This code uses various fuzzy c-means algorithms to do tissue segmentation on mammography.
You just run main.py in editor or enter python main.py in command prompt.
(In img directory, there are images for the test. These images are part of mini-MIAS database.)
[Default Option]
- Algorithm: FCM
- Number of bits of input images: 8
- Number of clusters: 4
- Fuzziness degree: 2
- Max number of iterations: 100
- Threshold to check convergence: 0.05
- Plotting results
- Save results as image files (\output\FCM)
- If you want to replace the mini data with your own data, put your images to
imgdirectory or edit path for your direrectory inmain.py. - If you change parameters of your experiment, you can change parameters by changing the default value of the argument in
main.pyor you can you the command line in command prompt. - You can see all the adjustable parameters and usage.
python main.py --help
Example usage in the command prompt:
- Running the program with EnFCM algorithm:
python main.py --algorithm EnFCMorpython main.py -a EnFCM' - Running the program with 5 clusters:
python main.py --num_cluster 5orpython main.py -c 5 - Do not plot the results:
python main.py --plot_show 0
Iteration 0 : cost = 1572877.355810 Iteration 1 : cost = 16930.249564 Iteration 2 : cost = 62971.214897 Iteration 3 : cost = 220503.731791 Iteration 4 : cost = 668433.909952 Iteration 5 : cost = 507337.662709 Iteration 6 : cost = 175471.958149 Iteration 7 : cost = 114386.144020 Iteration 8 : cost = 73307.442600 Iteration 9 : cost = 44495.695964 Iteration 10 : cost = 25692.153765 Iteration 11 : cost = 17081.527860 Iteration 12 : cost = 12589.375744 Iteration 13 : cost = 9252.105186 Iteration 14 : cost = 6728.617855 Iteration 15 : cost = 4874.316781 Iteration 16 : cost = 3543.550238 Iteration 17 : cost = 2592.132178 Iteration 18 : cost = 1910.585002 Iteration 19 : cost = 1418.790884 Iteration 20 : cost = 1060.731109 Iteration 21 : cost = 797.630195 Iteration 22 : cost = 602.574438 Iteration 23 : cost = 456.886919 Iteration 24 : cost = 347.410607 Iteration 25 : cost = 264.742439 Iteration 26 : cost = 202.076947 Iteration 27 : cost = 154.435123 Iteration 28 : cost = 118.134485 Iteration 29 : cost = 90.428773 Iteration 30 : cost = 69.256245 Iteration 31 : cost = 53.061159 Iteration 32 : cost = 40.664660 Iteration 33 : cost = 31.170869 Iteration 34 : cost = 23.897207 Iteration 35 : cost = 18.322969 Iteration 36 : cost = 14.050185 Iteration 37 : cost = 10.774443 Iteration 38 : cost = 8.262844 Iteration 39 : cost = 6.336918 Iteration 40 : cost = 4.860020 Iteration 41 : cost = 3.727413 Iteration 42 : cost = 2.858808 Iteration 43 : cost = 2.192627 Iteration 44 : cost = 1.681706 Iteration 45 : cost = 1.289846 Iteration 46 : cost = 0.989259 Iteration 47 : cost = 0.758760 Iteration 48 : cost = 0.581969 Iteration 49 : cost = 0.446360 Iteration 50 : cost = 0.342367 Iteration 51 : cost = 0.262587 Iteration 52 : cost = 0.201409 Iteration 53 : cost = 0.154481 Iteration 54 : cost = 0.118486 Iteration 55 : cost = 0.090875 Iteration 56 : cost = 0.069699 Iteration 57 : cost = 0.053462 Iteration 58 : cost = 0.041010
| Algorithm | Result |
|---|---|
| FCM |  |
| EnFCM |  |
| MFCM |  |
- If it is not an 8-bit image, the code may needs to be modified.
- When there is a problem with the environment, you can try this command line in your command prompt.
pip install -r requirements.txt
- [1] L. Szilagyi and et.al. "MR brain image segmentation using an enhanced fuzzy C-means algorithm." IEEE/ Engineering in Medicine and Biology Society (ICat.) 2003.
- [2] Z. Chen and R. Zwiggelaar "A Modified Fuzzy C Means Algorithm for Breast Tissue Density Segmentation in Mammograms." IEEE/Information Technology and Applications in Biomedicine (ITAB) 2010.
- [3] J. Song and Z. Zhang "A Modified Robust FCM Model with Spatial Constraints for Brain MR Image Segmentation." Information 2019.
- https://github.com/ab93/SIFCM
- Need to improve performance to get a filtered image in MFCM algorithm.