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Can Color Detect Cancer: Spectral Analysis for Early Detection

Explore how color information extraction and spectral analysis can aid in early cancer detection through image registration and signal separation techniques.

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Can Color Detect Cancer: Spectral Analysis for Early Detection

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  1. Can Color Detect Cancer? Andrew Rabinovich 12/5/02

  2. Dead or Not? E – 300% cancerous  DEAD F – 0% cancerous  HEALTHY

  3. How To Detect Cancer? • Spectral Information • Spetial Information  Texture

  4. Spectral Information Analysis • Proper Image Acquisition • Pre-processing(image registration) • Color Information Extraction

  5. Image Acquisition RGB vs. Hyperspectral

  6. Image Registration Registering spectral bands with each other is absolutely unavoidable!!! Acquisition system instability & optical aberrations result in spectral stack misalignment

  7. Raw Spectral Data Short Band Pass (Blue) Long Band Pass (Red)

  8. Misalignment

  9. Misalignment

  10. Registration of Multi modal Images • No brightness constancy • Common features at high resolution • Individual features at low resolution • Suppress the individual and extract the common using a high pass filter

  11. Laplacian of Gaussian Filter

  12. Filtered Images Low Band Filtered High Band Filtered

  13. Shi & Tomasi Affine Registration Determine the motion based on an Affine transformation Transformation is found to sub-pixel resolution

  14. Registered Spectral Images

  15. Registered Spectral Images

  16. Before and After

  17. Color Models to Extract Spectral Signal • Color Deconvolution • Non-Negative Matrix Factorization • Independent Components Analysis

  18. Color Deconvolution

  19. Non-Negative Matrix Factorization

  20. ICA

  21. Discussion • To quantify the separation of spectral signals, each of the dies must be imaged independently and compared with the separated signal • This study was done with RGB, however, Hyperspectral is a MUST

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