Can Color Detect Cancer?Dead or Not?How To Detect Cancer?Spectral Information AnalysisImage AcquisitionImage RegistrationRaw Spectral DataMisalignmentSlide 9Registration of Multi modal ImagesLaplacian of Gaussian FilterFiltered ImagesShi & Tomasi Affine RegistrationRegistered Spectral ImagesSlide 15Before and AfterColor Models to Extract Spectral SignalColor DeconvolutionNon-Negative Matrix FactorizationICADiscussionCan Color Detect Cancer?Andrew Rabinovich12/5/02Dead or Not?E – 300% cancerous DEAD F – 0% cancerous HEALTHYHow To Detect Cancer?•Spectral Information •Spetial Information TextureSpectral Information Analysis•Proper Image Acquisition•Pre-processing(image registration)•Color Information ExtractionImage AcquisitionRGB vs. HyperspectralImage RegistrationRegistering spectral bands with each other is absolutely unavoidable!!!Acquisition system instability & optical aberrations result in spectral stack misalignmentRaw Spectral DataShort Band Pass (Blue)Long Band Pass (Red)MisalignmentMisalignmentRegistration 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 filterLaplacian of Gaussian Filter0.1 0.5 15(-1.9694, 2.1693) (-1.7186, 2.0336) (-1.9646, 2.1624)10(-1.9264, 2.1329) (-1.8773, 2.1047) -1.9599 2.159220(-1.8815, 2.1150) (-1.7773, 2.0511) -1.9559 2.163350(-1.8809, 2.1283) (-1.7986, 2.0602) -1.9472 2.1762Mean Shift: (-1.8970, 2.1253)Filtered ImagesLow Band FilteredHigh Band FilteredShi & Tomasi Affine RegistrationDetermine the motion based on an Affine transformationdDx Transformation is found to sub-pixel resolutionRegistered Spectral ImagesRegistered Spectral ImagesBefore and AfterColor Models to Extract Spectral Signal•Color Deconvolution•Non-Negative Matrix Factorization•Independent Components AnalysisColor DeconvolutionNon-Negative Matrix FactorizationICADiscussion•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
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