My new textbook and job

So many things have happened in the last few months and I have not had time to add new entries to my blog. The first is the textbook that I co-authored with Sridevi Pudipeddi which was released at the end of February.  It was marathon run to complete and get the book ready for publishing.  I also moved to a new job in California in April.


During my work as image processing consultant at the Minnesota Supercomputing Institute, I have worked with students in various disciplines of science.  In all these cases, images were acquired using x-ray, CT, MRI, Electron microscope and Optical microscope.  It is important that the students have knowledge of both the physical methods of obtaining images and the analytical processing methods to understand the science behind the images. Thus, a course in image acquisition and processing has broad appeal across the STEM disciplines and is useful for transforming undergraduate and graduate curriculum to better prepare students for their future.

There are books that discusses image acquisition alone and there are books on image processing alone.  The image processing algorithms depend on the image acquisition method. We wrote a book that discusses both, so that students can learn from one source. You can check out sample chapter of the book at reedwith.us. You can buy the book at Amazon by clicking on the image below.

I also changed job.  I started working as Senior Engineer at Elekta in Sunnyvale, CA. I will be focussing mostly on x-ray and CT during my tenure at Elekta.

Plotting three variable graph using Matlab

Recently, a user wanted to visualize the effect of four different test conditions causing changes in three different parameters.  This visualization will help understand the effect of change in one parameter on others.

The user suggested to plot the three parameters along three different axis.  For example, the three parameters with values of [95.0, 1.2, 4.5] will correspond to the co-ordinates of [95.0, 0.0, 0.0], [0, 1.2, 0] and [0, 0, 4.5].  Using these coordinates, one can form a triangle.  The shape of the triangle will be different for the various test conditions and it will be easier to visualize the effect of the test conditions on the parameters.

I was not initially sure whether I could accomplish this using a standard Matlab plots.  I did a search on google but was not successful, as I did not have a good search term.  I resorted to creating a OpenGL program using GL_TRIANGLES.   I later found that Matlab has similar functionality.  Triangles and other polygons can be easily constructed in Matlab using the "patch" function.

The program

The vals contains the value that needs to be plotted.  Each column is one test condition and the rows contain the parameters that need to be plotted along the axis.  The "for loop" runs for each column and creates the x, y and z coordinates and stores them in a, b and c.  The patch command will create a triangle using the three coordinates.  The last parameter in the patch command is the color of the patch.  By default, patch is rendered with all surface opaque and the color specified in the patch command.  Since there are too many surfaces, the patch was made transparent and the edges were given different line style and thickness using "plottools".  The resulting plot can be seen below.

% The variables vals has three rows and four columns. The columns contain co-ordinate values along x,y,z axis respectively.  The four rows will result in four triangular surfaces.

vals = [11.11,3.55,4.97,2.14;
         2.61,4.63,4.53,4.66;
         91.2,79,93.4,56.3];

figure;
hold on;
for i = 1:size(vals,2) % For each column in vals
   a = [vals(1,i)     0            0]
   b = [0         vals(2,i)        0]
   c = [0             0       vals(3,i)]
   patch(a,b,c,10*i)
end
grid on;