1. SICSURFIS – SPECTRAL IMAGING OF COMPLEX SURFACE TOMOGRAPHIES
Principal investigator (PI): Docent Ilkka Pölönen (JyU), Principal Scientist Heikki Saari (VTT), Professor Jarmo Alander (UVa), Professor Annamari Ranki (HUCH)

2. Challenge

3. Objectives
To minimize spectral imager developing mems-Fabry-Pérot interferometers capable to cover wide spectral range with one component ( nm)
To extend spectral range of imager to nm
To design integrated led-light source with Fabry-Perot component
To study polarization effects in order to reduce specular high-light reflections
To design FPGA implementation for image guided filters and other time critical parts of the software running on Soc-FPGA (Soc-FPGA contains both FPGA for high performance computing and ARM processors for user and other interfaces)
To derive fast closed-form approximations for dermal and dental chromophore mapping
To generate computation mesh automatically from surface models

4. Objectives
To create a novel model for light travelling in complex matter (such as skin or tooth) based on Maxwell equations and discrete exterior calculus.
To apply all the above for skin and tooth phantoms (teeth removed for orthodontics) and clinical trials
To explore the utility of the spectral imaging system for the detection of ICG-labelled malignant cells by using e.g. ICG-labelled anti- melanoma antibodies (such as those in clinical use) in a xenograft model.

5. Hypothesis
The reduced size of the spectral imager improves usability (this includes both optics and computing hardware)
Integrated led-light source narrows FWHM’s and increases SNR
Multiple direction lightning enables photometric stereo, which will give surface models and albedo for complex surface
Polarization will reduce high-light reflections and
In spectral image, we can reduce spectral heterogeneousness of complex surfaces with image- guided filters
Close-form approximations are simpler to derive from albedo
Developed methods will improve skin cancer screening, delineation and detection, as well as treatment monitoring.
Caries can be imaged non-invasively
We can create an optical biopsy - skin and tooth surface topography and tomography based on measured spectra.

7. Workpackages WP1: Identification of requirements WP2: Devices
WP3: Computational modelling and machine learning
WP4: Validation
WP5: Dissemination

10. SKIN STRUCTURE

13. Skin optical model

14. Skin optical model