Geometry-calibration-for-tomographic-x-ray-imaging-systems

An Matlab implementation for geometry calibration of an x-ray imaging system.

The methods and algorithm are inspired by Li, Xinhua, Da Zhang, and Bob Liu. "A generic geometric calibration method for tomographic imaging systems with flat-panel detectors—A detailed implementation guide." Medical physics 37, 7 (2010): 3844-3854.

How to install?

Drag the function file (solveGeo.m) into your project and/or add it to your matlab function search path.

How to use?

Example

Check the provided example for how to use the script.

General usage

The function will output three values corresponding to the x-ray focal spot positions (in pixels) x, y, and z in the detector coordinate system.

Load the 3D coordinates of the features of the calibration phantom in Matlab. We recommend format this file into a m-by-3 matrix, where m is the total number of features in the phantom. The first column is the x coordinates of the features in the phantom coordination system. The second and third column corresponds the y and z coordinates.

IMPORTANT: your phantom MUST have at least 6 features.
In the x-ray projection image of the phantom, use your own method to identify m features in the image. Find the coordinates of each feaute in the projection image coordinate system. And make a m-by-2 matrix 2D, where the first column is the x coordinate of the feature in the image plane (u), and the second column is the y coordinates of the features in the image plane (v).

IMPORTANT: the 2D feaure matrix MUST correspond to the 3D feature matrix.
Calculate the focal spot location using the provided function solveGeo.m.

[x,y,z] = solveGeo(feature3D, feature2D)
The result from step 3 is in the units of pixels in the detector coordinate system. To convert the number into real dimensions, multiply each value by the pixel size of the detector.

Batch process a sequence of tomographic projection images

If you want to batch process the whole sequence, you can loop through the projection images, apply the function on each image to calculate the focal spot location for the image, and summarize the results in an array. A pseudocode snippets is provided as example.

load('feature3D.mat');
pixel_size = yourImagePixelSizeInMilimeters;
N = numel(imageSequence);
Location = zeros(N,3);
for i = 1:N
    image = loadYourIthImage(imageSequence,i);
    feature2D = yourAlgorithmToFind2DFeatures(image); %% Implement your own methods to locate the features here.
    Location(i,:) = solveGeo(feature3D,feature2D);
end
%% to convert values into mm
Location = Location * pixel_size;

##Reference Li, Xinhua, Da Zhang, and Bob Liu. "A generic geometric calibration method for tomographic imaging systems with flat-panel detectors—A detailed implementation guide." Medical physics 37, 7 (2010): 3844-3854.

##License The MIT License (MIT)

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

jingsh / Geometry-calibration-for-tomographic-x-ray-imaging-systems