Dark-based Optical Sectioning assists Background Removal in Fluorescence Microscopy
Abstract A fundamental challenge in fluorescence microscopy is the defocused background caused by scattering light, optical aberration, or limited axial resolution. Severe defocus backgrounds will submerge the in-focus information and cause artifacts in the following processing. Here, we leverage a priori knowledge about dark channels of biological structures and dual frequency separation to develop a single-frame defocus removal algorithm. It stably improves the signal-to-background ratio and structural similarity index measure of images by approximately 10-fold, and recovers in-focus signal with 85% accuracy, even when the defocus background is 50 times larger than in-focus information. Our Dark-based optical sectioning approach (Dark sectioning) is fully compatible with various microscopy techniques, such as wide-filed microscopy, polarized microscopy, laser-scanning / spinning-disk confocal microscopy, stimulated emission depletion microscopy, lightsheet microscopy, and light-field microscopy. It also complements reconstruction or processing algorithms such as deconvolution, structure illumination microscopy, and super-resolution optical fluctuation imaging..
| Medienart: |
|
|---|
Preprint| Erscheinungsjahr: |
2024 |
|---|---|
| Erschienen: |
2024 |
| Enthalten in: |
bioRxiv.org - (2024) vom: 06. März Zur Gesamtaufnahme - year:2024 |
|---|
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Cao, Ruijie [VerfasserIn] |
|---|
| Links: |
Volltext [kostenfrei] |
|---|
| Themen: |
|---|
| doi: |
10.1101/2024.03.02.578598 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
XBI042693594 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | XBI042693594 | ||
| 003 | DE-627 | ||
| 005 | 20240306115004.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 240304s2024 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1101/2024.03.02.578598 |2 doi | |
| 035 | |a (DE-627)XBI042693594 | ||
| 035 | |a (biorXiv)10.1101/2024.03.02.578598 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Cao, Ruijie |e verfasserin |0 (orcid)0000-0002-2463-1136 |4 aut | |
| 245 | 1 | 0 | |a Dark-based Optical Sectioning assists Background Removal in Fluorescence Microscopy |
| 264 | 1 | |c 2024 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a Computermedien |b c |2 rdamedia | ||
| 338 | |a Online-Ressource |b cr |2 rdacarrier | ||
| 520 | |a Abstract A fundamental challenge in fluorescence microscopy is the defocused background caused by scattering light, optical aberration, or limited axial resolution. Severe defocus backgrounds will submerge the in-focus information and cause artifacts in the following processing. Here, we leverage a priori knowledge about dark channels of biological structures and dual frequency separation to develop a single-frame defocus removal algorithm. It stably improves the signal-to-background ratio and structural similarity index measure of images by approximately 10-fold, and recovers in-focus signal with 85% accuracy, even when the defocus background is 50 times larger than in-focus information. Our Dark-based optical sectioning approach (Dark sectioning) is fully compatible with various microscopy techniques, such as wide-filed microscopy, polarized microscopy, laser-scanning / spinning-disk confocal microscopy, stimulated emission depletion microscopy, lightsheet microscopy, and light-field microscopy. It also complements reconstruction or processing algorithms such as deconvolution, structure illumination microscopy, and super-resolution optical fluctuation imaging. | ||
| 650 | 4 | |a Biology |7 (dpeaa)DE-84 | |
| 650 | 4 | |a 570 |7 (dpeaa)DE-84 | |
| 700 | 1 | |a Li, Yaning |4 aut | |
| 700 | 1 | |a Wang, Wenyi |4 aut | |
| 700 | 1 | |a Zhang, Guoxun |4 aut | |
| 700 | 1 | |a Wang, Gang |0 (orcid)0009-0002-9979-093X |4 aut | |
| 700 | 1 | |a Sun, Yu |0 (orcid)0009-0009-0484-5637 |4 aut | |
| 700 | 1 | |a Ren, Wei |0 (orcid)0000-0002-5014-8113 |4 aut | |
| 700 | 1 | |a Sun, Jing |4 aut | |
| 700 | 1 | |a Hou, Yiwei |0 (orcid)0000-0002-5764-2384 |4 aut | |
| 700 | 1 | |a Xu, Xinzhu |0 (orcid)0000-0003-2302-2053 |4 aut | |
| 700 | 1 | |a Hu, Jiakui |4 aut | |
| 700 | 1 | |a Lu, Yanye |0 (orcid)0000-0002-3063-8051 |4 aut | |
| 700 | 1 | |a Li, Changhui |0 (orcid)0000-0002-6179-2684 |4 aut | |
| 700 | 1 | |a Wu, Jiamin |0 (orcid)0000-0003-3479-1026 |4 aut | |
| 700 | 1 | |a Li, Meiqi |0 (orcid)0000-0003-3586-176X |4 aut | |
| 700 | 1 | |a Qu, Junle |0 (orcid)0000-0001-7833-4711 |4 aut | |
| 700 | 1 | |a Xi, Peng |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t bioRxiv.org |g (2024) vom: 06. März |
| 773 | 1 | 8 | |g year:2024 |g day:06 |g month:03 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.1101/2024.03.02.578598 |z kostenfrei |3 Volltext |
| 912 | |a GBV_XBI | ||
| 951 | |a AR | ||
| 952 | |j 2024 |b 06 |c 03 | ||