000			02091 am a22002653u 4500
042			_adc
100	1	0	_aMahecic, Dora _eauthor _91419
700	1	0	_aStepp, Willi L. _eauthor _91420
700	1	0	_aZhang, Chen _eauthor _91421
700	1	0	_aGriffié, Juliette _eauthor _91422
700	1	0	_aWeigert, Martin _eauthor _91423
700	1	0	_aManley, Suliana _eauthor _91424
245	0	0	_aEvent-driven acquisition for content-enriched microscopy
260			_c2022-09-08.
500			_a/pmc/articles/PMC7613693/
500			_a/pubmed/36076039
520			_aA common goal of fluorescence microscopy is to collect data on specific biological events. Yet, the event-specific content that can be collected from a sample is limited, especially for rare or stochastic processes. This is due in part to photobleaching and phototoxicity, which constrain imaging speed and duration. We developed an event-driven acquisition (EDA) framework, in which neural network-based recognition of specific biological events triggers real-time control in an instant structured illumination microscope (iSIM). Our setup adapts acquisitions on-the-fly by switching between a slow imaging rate while detecting the onset of events, and a fast imaging rate during their progression. Thus, we capture mitochondrial and bacterial divisions at imaging rates that match their dynamic timescales, while extending overall imaging durations. Because EDA allows the microscope to respond specifically to complex biological events, it acquires data enriched in relevant content.
540			_a
540			_ahttps://www.springernature.com/gp/open-research/policies/accepted-manuscript-termsUsers may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms
546			_aen
690			_aArticle
655	7		_aText _2local
786	0		_nNat Methods
856	4	1	_uhttp://dx.doi.org/10.1038/s41592-022-01589-x _zConnect to this object online.
999			_c1935 _d1935