Cone beam CT simulation 1.0

Cone beam CT simulationBy: Deshan Yang, PhDDepartment of radiation oncology, school of medicine, Washington University in Saint LouisEmail: dyang@radonc.wustl.eduFiles:compute_projections.m - the main program, to compute all projection and save the 2D projection images into a foldercompute_one_projection.m - Called by the main program to compute only one projection imagestraight_line_integral.m - The core function to compute a line integral through a 3D matrixA lot of lines are commented out in this file because the file was originally writtenin MATLAB only, and laterly rewritten into c for speed improvement.straight_line_integral_inner.c - This is what rewritten in C from the straight_line_integral.msort_ts1_ts2.c - A utility function to combine two sorted array into one sorted array.It is written in c to improve the speedcreate_CSV_file_for_OSCaR.m - To create the CSV file which is used in OSCaR CBCT reconstruction(http://www.cs.utoronto.ca/~nrezvani/OSCaR.html)However, OSCaR does not support the saved mat data files without modification.I have the modified OSCaR functions.load_all_projection_images.m - Loading all projection images from a folder into a 3D volumemake_sure_positive.m - A small utility functionBinary files:*.mexw32, *.mexw64 The compiled binary MEX files for 32-bit and 64-bit windowsOther files: - For different ways to compute projections. They are not in use anymore becausethey are either much slower or less accurateHow to setup the 3D data:You need to prepare an image 3D volume as the digital phantom (or patient, or object, whatever you call it).For this main function: compute_projections(xs,ys,zs,data3d,mode,output_folder)xs: the x coordinates of the image pixels in an arrayys: the y coordinates of the image pixels in an arrayzs: the z coordinates of the image pixels in an arrayxs, ys and zs should be centered at [0,0,0] which is the CBCT isocenter.About computation performance:The straight_line_integral function is partially written in c. It is very accurate and fairly fast.The computation of projection implemented here is both faster and more accurate than the radon transformation code in MATLAB.For a 3D matrix (512x512x176), it takes about 35 seconds to compute one 2D projection in resolution of 512x384 on a DELL with 2.33 GHz CPU.Computation does not need a lot of RAM from my understanding.

Requirements:	No special requirements
Platforms:	Matlab
Keyword:	Anymore,  Bit,  Digital,  Prepare,  Projections,  Setup,  Windows
Users rating:	0/10