Additional file 4 of ReCSAI: recursive compressed sensing artificial intelligence for confocal lifetime localization microscopy
Additional file 4. Fig. S4. Wavelet filter bank peak detection on an example frame of a FLIMbee measurement. The input image a is deconstructed with a wavelet filter bank, trained to extract frequencies resembling a PSF. A threshold is applied before reconstructing to generate a denoised image b. Po...
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creator | Reinhard, Sebastian Helmerich, Dominic A. Boras, Dominik Sauer, Markus Kollmannsberger, Philip |
description | Additional file 4. Fig. S4. Wavelet filter bank peak detection on an example frame of a FLIMbee measurement. The input image a is deconstructed with a wavelet filter bank, trained to extract frequencies resembling a PSF. A threshold is applied before reconstructing to generate a denoised image b. Potential emitters are identified with a local maximum detection. The detected peaks are marked with red rectangles. |
doi_str_mv | 10.6084/m9.figshare.22605511 |
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Fig. S4. Wavelet filter bank peak detection on an example frame of a FLIMbee measurement. The input image a is deconstructed with a wavelet filter bank, trained to extract frequencies resembling a PSF. A threshold is applied before reconstructing to generate a denoised image b. Potential emitters are identified with a local maximum detection. 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Fig. S4. Wavelet filter bank peak detection on an example frame of a FLIMbee measurement. The input image a is deconstructed with a wavelet filter bank, trained to extract frequencies resembling a PSF. A threshold is applied before reconstructing to generate a denoised image b. Potential emitters are identified with a local maximum detection. 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Fig. S4. Wavelet filter bank peak detection on an example frame of a FLIMbee measurement. The input image a is deconstructed with a wavelet filter bank, trained to extract frequencies resembling a PSF. A threshold is applied before reconstructing to generate a denoised image b. Potential emitters are identified with a local maximum detection. The detected peaks are marked with red rectangles.</abstract><pub>figshare</pub><doi>10.6084/m9.figshare.22605511</doi><oa>free_for_read</oa></addata></record> |
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title | Additional file 4 of ReCSAI: recursive compressed sensing artificial intelligence for confocal lifetime localization microscopy |
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