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Spectrophotometric analysis of two All-Ceramic materials. Varun Singh Barath University of Cologne, Germany. Dilemma. Esthetic Dentistry. Since ancient times – teeth have been an integral part of the face Animal teeth and Ivory– all carved in the form of human teeth

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spectrophotometric analysis of two all ceramic materials

Spectrophotometric analysis of two All-Ceramic materials

Varun Singh Barath

University of Cologne, Germany

esthetic dentistry
Esthetic Dentistry
  • Since ancient times – teeth have been an integral part of the face
  • Animal teeth and Ivory– all carved in the form of human teeth
  • Early 16th Century – Mineral teeth
esthetic dentistry5
Esthetic Dentistry
  • Metal Ceramic restorations – 4 decades ago were the “State of Art”
  • All-Ceramic restorations – advancements in last decade have made them popular
    • Increase in strength
    • Better biocompatiblity
    • Excellent optical properties
slide6

PART 1: Spectrophotometric analysis of two All-Ceramic materials with the effect of the background shade on the final shade

  • PART 2: Proposed Model for Color Prediction using Kubelka-Munk theory and Artificial Neural Networks
slide7

Spectrophotometric analysis of two All-Ceramic materials with the effect of the background shade on the final shade

some aspects of color
Some aspects of Color
  • Color is the perception of light by the mind in response to a stimuli from the eye
  • It is a visual sensation
  • Different colors have different wavelengths
  • Visible part of the spectrum 380 – 750 nm
color systems
Color systems
  • Numerical representation of Color
  • International Commission of Illumination (Commission Internationale de l’Eclairage).
  • Important colorimetric systems are RGB, XYZ, CIELAB, CMC, Munsell system, to name a few
cielab system
CIELAB system

Courtesy: Handprint media

cielab system12
CIELAB system
  • Estd. 1976 (by the International Commission of Illumination (Commission Internationale de l’Eclairage))
  • L* - vertical, achromatic coordinate

0 (black) to 100 (white);

  • a* - horizontal, green/red coordinate,

-80 (green) to +80 (red);

  • b* - horizontal, blue/yellow coordinate

-80 (blue) to +80 (yellow);

cielab system13
CIELAB system

Courtesy: Handprint media

cielab system14
CIELAB system
  • C - saturation, representing the difference of a specific color in relation to gray color of the same lightness
  • H° - hue is represented in the ab plane

H=0° corresponds to red color,

H=90° corresponds to yellow,

H=180° corresponds to green,

H=270° corresponds to blue color

experimental design
Experimental Design
  • Aim: to study the effect of background shade on the final shade of All-Ceramic Systems (In-Ceram Alumina, Empress2)
  • Shades chosen: lighter than the lightest, darker than the darkest and one from the middle
  • Luting Agents: ZnPO4 , GIC, RLA
  • Background: Standard black and white
armamentarium
Armamentarium
  • Ceramic samples as clinical units

In-Ceram Alumina, 1,0 mm

In-Ceram Alumina, 1,4 mm

Empress 2, 1,4 mm

armamentarium19
Armamentarium
  • Micrometer (Mitutoyo, Japan)
armamentarium20
Armamentarium
  • Sample Preparation (Simulating a clinical All-Ceramic restoration)
armamentarium21
Armamentarium
  • Spectrophotometer (Dr. Lange GmBH, Berlin, Germany)

Spectral Range: 380 – 720nm

Viewing Geometry: d/8°

armamentarium22
Armamentarium
  • Standard Black and White Backgrounds
formula for color difference
Formula for color difference
  • ∆E = [(L w– L b)2 + (a w– a b)2 + (b w– b b)2] ½
  • ∆L = L w– L b
  • ∆a = a w– a b
  • ∆b = b w– bb
clinically significant color differences
Clinically significant color differences
  • ∆E > 3.7 : Very Poor match (Johnston and Kao, 1989)
  • ∆E > 2 : Clinically not acceptable (Touati et al, 1993)
  • ∆E ≤ 2 : Clinically acceptable (O‘Brien et al, 1990)
  • ∆E < 1 : Not appriciable (Kuehni and Marcus, 1990)
correlation l wb and e bcwc of translucency with the color change due to luting agent
Correlation:∆Lwb and ∆Ebcwc(of translucency with the color change due to luting agent)
  • Pearsons correlation (r):

Compolute = 0.13 p = 0.38 0.21 ±0.05 mm

GIC = 0.05 p = 0.76 0.24 ±0.04 mm

ZnPO = 0.82 p = 0.00 0.24 ±0.10 mm

conclusions
Conclusions
  • All-Ceramics due to their translucency have an effect of the luting agents and background shade (dentine/discolored tooth/post) on the final shade
  • The two All-Ceramics examined showed a shift in the the ∆a values due to black background (shift towards red) (reflection curves at various wavelengths to be investigated)
conclusions42
Conclusions
  • As ceramic thickness increases the effect of luting agent and background decreases
  • Depending on the luting agent the background shade can be partially masked
  • Luting agents have an effect on the final color
conclusions43
Conclusions
  • The outcome of the ceramic restorations cannot be predicted with accuracy
  • Not only the color, that is percieved by the eye is important but also the optical properties of the materials shoud be studied for predicting the outcome of the all ceramic restorations
future work
Future Work

Model for Color Prediction using Kubelka-Munk theory and Artificial Neural Networks for all ceramic restorations

kubelka munk theory
Kubelka-Munk theory
  • color mixing model which describes the reflectance and transmittance of a color sample with respect to the absorption and scattering spectra of the material
  • mathematical model used to describe the reflectance
  • considers the absorption and scattering in a colored sample of fixed thickness
kubelka munk theory46
Kubelka-Munk theory
  • four factors:
    • an absorption spectrum K(λ )
    • a scattering spectrum S(λ)
    • the sample thickness X
    • the reflectance spectrum of the substrate or backing Rp(λ )
kubelka munk km theory
Kubelka-Munk (KM) theory
  • Has been used to measure the reflectance of All-Ceramic materials (Miyagawa and Powers, (1982); Woolsey, G. D., W. M. Johnston, et al. (1984); Cook and McAree, (1985); ......................................... Davis, B. K., W. M. Johnston, et al. (1994))
  • “The data on the absorption/scattering coefficient ratio (K/S values) at certain wavelengths are necessary for the creation of a computer database and as well as for the computer color prescription”(Paravina R.D, (1999) )
artificial neural network ann
Artificial Neural Network (ANN)
  • The ANN technology is a computer system solution with a surprising capacity to learn from input data
  • computer-based algorithms which are modeled on the structure and behaviour of neurons in the human brain and can be trained to recognize and categorize complex patterns.
artificial neural network ann49
Artificial Neural Network (ANN)
  • Neural networks are well suited for data mining tasks due to their ability to model complex, multi-dimensional data
  • Some applications of ANN.

Stock market prediction

Weather prediciton

Speech recognition

Face recognition.........................

artificial neural network ann50
Artificial Neural Network (ANN)

Threshold Logical Unit

artificial neural network
Artificial Neural Network

Feed forward fully connected back propagation algorithm for weight adjustments

cielab for ann
CIELab for ANN ??
  • ADVANTAGES:
    • Easier access to CIELab data
    • Already existing databases
  • DISADVANTAGES:
    • More experimental work required
    • Does not predict the reflectance spectra at various thickness
colpres color prescription
ColPres (Color Prescription)
  • Development of an algorithm
  • Development of test Database (MySQL)
  • Testing the algorithm
  • Development of a Complete Database (MySQL)
  • Full implementaion of the algorithm (Java)
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