B. Murienne - Master Project Thesis - Infoscience - EPFL

the sum of the products. Spatial filtering of an image is the process of modifying each pixel value
based upon its neighboring pixel values. This filtering has to be done for all images of one run.
Temporal filtering using either centered median filters, low-pass Kaiser window filter or
mean-value filter is then performed [41]. A median filter is generally used to reduce noise and
usually does better job than a mean filter in preserving action potential morphology. Temporal
filtering of a stack of images is the process of modifying the sequence of images based upon its
temporal sequence of values. It involves looking at one pixel at a time over the time course of the
run and has to be done for all pixels.
in Figure 9.
The signal resulting from the phased-shift spatial filtering and temporal filtering is shown
2.6.3 Feature extraction
Figure 9. Final filtered signal [41].
• Maps of activation, repolarization and APD
Maps of activation, repolarization and APD time can be created from the optical signals
obtained, as represented in Figure 10 (a,b,c). In 2001, maps of activation, repolarization and ADP
were generated by Sung et al., with and without phase-shifting as well as with different kernel
sizes, and compared. The best signal was obtained using the 7×7 kernel filter but the signal
quality was only slightly better than with the 5×5 kernel and the computational cost was greater
[41].
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