deletions | additions       diff --git a/res_region.md b/res_region.md  index 8ce78cf..d51c25c 100644  --- a/res_region.md  +++ b/res_region.md 
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### Region detection  Before it is possible to fit the fluorescence signal from in  each pixel with a transient function, candidate regions containing possible events must be detected. For this we have modified a continous wavelet transform based peak detection algorithm by Du et al.\cite{Du_2006}. Whereas the the original algorithm of Du et al. provides the location of the peak, we have extended it to also yield the the width of the peak. The original algorith works by joining the calculating a  wavelet transform values along local maxima of the signal  for increasing window lengths (Figure \ref{fig:regs} B). Ridge lines obtained in this manner are taken to along local maxima on the surface  correspond to peaks if they satisfy certain criteria (length of the ridge, SNR, etc.) etc., see Du et al.\cite{Du_2006} for details)  In our extension, the width of the peak is obtained from finding the first maximum of the wavelet transform values along the ridge line (Figure \ref{fig:regs}C). The width of the region is taken as \(peak_{center} - 1.5\times width, peak_{center}+2\times width\)  Region estimation is provides a ranked list of potential event regions. The rank of a region indicates how many regions having a lower peak SNR overlap with it. For example, region 1 and 3 on Figure \ref{fig:regs}D have rank 3, because neither overlap with a region having a lower peak SNR. Region 2 has a rank of 2 as it overlaps with region 3 which has a lower peak SNR. Ranking is necessary to ensure overlapping signals are correctly fitted in the fitting stage.