1. Algorithm for Morphological Cancer Detection
Carmalyn Lubawy
Melissa Skala
ECE 533 Fall 2004 Project

2. Background
Cancer diagnosis relies on morphological differences between normal and cancerous tissues
Cancerous cells are more disorganized than normal cells
Multiphoton microscopy has been used to evaluate cell morphology in normal and cancerous tissues
Normal
Cancer
255
128

3. Goal
Develop an algorithm that provides relative differences in cell organization between multiphoton images of normal and cancerous tissues1
1. Fitzke, F.W., Fourier Transform Analysis of Human Corneal Endothelial Specular Photomicrographs. Exp Eye Res,

4. Algorithm Flowchart Input Image Median Filter Unsharp Mask Threshold
FFT
Log
Mean Filter
Line Plot

5. Original data
Normal 1
Cancer 1
Normal 2
Cancer 2

6. After Median filter
Normal 1
Cancer 1
Normal 2
Cancer 2

7. After Unsharp Mask
Normal 1
Cancer 1
Normal 2
Cancer 2

8. After Threshold
Normal 1
Cancer 1
Normal 2
Cancer 2

9. After FFT
Normal 1
Cancer 1
Normal 2
Cancer 2

10. After Log
Normal 1
Cancer 1
Normal 2
Cancer 2

11. After Mean Filter
Normal 1
Cancer 1
Normal 2
Cancer 2

12. Final graph
Normal 1
Cancer 1
Normal 2
Cancer 2

13. Conclusions
Normal cells have peak at a spatial frequency of about 127 mm-1
Normal cells are about 7.8 mm wide
Image processing allows for automatic evaluation of differences in cell organization between normal and cancerous tissues