THE D. ATA PROCESSING PIPELINE. Process one frame,. Repeatâ¦, Average. Video cube. Video frame. (image) time. Super-resolution image. Image patching.
y
x
t
THE DATA PROCESSING PIPELINE
SPIDER SParse deconvolution of hIgh-Density supER-resolution images SParse deconvolution Siewert Hugelier, Johan J. de Rooi, Romain Bernex, Sam Duwé, Olivier Devos, Michel Sliwa,supER-resolution Peter Dedecker, Paul H. C. Eilers & Cyril Ruckebusch of hIgh-Density Video cube time Scientific Reports | 6:21413 |2016 Siewert Hugelier, Johan J. de Rooi, Romain Bernex, Sam Duwé, Olivier Devos, Michel Sliwa, Peter Dedecker, Paul H. C. Eilers & Cyril Ruckebusch
Scientific Reports | 6:21413 |2016
Super-resolution image
Process one frame, Data cube Repeat…, Average
Video frame Image Background correction (image)
Super-resolution 1 pixel
2x2
4x4
Image patching 1 image
n
s Dividing pixels into sub-pixels to improve Over-sampled grid localization accuracy
Averaging the positions and intensities of individual fluorophores over successive time Video cube frames Sparse deconvolution
Process one frame, Repeat…, Average
. . .. . .
Super-resolution image
PREPROCESSING SPATIAL MODE Correct for the spatial structure due to cellular auto-fluoresence (endogenous fluorophores) Raw frames
Background
Corrected frames
7000 Original signal background SPIDER signal
6000 5000 4000 3000 2000 1000 0 -1000
0
100
200
300
400
500
600
Assymetric least-squares with 2D tensors of P-splines P: Asymmetric weights p if yi≥i 1-p if yi