1 / 13

Algorithm for Morphological Cancer Detection

Algorithm for Morphological Cancer Detection. Carmalyn Lubawy Melissa Skala ECE 533 Fall 2004 Project. 255. 128. 0. Background. Cancer diagnosis relies on morphological differences between normal and cancerous tissues Cancerous cells are more disorganized than normal cells

lholm
Download Presentation

Algorithm for Morphological Cancer Detection

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

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

  2. 255 128 0 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

  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, 1997. 65

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

  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

More Related