What is the general formula for radon back projection for a javascript implementation? I'm aiming to implement a simulation of computed tomography back projection in javascript/HTML5 canvas.

Trying to figure the correct approach for doing a back projections and I have been studying the presentation below:

http://www.dtic.upf.edu/~afrangi/ibi/reconstruction_color_2.pdf. On pp. 9-13 of the above pdf presentation a step by step example of back projection is shown.

This example involves a 2x2 matrix (with 4 projections and a total of 10 line integrals) and computes the line integrals of each projection where the value of each corresponding line integral is added to each matrix cell, respectively. Subsequently the total number of line integrals is subtracted from the value of each matrix cell. Finally the resulting value in each matrix cell is divided by the number of projections minus one.

Does this approach hold in general for larger, say a 100x100 matrix with larger cell values, say around 100?
To implement projection the simplest way is to rotate your image then sum over a row or column. The simplest way to implement back projection is to take a line of your sinogram which is a projection from certain view (angle) then repeat that line to form an image then rotate that image regarding the projection view, then sum all of backprojected views.
There is a unique formula for continuous case but for discrete case there are many different implementation, this one is the simplest.  

Good luck.