ICBM COMPUTATIONAL ANALYSIS OF CELL BEHAVIOUR IN DEVELOPING EMBRYOS |04|2007 Miguel Concha / Steffen Härtel Programa de Anatomía y Biología del Desarollo, Instituto de Ciencias Biomédicas, Facultad de Medicina, Universidad de Chile, Santiago, Chile

Muestra Microscopio Confocal (LSM) Imágenes I(x,y,z,c,t) Pretratamiento Segmentación Modelo Tridimensional Reconstrucción Visualización Parametrización Steffen Härtel | | Santiago | Chile

Bastones Conos (S, M, L) -> 10 8 Bastones -> 6·10 6 Conos: L : M : S (primates) 580 nm : 545 nm : 420 nm ~10: ~10: 1 en cantidad y sensitividad 3. Colores La fóvea Steffen Härtel | | Santiago | Chile

3. Colores -> 10 8 Bastones -> 6·10 6 Conos: [Azul] / [Amarillo]: [+S] / [M+L] [Verde] / [Rojo]: [M-L] / [L-M] Steffen Härtel | | Santiago | Chile S - Conos M - Conos L - Conos ‘Midget-Cell‘

3. Colores 10 8 Conos & bastones Nervus opticus 8· 10 5 Células horizontales Células bipolares [Glutamato]~1/I Células amacrin Celulas del Ganglio Células del ganglio Se conocen~15 tipos diferentes de células de ganglio. Steffen Härtel | | Santiago | Chile

3. Colores ->[I, L, M, S, x, y, t] - Receptores: - [Glu] ~ [Na + ] en ‘Off-cells‘ bipolares - [Glu] ~ [Na + ] -1 en ‘On-cells‘ bipolares ->[] = [] + [dI/dt, dL/dt, dM/dt, dS/dt] ->[] = [] + [z] - Activación/Inhibición lateral: - Células horizontales emiten GABA, en caso de una excitación homogenia en [x,y] ->[] = [] + [dI/dxy, dL/dxy, dM/dxy, dS/dxy] Steffen Härtel | | Santiago | Chile

3. Colores Steffen Härtel | | Santiago | Chile Representación simbólica o modelo individual del mundo real

3. Colores Steffen Härtel | | Santiago | Chile

3. Colores Steffen Härtel | | Santiago | Chile

3. Colores Steffen Härtel | | Santiago | Chile Alessandro Rizzi GIC - Graphic, Imaging and Color research group Università di Milano

3. Colores RGB (Red Green Blue), (R:0-255, G: 0-255, B:0-255) : R G B H V S HSV (Hue Saturation Value), (H:0-2 , S:0-1, V:0-1)

3. Colores The Hue Saturation Value (or HSV) model defines a color spacecolor space in terms of three constituent components: HueHue, the color type (such as red, blue, or yellow); Measured in values of by the central tendency of ist wavelength SaturationSaturation, the 'intensity' of the color (or how much greyness is present), Measured in values of 0-100% by the amplitude of the wavelength. ValueValue, the brightness of the color. Measured in values of 0-100% by the spread of the wavelength HSV is a non-linear transformation of the RGB color space.non-lineartransformationRGB color space

-> RGB.....Se puede usar muy bien para fines científicos pero no sirve para obtener una medida para lo que el ser humano califica como diferencia entre colores (R 1 G 1 B 1 ) y (R 2 G 2 B 2 ). -> Diferencia entre (H 1 S 1 I 1 ) y (H 2 S 2 I 2 ): 3. Colores

I( 290,267 ) = 220 r g b 0 : 220 : : 220 : : 220 : 255 Una mesa de color está definida por 3 vectores r, g, b de 8 bits c/u Amarillo (255, 255, 0) Negro (0, 0, 0) Rojo (255, 0, 0) Verde (0, 255, 0) Blanco (255, 255, 255) Cian (0, 255, 255) Magenta (255, 0, 255) Azul (0, 0, 255) red = [r 0, r 1,…...…...,r 255 ] green = [g 0, g 1,……...,g 255 ] blue = [b 0, b 1,……...,b 255 ] Un canal tiene 8 bits y se pueden codificar 256 colores o intensidades Steffen Härtel | | Santiago | Chile 3. Colores

r g b 000::::0::0000::::0:: : 200 : ::::0::0000::::0::0 3. Colores Steffen Härtel | | Santiago | Chile

r g b : 220 : ::::0::0000::::0::0 000::::0::0000::::0::0 3. Colores Steffen Härtel | | Santiago | Chile

3. Colores Steffen Härtel | | Santiago | Chile

3. Colores Steffen Härtel | | Santiago | Chile

ICBM COMPUTATIONAL ANALYSIS OF CELL BEHAVIOUR IN DEVELOPING EMBRYOS |04|2007 Miguel Concha / Steffen Härtel Programa de Anatomía y Biología del Desarollo, Instituto de Ciencias Biomédicas, Facultad de Medicina, Universidad de Chile, Santiago, Chile

Scaling Index Methods for the Automated Quantification of Colocalization in Fluorescence Microscopy Steffen Härtel | CECS | | Introduction 3| Statistics: PSF & PDF 2| Colocalization Scaling Index Methods C-SIMs 4| Diffusion C-SIM

6| Introduction: QueryStat in PubMed colocalization = colocalization + co-localization

6| Introduction: QueryStat in PubMed

6| Introduction: ClC-2 & … ?

6| Introduction: Global Methods PC = r’ Pearson's Product Moment Pearson's Correlation Coefficient …

6| Introduction: Global Methods

6| Introduction: Costes et al. 2004

6| C-SIM C-SIM(x i,y j,r) x i -> y j -> r=2 C-SIM(x i,y j,r) * I 1/2 (x,y) Imagenes I 1/2 (x,y) I2I2 I1I1 CSI C-SIM(x,y,r) PC = r’

6| C-SIM (PC)

6| C-SIMs Correlation Coefficient of Raw Images (CCRI) | Joint Moment of Standardized Images (JMSI):

6| PC, CCRI, & JMCI:  = 500

6| CCRI, & JMCI:  = 500

6| JMCI(r): r = 1 r = 2 r = 3 r = 4 r = 5 r = 6 r = 7

6| Auto – correlation & FCS: ‘Auto-correlation measures self-similarity of a time signal and highlights characteristic time constants of underlying processes.’

6| Auto – correlation & FCS: