I want to ask how this coefficient is calculated and can the coefficient in the picture be used as a general purpose if I have the airburst data and the projection data
I tried to implement it myself with matlab but I didn't get very good results.
Do I need to normalize the input data in the program
Here is my matlab code I want to implement the fitting coefficient of
FSRF But it didn't work out well
% Using ImageJ for operations:% 1. Extract the last 10 frames of the open
exposure, convert to 32-bit, compute the average, draw ROI, measure, and save
as an Excel file
% 2. Extract the stack for the dark field, convert to 32-bit, draw ROI, use
multi-measure, and save as an Excel file
% 3. Split the stack and merge the stack
% 4. Combine into one Excel file with open exposure data first and dark field
data following
% 5. Copy the mean to a .txt file
% Result: mean.txt
mean2 = table2array(mean); % Convert imported table type to array type
m = mean2(1);
n = mean2(2:end);
nm = n / m;
% Normalization
FSRF = nm;
x = 1:510; % Number of dark field frames
x = x';
y = FSRF; % Dark field data
% Fitting function
fitfunc = @(params, x) (params(1) * exp(-params(2) * x) + params(3) *
exp(-params(4) * x) + params(5) * exp(-params(6) * x) + params(7) *
exp(-params(8) * x));
initialGuess = [7e-3, 0.001, 1e-2, 0.01, 1e-2, 0.08, 3e-2, 0.6]; % Initial
values
paramsFit = lsqcurvefit(fitfunc, initialGuess, x, y);
B1_fit = paramsFit(1);
A1_fit = paramsFit(2);
B2_fit = paramsFit(3);
A2_fit = paramsFit(4);
B3_fit = paramsFit(5);
A3_fit = paramsFit(6);
B4_fit = paramsFit(7);
A4_fit = paramsFit(8);
y_fit = fitfunc(paramsFit, x);
plot(x, y, 'ro', x, y_fit, 'b-');
grid on
legend('Sample Data', 'Fitted Curve');
save AB.mat A1_fit A2_fit A3_fit A4_fit B1_fit B2_fit B3_fit B4_fit
Here is the program I used to fit the coefficients in matlab into c++
// TaoSunLagCorrectionTest.cpp : Defines the entry point for the console
application.//
#include "stdafx.h"
#include "TaoSunLagCorrection.h"
#include "rtkLagCorrectionImageFilter.h"
#include <chrono> // For timing
#include <fstream> // For file operations
// Suppress fopen warnings
#pragma warning(disable:4996)
int main()
{
int height = 1328;
int width = 1024;
int angles = 360;
//-------------------- Read projection data ----------------
FILE* file1;
const char* filename1 =
"E:/TaoSunCUDA12/LagCorrection/data/Stack50-409_110kv 15macu 0.5mm 50hz - CT
Phantom - full-fan.raw";
// Buffer to store read data
float* proj1 = (float*)malloc(height * width * angles *
sizeof(float));
if (proj1 == NULL)
{
printf("Memory allocation failed.\n");
return -1;
}
file1 = fopen(filename1, "rb");
if (file1 == NULL)
{
printf("Cannot open file %s\n", filename1);
return -1;
}
// Read data from file into memory (vector)
printf("Starting to read projection ... \n");
fread(proj1, sizeof(float), height * width * angles, file1);
fclose(file1);
//--------------------- Correction ----------------------
float* projoutput = (float*)malloc(height * width * angles *
sizeof(float));
// Start timing
auto start_time = std::chrono::high_resolution_clock::now();
// Lag correction parameters: detector (inherent
characteristics), frame rate (default binning mode)
printf("Starting lag correction ... \n");
float m_A[4] = { 0.7055f, 0.141f, 0.0212f, 0.0033f };
float m_B[4] = { 2.911e-3f, 0.4454e-3f, 0.0748e-3f, 0.0042e-3f };
taoSun_LagCorrection(projoutput, proj1, m_A, m_B, height, width,
angles);
// End timing
auto end_time = std::chrono::high_resolution_clock::now();
// Output elapsed time
std::chrono::duration<double> elapsed = end_time - start_time;
std::cout << "Total execution time: " << elapsed.count() << "
seconds" << std::endl;
// After processing all projections, write the large memory data
to a file in one go
printf("Starting to write corrected projection ... \n");
std::ofstream
outputFile("E:/TaoSunCUDA12/LagCorrection/data/output0902.raw",
std::ios::binary); // Open a new raw file for writing processed data
if (!outputFile.is_open())
{
std::cerr << "Error: Cannot open output raw file!"
<< std::endl;
return EXIT_FAILURE;
}
size_t totalSize = angles * height * width * sizeof(float);
// Pre-calculate total memory required for all projection data
outputFile.write(reinterpret_cast<const char*>(projoutput),
totalSize);
outputFile.close(); // Close the file
// Release the large allocated memory
free(projoutput);
free(proj1);
std::cout << "\n\nTest PASSED! " << std::endl;
return 0;
}
366B5C00@EDDFEE43.CA4C246700000000.png
Description: Binary data
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