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HcmV?d00001 From 57974ab68807d87477d15068e050ae185a422d98 Mon Sep 17 00:00:00 2001 From: The Open Journals editorial robot <89919391+editorialbot@users.noreply.github.com> Date: Sun, 24 Nov 2024 20:49:34 +0000 Subject: [PATCH 2/7] Creating 10.21105.joss.07125.crossref.xml --- joss.07125/10.21105.joss.07125.crossref.xml | 362 ++++++++++++++++++++ 1 file changed, 362 insertions(+) create mode 100644 joss.07125/10.21105.joss.07125.crossref.xml diff --git a/joss.07125/10.21105.joss.07125.crossref.xml b/joss.07125/10.21105.joss.07125.crossref.xml new file mode 100644 index 0000000000..bbe081258c --- /dev/null +++ b/joss.07125/10.21105.joss.07125.crossref.xml @@ -0,0 +1,362 @@ + + + + 20241124204847-050ec0b8e3636e42bef6920ff0c1039b76b4ecf0 + 20241124204847 + + JOSS Admin + admin@theoj.org + + The Open Journal + + + + + Journal of Open Source Software + JOSS + 2475-9066 + + 10.21105/joss + https://joss.theoj.org + + + + + 11 + 2024 + + + 9 + + 103 + + + + BrightEyes-MCS: a control software for multichannel +scanning microscopy + + + + Mattia + Donato + + Molecular Microscopy and Spectroscopy, Istituto Italiano di Tecnologia, Genoa, 16152, Italy + + https://orcid.org/0000-0003-0026-747X + + + Eli + Slenders + + Molecular Microscopy and Spectroscopy, Istituto Italiano di Tecnologia, Genoa, 16152, Italy + + https://orcid.org/0000-0002-6757-1372 + + + Alessandro + Zunino + + Molecular Microscopy and Spectroscopy, Istituto Italiano di Tecnologia, Genoa, 16152, Italy + + https://orcid.org/0000-0002-2512-8751 + + + Luca + Bega + + Molecular Microscopy and Spectroscopy, Istituto Italiano di Tecnologia, Genoa, 16152, Italy + + + + Giuseppe + Vicidomini + + Molecular Microscopy and Spectroscopy, Istituto Italiano di Tecnologia, Genoa, 16152, Italy + + https://orcid.org/0000-0002-3085-730X + + + + 11 + 24 + 2024 + + + 7125 + + + 10.21105/joss.07125 + + + http://creativecommons.org/licenses/by/4.0/ + http://creativecommons.org/licenses/by/4.0/ + http://creativecommons.org/licenses/by/4.0/ + + + + Software archive + 10.5281/zenodo.14012812 + + + GitHub review issue + https://github.com/openjournals/joss-reviews/issues/7125 + + + + 10.21105/joss.07125 + https://joss.theoj.org/papers/10.21105/joss.07125 + + + https://joss.theoj.org/papers/10.21105/joss.07125.pdf + + + + + + A robust and versatile platform for image +scanning microscopy enabling super-resolution FLIM + Castello + Nature Methods + 16 + 10.1038/s41592-018-0291-9 + 2019 + Castello, M., Tortarolo, G., +Buttafava, M., Deguchi, T., Villa, F., Koho, S., Pesce, L., Oneto, M., +Pelicci, S., Lanzanó, L., Bianchini, P., Sheppard, C. J. R., Diaspro, +A., Tosi, A., & Vicidomini, G. (2019). A robust and versatile +platform for image scanning microscopy enabling super-resolution FLIM. +Nature Methods, 16, 175–178. +https://doi.org/10.1038/s41592-018-0291-9 + + + Focus image scanning microscopy for sharp and +gentle super-resolved microscopy + Tortarolo + Nature Communications + 13 + 10.1038/s41467-022-35333-y + 2022 + Tortarolo, G., Zunino, A., Fersini, +F., Castello, M., Piazza, S., Sheppard, C. J. R., Bianchini, P., +Diaspro, A., Koho, S., & Vicidomini, G. (2022). Focus image scanning +microscopy for sharp and gentle super-resolved microscopy. Nature +Communications, 13. +https://doi.org/10.1038/s41467-022-35333-y + + + Single-photon microscopy to study +biomolecular condensates + Perego + Nature Communications + 14 + 10.1038/s41467-023-43969-7 + 2023 + Perego, E., Zappone, S., Castagnetti, +F., Mariani, D., Vitiello, E., Rupert, J., Zacco, E., Tartaglia, G. G., +Bozzoni, I., Slenders, E., & Vicidomini, G. (2023). Single-photon +microscopy to study biomolecular condensates. Nature Communications, 14, +8224. https://doi.org/10.1038/s41467-023-43969-7 + + + Super-resolution in confocal +imaging + Sheppard + Optik + 80 + 1988 + Sheppard, C. (1988). Super-resolution +in confocal imaging. Optik, 80, 53–54. + + + Image scanning microscopy + Müller + Physical Review Letters + 104 + 10.1103/PhysRevLett.104.198101 + 2010 + Müller, C. B., & Enderlein, J. +(2010). Image scanning microscopy. Physical Review Letters, 104. +https://doi.org/10.1103/PhysRevLett.104.198101 + + + Reconstructing the image scanning microscopy +dataset: An inverse problem + Zunino + Journal of Optics + 39 + 10.1088/1361-6420/accdc5 + 2022 + Zunino, A., Castello, M., & +Vicidomini, G. (2022). Reconstructing the image scanning microscopy +dataset: An inverse problem. Journal of Optics, 39, 064004. +https://doi.org/10.1088/1361-6420/accdc5 + + + Open-source tools enable accessible and +advanced image scanning microscopy data analysis + Zunino + Nature Photonics + 17 + 10.1038/s41566-023-01216-x + 2023 + Zunino, A., Slenders, E., Fersini, +F., Bucci, A., Donato, M., & Vicidomini, G. (2023). Open-source +tools enable accessible and advanced image scanning microscopy data +analysis. Nature Photonics, 17, 457–458. +https://doi.org/10.1038/s41566-023-01216-x + + + Structured detection for simultaneous +super-resolution and optical sectioning in laser scanning +microscopy + Zunino + 10.48550/arXiv.2406.12542 + 2024 + Zunino, A., Garrè, G., Perego, E., +Zappone, S., Donato, M., & Vicidomini, G. (2024). Structured +detection for simultaneous super-resolution and optical sectioning in +laser scanning microscopy. +https://doi.org/10.48550/arXiv.2406.12542 + + + SPAD-based asynchronous-readout array +detectors for image-scanning microscopy + Buttafava + Optica + 7 + 10.1364/optica.391726 + 2020 + Buttafava, M., Villa, F., Castello, +M., Tortarolo, G., Conca, E., Sanzaro, M., Piazza, S., Bianchini, P., +Diaspro, A., Zappa, F., Vicidomini, G., & Tosi, A. (2020). +SPAD-based asynchronous-readout array detectors for image-scanning +microscopy. Optica, 7, 755. +https://doi.org/10.1364/optica.391726 + + + Cooled SPAD array detector for low light-dose +fluorescence laser scanning microscopy + Slenders + Biophysical Reports + 1 + 10.1016/j.bpr.2021.100025 + 2021 + Slenders, E., Perego, E., Buttafava, +M., Tortarolo, G., Conca, E., Zappone, S., Pierzynska-Mach, A., Villa, +F., Petrini, E. M., Barberis, A., Tosi, A., & Vicidomini, G. (2021). +Cooled SPAD array detector for low light-dose fluorescence laser +scanning microscopy. Biophysical Reports, 1, 100025. +https://doi.org/10.1016/j.bpr.2021.100025 + + + Compact and effective photon-resolved image +scanning microscope + Tortarolo + Advanced Photonics + 6 + 10.1117/1.ap.6.1.016003 + 2024 + Tortarolo, G., Zunino, A., Piazza, +S., Donato, M., Zappone, S., Pierzyńska-Mach, A., Castello, M., & +Vicidomini, G. (2024). Compact and effective photon-resolved image +scanning microscope. Advanced Photonics, 6. +https://doi.org/10.1117/1.ap.6.1.016003 + + + The BrightEyes-TTM as an open-source +time-tagging module for democratising single-photon +microscopy + Rossetta + Nature Communications + 13 + 10.1038/s41467-022-35064-0 + 2022 + Rossetta, A., Slenders, E., Donato, +M., Zappone, S., Fersini, F., Bruno, M., Diotalevi, F., Lanzanò, L., +Koho, S., Tortarolo, G., Barberis, A., Crepaldi, M., Perego, E., & +Vicidomini, G. (2022). The BrightEyes-TTM as an open-source time-tagging +module for democratising single-photon microscopy. Nature +Communications, 13, 7406. +https://doi.org/10.1038/s41467-022-35064-0 + + + ImSwitch: Generalizing microscope control in +python + Moreno + Journal of Open Source +Software + 6 + 10.21105/joss.03394 + 2021 + Moreno, X., Al-Kadhimi, S., Alvelid, +J., Bodén, A., & Testa, I. (2021). ImSwitch: Generalizing microscope +control in python. Journal of Open Source Software, 6, 3394. +https://doi.org/10.21105/joss.03394 + + + Computer control of microscopes using +µManager + Edelstein + Current Protocols in Molecular +Biology + 92 + 10.1002/0471142727.mb1420s92 + 2010 + Edelstein, A., Amodaj, N., Hoover, +K., Vale, R., & Stuurman, N. (2010). Computer control of microscopes +using µManager. Current Protocols in Molecular Biology, 92. +https://doi.org/10.1002/0471142727.mb1420s92 + + + Confocal-based fluorescence fluctuation +spectroscopy with a SPAD array detector + Slenders + Light: Science & +Applications + 10 + 10.1038/s41377-021-00475-z + 2021 + Slenders, E., Castello, M., +Buttafava, M., Villa, F., Tosi, A., Lanzanò, L., Koho, S. V., & +Vicidomini, G. (2021). Confocal-based fluorescence fluctuation +spectroscopy with a SPAD array detector. Light: Science & +Applications, 10. +https://doi.org/10.1038/s41377-021-00475-z + + + ISM-FLUX: MINFLUX with an array +detector + Slenders + Physical Review Research + 5 + 10.1103/PhysRevResearch.5.023033 + 2023 + Slenders, E., & Vicidomini, G. +(2023). ISM-FLUX: MINFLUX with an array detector. Physical Review +Research, 5, 023033. +https://doi.org/10.1103/PhysRevResearch.5.023033 + + + Arkitekt : An open-source framework for +modern bioimage workflows + Roos + 2023 + Roos, J. (2023). Arkitekt : An +open-source framework for modern bioimage workflows [PhD thesis, +Université de Bordeaux]. +https://theses.hal.science/tel-04341599 + + + + + + From 0eff4542508aab14bc3da5cdc843b8bc6841dd2d Mon Sep 17 00:00:00 2001 From: The Open Journals editorial robot <89919391+editorialbot@users.noreply.github.com> Date: Sun, 24 Nov 2024 20:49:35 +0000 Subject: [PATCH 3/7] Adding JATS media file: figure1.svg --- joss.07125/paper.jats/figure1.svg | 208 ++++++++++++++++++++++++++++++ 1 file changed, 208 insertions(+) create mode 100644 joss.07125/paper.jats/figure1.svg diff --git a/joss.07125/paper.jats/figure1.svg b/joss.07125/paper.jats/figure1.svg new file mode 100644 index 0000000000..7687f4ea94 --- /dev/null +++ b/joss.07125/paper.jats/figure1.svg @@ -0,0 +1,208 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 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+ + + + +Journal of Open Source Software +JOSS + +2475-9066 + +Open Journals + + + +7125 +10.21105/joss.07125 + +BrightEyes-MCS: a control software for multichannel +scanning microscopy + + + +https://orcid.org/0000-0003-0026-747X + +Donato +Mattia + +mattia.donato@iit.it + +* + + +https://orcid.org/0000-0002-6757-1372 + +Slenders +Eli + + + + +https://orcid.org/0000-0002-2512-8751 + +Zunino +Alessandro + + + + + +Bega +Luca + + + + +https://orcid.org/0000-0002-3085-730X + +Vicidomini +Giuseppe + + + + + +Molecular Microscopy and Spectroscopy, Istituto Italiano di +Tecnologia, Genoa, 16152, Italy + + + + +* E-mail: mattia.donato@iit.it + + +30 +10 +2024 + +9 +103 +7125 + +Authors of papers retain copyright and release the +work under a Creative Commons Attribution 4.0 International License (CC +BY 4.0) +2024 +The article authors + +Authors of papers retain copyright and release the work under +a Creative Commons Attribution 4.0 International License (CC BY +4.0) + + + +Python +imaging +microscopy +flim +image scanning microscopy + + + + + + Introduction +

Fluorescence microscopy is an essential workhorse of biomedical + sciences, thanks to its capability to provide specific and + quantitative information on the observed specimens. The advent of + super-resolution techniques has further improved the quality of the + images produced by optical microscopes. Among the numerous + super-resolution techniques, image scanning microscopy (ISM) emerged + as a robust and reliable technique, being able to provide gentle + imaging at a high signal-to-noise ratio (SNR) with excellent optical + sectioning + (Castello + et al., 2019; + Perego + et al., 2023; + Tortarolo + et al., 2022)​. An ISM microscope shares the same architecture + as a confocal laser scanning microscope (CLSM) but exploits a pixeled + detector. Each detector element acts as a displaced small pinhole and + generates a confocal-like image after a full scan of the field of + view. As the detector is made by a matrix of pixels, the raw ISM + dataset is not a 2D image, it is a 4D dataset, which can be seen in + two ways: each single pixel scanned on the sample plane is associated + with a micro-image of the detector; vice-versa, for each physical + pixel on the detector plane is associated a full-scanned field of view + on the sample plane + (Müller + & Enderlein, 2010; + Sheppard, + 1988)​. Using tailored reconstruction algorithms, the images of + the raw ISM dataset can be fused to produce a single super-resolution + image using all the photons collected by the detector, guaranteeing an + excellent SNR​ + (Zunino + et al., 2022, + 2023, + 2024)​.

+

The capabilities of ISM can be further extended if coupled with a + fast detector, such as an array of single photon avalanche diodes + (SPAD)​  + (Buttafava + et al., 2020; + Slenders, + Perego, et al., 2021)​. This type of detector features the + readout of each pixel is independent and async, preserving the + temporal information of each photon arrival. In other words, it is + possible to tag each photon with its arrival time with respect to the + excitation laser, expanding the dataset to a 5D array. This data can + be used for estimating the fluorescence lifetime allowing the + fluorescent lifetime imaging scanning microscopy (FLISM), a microscopy + technique that merges the temporal information with the ISM advantages + mentioned above + (Rossetta + et al., 2022; + Tortarolo + et al., 2024)​.

+ + Statement of need +

In live-cell microscopy, the demand for high-resolution imaging + coexists with the necessity to protect sample integrity. Fast pixel + dwell times are instrumental in this pursuit, minimizing sample + damage while enhancing image quality. Leveraging the capabilities of + the SPAD array detector, which can achieve megahertz photon flux per + single pixel, requires an advanced data acquisition and control + system based on FPGA technology. Existing open-source microscope + control software, such as + ImSwitch​ (Moreno + et al., 2021)​ and + µManager​ (Edelstein + et al., 2010)​, while general-purpose, flexible, and + scriptable, are primarily designed for camera-based systems. They + are not optimized to handle the precise synchronization and + high-performance demands of ISM instruments, especially for + configuration with pixel dwell times as low as 1 µs and photon flux + rates in the megahertz range.

+

In contrast, BrightEyes-MCS (Microscope Control Suite) is an + open-source software specifically designed for controlling + laser-scanning microscopes equipped with SPAD detectors. It + overcomes the limitations of other software by providing real-time + synchronization, high-throughput data acquisition, and seamless + compatibility with the high-speed scanning demands of ISM + systems.

+

BrightEyes-MCS not only features a user-friendly graphical + interface (GUI) for microscope control, but also supports real-time + previews and efficient data saving in the HDF5 format, which is + ready for internal processing or integration with external analysis + tools. Although tailored for ISM, BrightEyes-MCS is versatile and + can be adapted for various applications, including fluorescence + correlation spectroscopy (FCS), spectroscopy, and other advanced + imaging techniques. This flexibility makes it a valuable resource + for researchers working with diverse microscopy setups that require + precise control and high-performance data acquisition.

+

BrightEyes is the name of the project founded by the ERC in 2018 + (Consolidator Grant, N. 818699). In this context, other open-source + tools have been developed, like BrighEyes-TTM, an open-hardware + time-tagging module + (Rossetta + et al., 2022), BrightEyes-ISM + (Zunino + et al., 2023), a python library for ISM data analysis.

+
+
+ + System Architecture + +

Scheme of BrightEyes-MCS architecture. +

+ +
+

The BrightEyes-MCS controls and handles the data stream with the + underlying hardware, based on a field-programmable gate array (FPGA) + from National Instrument (NI). These boards provide the digital + inputs/outputs (I/O), and some models also provide analog I/Os. + [fig:fig1] shows a + sketch of the system architecture.

+

The system architecture features two parts: i) the low-level + firmware (BrightEyes-MCSLL) managing the hardware and the electronics, + running on the FPGA; ii) the high-level software (BrightEyes-MCS) + which includes the GUI and its libraries running on the PC.

+

The firmware was developed specifically for image scanning + microscopy, on NI LabView for FPGA. It is a separate project, free, + downloadable but it is not open source. The firmware can be controlled + by the high-level software through registers and the data are streamed + through dedicated FIFOs. Details are out of the scope of this paper + and together with its documentation are available in the + BrightEyes-MCSLL + repository.

+

Each time an acquisition starts, BrightEyes-MCS automatically loads + the firmware into the FPGA, sets the registers (for example for + configuring the number of pixels, and dwell-time), and waiting for the + data arriving through FIFO.

+

BrightEyes-MCS supports up to 25 digital channels (plus 2 extra + channels) and up-to 2 analog inputs. It controls the scanning and the + positioning with a maximum speed of 1 us for pixel dwell time and it + is possible to set a further time-subdivision of the same pixel down + to 0.5us per bin.

+

There is also the possibility of activating the so-called Digital + Frequency Domain (DFD) mode + (Tortarolo + et al., 2024)​. It is a heterodyne technique that allow to + obtain higher time resolution. In this mode, the laser pulsing is + driven by the FPGA, and for each detector element it is acquired the + histogram of the time-arrival of the photons with respect to the laser + pulse (known as Time-Correlated Single Photon Counting, TCSPC), with a + bin precision of 0.3 ns.

+

The software has been tested in a machine equipped with an Intel + Xeon CPU (2.2GHz) with 12 cores, and 32GByte of RAM. This system was + able to acquire datasets up to 2000x2000x25x81 (x, y, ch,t).

+
+ + Specifications +

The specifications of BrightEyes-MCS depend on the hardware + features of the NI FPGA used. To actuate the scanners, analog outputs + are needed. Since not all FPGA models provide them, they can be + replaced with an external independent board.

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Channels25
Extra Channels2
Analog Inputs Channels2 (selected out of 8), or not supported with + external DAC
Analog Output Channels8, or 4 with external DAC
Pixel Dwell Time1.0 µs
Minimum time binnormal mode0.5 µs
DFD mode0.2 ns
Data storageHDF5, data and metadata
Data array dimensionrepetition, z, y, x, time-bin, + detector-channel
Boards tested25 ch. + +

NI USB-7856R

+
+
+ +

NI USB-7856R OEM

+
+
+ +

NI PXIe-7856R

+
+
+ +

NI PXIe-7822R

+
+
(with external DAC*)
+ +

NI PCIe-7820R

+
+
(with external DAC*)
*As external DAC has been tested the + commercial evaluation board EVAL-AD5764 from Analog + Device.
+
+
+ + Hardware and Electronics + +

Scheme of the hardware of BrightEyes-MCS + system.

+ +
+

This sketch shows the main electronics components controlled by + BrightEyes-MCS.

+

The sample positioning and the scanning are controlled by the + analog outputs connected to positioner. They can be either linear + galvo mirrors or piezo stages. The analog outputs supported are 8 and + the user can select for each channel to be used as X, Y, Z, or a + constant voltage. The possibility of setting a constant voltage is + useful for other types of elements such as Acousto-optic modulators + (AOM).

+

The support of photomultiplier tubes (PMTs) is given by reading out + two analog inputs at the same time. The user can select the two analog + inputs out of 8 channels.

+

In the case of the NI FPGA board used lacking the analog I/O, the + analog outputs are provided by an external DAC connected to the + digital I/O of the FPGA. Similarly to it, we are planning to support + for external ADC for providing the analog inputs.

+

The BrightEyes-MCS can control up to 4 lasers through 4 digital + output lines. They can be switched on and off easily at the start and + end of a measurement. In the case of DFD mode – i.e. time-of-arrival / + lifetime measurement – the system provides the synchronization clock + to the lasers for triggering the pulses.

+
+ + Software Architecture + +

Scheme of the software + architecture

+ +
+

The Figure above shows the main parts of the BrightEyes-MCS Python + code. The main process runs the GUI (MainWindow). When an acquisition + is started the FPGAHandle instantiates the other three parallel + processes.

+

These processes are “infinite loops” (until the event + end-of-acquisition), implemented using the + multiprocessing + library. As they are independent Python instances, the communication + between needs “shared” objects such as mp.Dict, mp.Event and + MemorySharedArray (which uses mp.Array). Here below a short + description of what the three processes:

+ + +

The FpgaHandleProcess uploads and runs the firmware on the + FPGA, listen to commands from the Main, and executes them. These + commands are mainly related to read/write registers. This process + continuously reads data available on the FIFOs from the FPGA, + sending them to the DataPreProcess via a mp.Queue. The + communication with the data is given by the + nifpga + library. The FIFO readout can performed either with nifpga library + or with + nifpga-fast-fifo-recv, + a Python library written in Rust which we developed for reaching + higher readout performances.

+
+ +

The DataPreProcess is just waiting for data from the input + Queue and cumulate them up to a given value and sends them to the + AcquisitionLoopProcess with an mp.Queue.

+
+ +

The AcquisitionLoopProcess converts the raw data to a numpy + array. This is performed by FastConverter, a function developed in + Cython due to performance reasons. The converted data are reshaped + and stored into a buffer used for the live preview and for saving + the data to the HDF5 file + h5py + library.

+
+
+

The GUI is implemented with + PySide2 + library. The images and the other plots are drawn by + PyQtGraph + library. The GUI also provides an integrated Python console + (which uses the library + QtConsole + ) which exposes all running objects. This means that on the console, + the user can modify parts of the running software, in-live. This + allows to run scripts for automatized operation, moreover, it allows + to easily run scripts for example a quick data analysis at the end of + the measurement.

+ +

Screenshot of BrightEyes-MCS + GUI

+ +
+
+ + Conclusion +

The BrightEyes-MCS is a new open-source tool for controlling image + scanning microscopes. It provides a real-time preview and supports up + to 25 channels. It is designed for image-scanning microscopy with a + SPAD array but allows easily to be used on different scenarios. For + example, it can be used on a single-detector confocal microscope + equipped with a single-pixel SPAD or PMT. It can be used also outside + the context of scanning microscopy as for example it is possible to + use it in the context of Fluorescence correlation spectroscopy (FCS) + (Slenders, + Castello, et al., 2021)​. Furthermore, the software can support + single-molecule localization microscopy (SMLM) with non-conventional + scanning patterns, such as MINFLUX and ISMFLUX + (Slenders + & Vicidomini, 2023)​. Data acquired by BrightEyes-MCS are + stored in HDF5 format, which can be easily opened with popular data + analysis frameworks like Python notebooks or MATLAB. Additionally, a + Python library called BrightEyes-ISM + (Zunino + et al., 2023) has been developed, enabling users to open these + files and apply enhancement techniques such as APR + (Castello + et al., 2019) and Focus-ISM + (Tortarolo + et al., 2022)​​. For those using + Napari, + a plugin named + Napari-ISM + is available, allowing the same enhancements to be performed within + its graphical user interface.

+

As Python open-source tool can be easily adapted to other systems. + For example, BrightEyes-MCS has been integrated with BrightEyes-TTM, + an open-source time-tagging module that allows to time-tag single + photons with a resolution of about + 30ps​ (Rossetta + et al., 2022)​. It can be controlled by BrightEyes-MCS: every + time an acquisition is starting the TTM remotely starts acquiring data + in another machine. Moreover, BrightEyes-MCS can be controlled by + external tools via HTTP REST APIs, which allow access to the GUI + parameters, main commands (such as start acquisition, preview, and + stop), and the preview image. This facilitates integration into a + larger control framework, such as ImSwitch + (Moreno + et al., 2021)​ or Arkitekt + (Roos, + 2023).

+

In conclusion, BrightEyes-MCS presents a promising open-source + solution for controlling image-scanning microscopes. It features + real-time preview and multi-channel support, and offers great + versatility for various microscopy setups. We envision that our + open-source and free tool will be widely adopted by the scientific + community, contributing to the dissemination of open science culture + in microscopy.

+
+ + Disclosures & Acknowledgements +

G.V. has a personal financial interest (co-founder) in Genoa + Instruments, Italy. The remaining authors declare no competing + interests. We acknowledge our former colleagues, Marco Castello and + Simonluca Piazza, now founder and respectively CTO and CEO of Genoa + Instruments, for their important contributions to the firmware in the + early stages of the project. BrightEyes-MCS is designed to be an + open-source software for research purposes and does not reflect the + performance of the commercial products offered by Genoa + Instruments.

+

The repository of BrightEyes-MCS is + https://github.com/VicidominiLab/BrightEyes-MCS.

+
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