This code uses various fuzzy c-means algorithms to do tissue segmentation on mammography.

• Standard FCM
• Enhanced Fuzzy C-Means Algorithm (EnFCM)
• Modified FCM (MFCM)

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 img directory or edit path for your direrectory in main.py.
• If you change parameters of your experiment, you can change parameters by changing the default value of the argument in main.py or 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 EnFCM or python main.py -a EnFCM'
• Running the program with 5 clusters: python main.py --num_cluster 5 or python 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

1. If it is not an 8-bit image, the code may needs to be modified.
2. 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.