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Detection of Retinal Vessels inFundus Images throughTransfer Learning of Tissue SpecificPhoton Interaction Statistical Phy...
Contents• Motivation• Physics of Retinal Imaging• Statistical Physics of Tissue-Photon Interaction• Transfer Learning of T...
Motivation• Fundus imaging is used forscreening of– Diabetic retinopathy– Glaucoma– Age-related macular degeneration– Hype...
Physics of Retinal Imaging10 Apr 2013 ISBI 2013 - ThCT1.5 [Debdoot Sheet] 4Spatially varying spectral reflectance pattern ...
Statistical Physics of Tissue-PhotonInteraction10 Apr 2013 ISBI 2013 - ThCT1.5 [Debdoot Sheet] 5Photo-current readoutDark-...
Statistical Physics of Tissue-PhotonInteraction10 Apr 2013 ISBI 2013 - ThCT1.5 [Debdoot Sheet] 6Spatial response of the co...
Statistical Physics of Tissue-PhotonInteraction10 Apr 2013 ISBI 2013 - ThCT1.5 [Debdoot Sheet] 7( ) ( ) [ ]21,!,| λλλρρρ∈′...
Learning of TPI10 Apr 2013 ISBI 2013 - ThCT1.5 [Debdoot Sheet] 8{ } { }vascular-nonvessel,| ∈∀Θ ωωAssuming there exists a ...
Vessel Detection Framework10 Apr 2013 ISBI 2013 - ThCT1.5 [Debdoot Sheet] 9Learn TPI ModelTraining Image Ground Truth Labe...
Performance Assessment10 Apr 2013 ISBI 2013 - ThCT1.5 [Debdoot Sheet] 10
Performance Assessment10 Apr 2013 ISBI 2013 - ThCT1.5 [Debdoot Sheet] 11
Performance Assessment10 Apr 2013 ISBI 2013 - ThCT1.5 [Debdoot Sheet] 12
Take Home Message• Photons interact characteristically with different tissues– This is manifested through the spatially va...
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Detection of Retinal Vessels in Fundus Images through Transfer Learning of Tissue Specific Photon Interaction Statistical Physics

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Detection of Retinal Vessels in Fundus Images through Transfer Learning of Tissue Specific Photon Interaction Statistical Physics

  1. 1. Detection of Retinal Vessels inFundus Images throughTransfer Learning of Tissue SpecificPhoton Interaction Statistical PhysicsDebdoot SheetSchool of Medical Science and TechnologyIndian Institute of Technology Kharagpur, Indiadebdoot@smst.iitkgp.ernet.in10 Apr 2013 1ISBI 2013 - ThCT1.5 [Debdoot Sheet]Authored by: D. Sheet, S. P. K. Karri, S. Conjeti, S. Ghosh, J. Chatterjee and A. K. Ray
  2. 2. Contents• Motivation• Physics of Retinal Imaging• Statistical Physics of Tissue-Photon Interaction• Transfer Learning of TPI• Vessel Detection in Fundus Images – Framework• Performance Assessment10 Apr 2013 ISBI 2013 - ThCT1.5 [Debdoot Sheet] 2
  3. 3. Motivation• Fundus imaging is used forscreening of– Diabetic retinopathy– Glaucoma– Age-related macular degeneration– Hypertension and Stroke inducedchanges• Challenges include– Vessels, fovea, optic disc –localization and segmentation– Pathology detection– Image quality assessment• Vessel detection in white light Fundusimaging– Necessary for reporting of pathologies– Reduces clinician’s dependency on FA– Solutions include• Staal et al. (2004)• Niemeijer et al. (2004)• Zana et al. (2001)• Jiang et al. (2003)• Martinez-Perez et al. (1999)• Chaudhuri et al. (1989)• Limitations― Less Accurate (< 94%)― High inter-observer variability (κ<0.71)― Performance less than 2ndhuman-observer(Acc.=95%, κ=0.76)10 Apr 2013 ISBI 2013 - ThCT1.5 [Debdoot Sheet] 3
  4. 4. Physics of Retinal Imaging10 Apr 2013 ISBI 2013 - ThCT1.5 [Debdoot Sheet] 4Spatially varying spectral reflectance pattern of the retinaSpatially varying illumination modelPSF of the ophthalmoscopeSpectral transmission of ophthalmoscope( ) ( ) ( ) ( )[ ] ( )λλλλλ tyxpyxLyxRyxB ,,,,,,,, ∗=
  5. 5. Statistical Physics of Tissue-PhotonInteraction10 Apr 2013 ISBI 2013 - ThCT1.5 [Debdoot Sheet] 5Photo-current readoutDark-current noise Shot noiseReadout noise Quantization noiseExternal quantum efficiency of sensorRate of photon induced electron generationIntegration time Amplification factorQRSDC NANNNTKD ++++= )( ρTKNNNN QRSDC ρ<<,,,TTAKD ′=≅ ρρ
  6. 6. Statistical Physics of Tissue-PhotonInteraction10 Apr 2013 ISBI 2013 - ThCT1.5 [Debdoot Sheet] 6Spatial response of the collection siteInternal quantum efficiency of sensorSpectral irradiance pattern incident on the sensor( ) ( ) ( )∫∫∫=λλλλρ ddydxqyxSyxBy xr ,,,
  7. 7. Statistical Physics of Tissue-PhotonInteraction10 Apr 2013 ISBI 2013 - ThCT1.5 [Debdoot Sheet] 7( ) ( ) [ ]21,!,| λλλρρρ∈′∝′′−deTTdfTd( )Tdf RR′,| ρ( )Tdf GG′,| ρ( )Tdf BB′,| ρDistribution for GREEN sensor elementDistribution for BLUE sensor elementDistribution for RED sensor element[ ] ( )ddET var==′ρ[ ]{ } [ ] { } { }nkkkkkBGR ,,,,,, 21 ∈∈∀Φ=Θ λλ[ ] [ ] [ ][ ]kkdET λλλ ρ =′=Φ Multiscale photon density estimationTPI Model
  8. 8. Learning of TPI10 Apr 2013 ISBI 2013 - ThCT1.5 [Debdoot Sheet] 8{ } { }vascular-nonvessel,| ∈∀Θ ωωAssuming there exists a primal relation in TPI for each tissue type{ }trainI be a set of images in this relation holds valid and wherethese tissues are marked{ }( )train;,| IIΘωH Response of the learnt model providesprobability of finding vessels
  9. 9. Vessel Detection Framework10 Apr 2013 ISBI 2013 - ThCT1.5 [Debdoot Sheet] 9Learn TPI ModelTraining Image Ground Truth LabelsTest ImageLearn TPI ModelVessel Detection Probab.{ }( )train;,| IIΘωH
  10. 10. Performance Assessment10 Apr 2013 ISBI 2013 - ThCT1.5 [Debdoot Sheet] 10
  11. 11. Performance Assessment10 Apr 2013 ISBI 2013 - ThCT1.5 [Debdoot Sheet] 11
  12. 12. Performance Assessment10 Apr 2013 ISBI 2013 - ThCT1.5 [Debdoot Sheet] 12
  13. 13. Take Home Message• Photons interact characteristically with different tissues– This is manifested through the spatially varying spectral reflectancemodel R(∙)• The stochastic nature of TPI accounts for uncertainties inobservations.– Learning of TPI statistical physics overcomes these uncertainties.• Transfer learning is a good framework for solving such 2-levellearning tasks10 Apr 2013 ISBI 2013 - ThCT1.5 [Debdoot Sheet] 13

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