If you have the stats toolbox, then it looks like glyphplot will help you out. Or you can plot in 3-d, then use two attributes to show the other two dimensions.
Another idea is to plot points in 2-d to show two of the dimensions, then use color to indicate the other three dimensions. Thus, the RGB assigned to that marker will be defined by the other three dimensions. Of course, that means you must be able to visualize what the RGB coordinates of a color represent, so you need to understand color as it is represented in an RGB space.
You can use scatter3 to plot your data, using three features of data as dimensions, the fourth as color, and the class as different markers
figure,hold on
markerList = 'o*+';
for iClass = 1:nClasses
classIdx = dataClass==iClass;
scatter3(data(classIdx,1),data(classIdx,2),data(classIdx,3),[],data(classIdx,4),...
'marker',markerList(iClass));
end
When you use color to represent one of the features, I suggest to use a good colormap, such as pmkmp from the Matlab File Exchange instead of the default jet.
Alternatively, you can use e.g. mdscale to transform your higher-dimensional data to 2D for standard plotting.
There's a model called SOM (Self-organizing Maps) which builds a 2-D image of a multidimensional space.
I want to write a software that reads the satellite data from a text file and plots graph for different parameters of the oceans. The idea came from Oceonographic Data View(ODV).
My problem is plotting a graph on an image of the Indian ocean, where the image must be overlapped with the graph. Also, on zooming the area, the image with the graph could be zoomed.
How can I do this?
To load and display images, the Displaying Bit-Mapped Images tutorial from MathWorks may not be a bad place to start.
To overlay plots on the image, using hold on followed by plot should work.
An important part will be to have a sensible metric when displaying your image that allows you to place your overlays accurately. In the example below, notice the first and second arguments to image that define this; you could replace it by say linspace(0,1,size(X,1)) if you wanted it scaled between 0 and 1 instead of between 1 and 480 as below.
load mandrill
image(1:480,1:500,X) % display image
colormap(map)
hold on % prevent subsequent plot commands from destroying the image
plot([1 480],[100 100],'w','LineWidth',2) % plot an overlay line