Virtual Pub Special Edition on “Open Hardware” – September 22, 2023

Virtual Pub Special Edition on “Open Hardware” – September 22, 2023

Imaging technologies are becoming increasingly complex and ever more expensive, reducing the general accessibility and potential reach of cutting-edge techniques. Many scientists and companies are committed to making imaging hardware and software solutions openly available to a wide audience.

The Special Edition Virtual Pub “Open Hardware in Imaging” in collaboration with the Euro-BioImaging Industry Board will highlight these developments, by featuring presentations of a number of open hardware projects in biological and biomedical imaging.

From open and modular hardware framework for light microscopy to adapting legacy commercial microscope frames to new modalities in order to obtain super-resolution performance, there is something for everyone at this Virtual Pub, so don’t miss out!

Download agenda here.

 

Time Title Presenter
13:00-13:10 Opening  
13:10-13:25 Open-source to democratize the access to human MRI systems Ruben Pellicer-Guridi,
Asociación de Investigación MPC, Donostia–San Sebastián
13:25-13:40 The Benchtop mesoSPIM: a compact and versatile open-source light-sheet microscope for imaging cleared tissues Nikita Vladimirov,
University of Zurich
13:40-13:55 miEye: bench-top cost-effective open-source single-molecule localization microscopy hardware and software platform Marijonas Tutkus,
Vilniaus University
14:00-14:15 Harnessing Differentiable Data Models for Machine Learning Integration in Microscopy Luis Oala, Dotphoton
14:15-14:30 An open source structured illumination microscopy extension for general fluorescence microscope body Haoran Wang, Leibniz-Institute of Photonic Technology
14:30-14:45 General-purpose microscope control via Python: ImSwitch Jacopo Abramo, Leibniz-Institute of Photonic Technology
14:45-15:00 The BrightEyes-TTM: an open-source time-tagging module for fluorescence laser scanning microscopy Mattia Donato, Istituto Italiano di Tecnologia

all times are CEST

Watch Luis Oala’s talk

Open-source to democratize the access to human MRI systems

Ruben Pellicer-Guridi1, Joāo S Periquito2, Tom O’Reilly3, Lukas Winter4

1Asociación de Investigación MPC, Donostia–San Sebastián, Spain; 2The University of Sheffield, Sheffield, England; 3Leiden University Medical Center (LUMC), Leiden, Netherlands; 4Physikalisch-Technische Bundesanstalt (PTB), Berlin, Germany

Nuclear Magnetic Resonance Imaging, more commonly known as MRI, is among the most sophisticated medical diagnostic instrument available . It offers a powerful diagnosis capability in a wide range of pathologies, yet its use is restrained due to its high costs. Until recently, the high technical complexity and resource demands have limited the development of these systems to only a few companies worldwide. This setting has arguably hindered innovation, restricting third party institutes to focus primarily on niche elements of the systems such as pulse sequences and sensors. However, the past decade has experienced a paradigm shift, with the emergence of numerous research groups capable of developing complete systems. Most of these novel systems fall in the low-field category, which refers to employing weaker magnetic fields. While low-field systems offer advantages in terms of costs and safety, they require extra attention to optimize image quality, which is inherently limited through lower signal-to-noise ratios.
Open-source is having a central role on this renaissance of innovative MRI systems. Openly sharing knowledge and know how, and following a modular approach has brought down the threshold to build complete MRI scanners that previously required a sizable pool of time, material and human resources. From software to hardware, there are being abundant open-source efforts shared around MRI. The Open Source Imaging Initiative (OSI²) has played a crucial role in promoting these efforts since 2016, utilizing various channels within the community. Among others, OSI² visualizes these works neatly classified on a website, has initiated sessions around open-source in the most popular MRI international conferences, and routinely organizes gatherings and hackatons. The mission and vision of OSI² goes beyond being a promoter of open-source practices, and has also become a vibrant community of developers working together, with the ultimate goal of benefiting patients. As part of this endeavour, OSI² is creating a blueprint for fully disclosed human low-field MRI systems, encompassing all the necessary components to facilitate their replication and utilization. The open-source concept extends beyond technical advancements and knowledge, as it permeates global markets through transparent documentation and comprehension of the systems, including their construction and use.

The Benchtop mesoSPIM: a compact and versatile open-source light-sheet microscope for imaging cleared tissues

Nikita Vladimirov

University of Zurich

mesoSPIM is an open-source light-sheet microscopy project for imaging cleared tissues  (http://mesospim.org/). Our goal is to develop and share knowledge on how to build and use your own facility-grade light-sheet microscope – compatible with all tissue clearing techniques, at affordable cost, with open-source hardware and software, thus making light-sheet imaging more accessible for biological and medical research.
Currently, there are over 20 mesoSPIM systems in operation around the world, with 8 of them at microscopy core facilities, used for a variety of cleared samples in neuroscience and developmental biology. We demonstrate a new-generation “Benchtop” mesoSPIM design, which offers multiple improvements over the original mesoSPIM: resolution of up to 1.5 µm laterally and 3.5 µm axially, magnification range 0.9-20x, a 1.5x larger field of view, 4x smaller footprint, at a cost of about 95k USD. The user-friendly control software allows for acquisitions with multiple tiles, channels, and angles at high speed.
We demonstrate several applications from neuroscience and developmental biology, as well as a novel use in physics. The microscope is designed as an open-source high-throughput system with a compact footprint, affordable cost, and assembly instructions aimed at non-experts.

miEye: bench-top cost-effective open-source single-molecule localization microscopy hardware and software platform

Marijonas Tutkus

Vilnaus University

Our miEye Bench-top super-resolution microscope system [doi:10.1016/j.ohx.2022.e00368] provides exceptional performance using affordable equipment. We achieved a lateral sample drift of approximately 10 nm over 5 minutes, while our autofocusing system effectively controlled Z drift. Additionally, we achieved a ground-truth resolution of approximately <15 nm using DNA PAINT in vitro and <30 nm using dSTORM in fixated cells. The miEye system is an open-microscopy project, and we have made all information, including parts list, assembly guide, and software code (microEye: https://github.com/samhitech/microEye for microscope control, data acquisition, and analysis/visualization), available as open-source [doi:10.17605/OSF.IO/J2FQY].

In this presentation, I will present the latest updates to our microscope’s hardware and software, which includes the installation of a dual-view emission path and 3D localization using astigmatism. We have also conducted extensive testing of various industrial-grade CMOS cameras compared to our reference sCMOS cameras. I will showcase our system’s capabilities through demonstration experiments, such as reliable tracking of HaloJF647-tagged Kinesin molecules in living eukaryotic cells on GFP-tagged microtubules, highlighting the applicability and limitations of our system. This presentation will cover advancements in our super-resolution localisation microscopy system and its use in exploring biological systems.

Harnessing Differentiable Data Models for Machine Learning Integration in Microscopy

Luis Oala

Dotphoton

The integration of machine learning with data acquisition in microscopy has emerged as a promising frontier. This abstract summarizes key concepts, results, and implications from a study exploring the potential of physically accurate, differentiable data models in enhancing image acquisition and model training.

Our study introduces drift synthesis, forensics, and optimization, all underpinned by a differentiable data model. Drift synthesis creates physically faithful test cases for model selection. Forensics identifies areas for performance improvement. Optimization employs machine learning to optimize image processing by backpropagating from the task model through the ISP to the raw sensor data.

The microscopy experiments demonstrate the effectiveness of these concepts. Task models trained on physically faithful data models outperformed those trained on common corruptions. Changes in the black level configuration and denoising parameters pose the greatest risk for task model performance. The drift optimization experiment demonstrated how raw data and a differentiable data model can be used to identify unfavorable data models that should be avoided during task model deployment.

These findings suggest that machine-optimized processing could lower hardware costs, making high-quality ISPs more affordable. The use of physically accurate data models for dataset drift validation underscores the importance of precise data models in maintaining task model performance.

In the context of the Open Hardware in Imaging workshop, these findings highlight the potential of machine learning and physically accurate, differentiable data models to innovate image acquisition and model training in microscopy. The differentiable nature of the data model allows for the integration of classical machine learning with data acquisition, opening up new possibilities for research and application in microscopy.

For more details, refer to the full paper Oala, Luis, Marco Aversa, Gabriel Nobis, Kurt Willis, Yoan Neuenschwander, Michèle Buck, Christian Matek et al. “Data Models for Dataset Drift Controls in Machine Learning With Optical Images.” Transactions on Machine Learning Research (2023).

 

An open source structured illumination microscopy extension for general fluorescence microscope body

Haoran Wang

Leibniz-Institute of Photonic Technology, Jena, Germany

This work demonstrates a structured illumination extension for a general epi-fluorescence microscope.  Its low photon-dose and speed makes structured illumination microscopy (SIM) an ideal super-resolution (up to 2x) fluorescence microscopy for live cell imaging. However, the high price tag of commercial and home build devices makes it a rare and exclusive tool not available to a large group of researchers.

In our setup, a digital mirror device (DMD) is used as a spatial light modulator operating at video frame rates. The setup is fully controlled by the open source software “ImSwitch”, and thanks to the SIM reconstruction algorithm, the setup can reconstruct the raw images in real time. The self-contained module adapts to many commercial microscope bodies and can be replicated using off-the-shelf tools and hardware to provide high-resolution microscopy techniques on a small budget.

General-purpose microscope control via Python: ImSwitch

Jacopo Abramo

Leibniz-Institute of Photonic Technology, Jena, Germany

ImSwitch is an open-source microscope control software designed for custom-built microscopy setups. Fully developed in Python, it uses a Model-Viewer-Presenter (MVP) architecture – a standard in the industry as well. It offers strong modularity through customizable widgets that can be loaded as needed through JSON configuration files. ImSwitch supports hardware synchronization for scanning techniques and provides an extendable hardware layer, enabling seamless integration of different microscope components. By embedding napari, it also opens the possibility of using existing napari plugins in cohesion with the software. The ImSwitch community also aims to enrich the device control layer by integrating the Micro-Manager core with its rich support of devices.

The BrightEyes-TTM: an open-source time-tagging module for fluorescence laser scanning microscopy

Mattia Donato

Istituto Italiano di Tecnologia, Molecular Microscopy and Spectroscopy

Single-photon avalanche diode array detectors (SPAD) array detectors have changing fluorescence laser-scanning microscopy (LSM) by giving a new set of information about the location opening to a new photon-resolved data acquisition approach. Fluorescent photons are recorded one-by-one with a series of spatial and temporal signatures precluded to typical single-element detectors.

The rapid progress of detectors SPAD array detectors and the ever-evolving demands of research goals have motivated us to develop an open-source, low-cost, versatile, multi-channels time-tagging module (TTM) based on a FPGA (Field-Programmable Gate Array). The TTM is capable of simultaneously tagging multiple single-photon events with a precision of 30 ps, as well as multiple synchronization events with a precision of 4 ns.

The TTM is a slave device that can be easily connected to LSM microscope equipped with SPAD array detector, enabling to perform live-cell super-resolved fluorescence lifetime image scanning microscopy and fluorescence lifetime fluctuation spectroscopy.

Implemented on a commercial Xilinx Kintex-7 FPGA evaluation board, the TTM is an FPGA project developed using VHDL/Verilog. With its user-friendly approach, the pre-compiled firmware can be effortlessly uploaded by users onto the FPGA. The TTM seamlessly streams data through the USB 3.0 port. At the same time as the source code is available, experts can modify it and adapt it to the own needs. Furthermore, the TTM offers a framework of software for data acquisition and a set of Python library for data analysis.

The BrightEyes-TTM is part of the open-source suite, which was born as an offshoot of the BrightEyes project founded by the ERC in 2018. This suite also includes the Microscope Control System (MCS), a Python/NIFPGA-based microscope control system, and a comprehensive Python library for advanced data analysis in Image Scanning Microscopy (ISM).

We are confident that the introduction of the BrightEyes-TTM can support the microscopy community in promoting the adoption of SP-LSM in life science laboratories.

Looking back on the “BioImaging and the European Open Science Cloud” workshop

Looking back on the “BioImaging and the European Open Science Cloud” workshop

What a great opportunity to engage different stakeholders in a dialogue about Open Science, Open Data and the Sustainability of the EOSC!

Workshop crowd 2023

Scenes from the BioImaging and European Open Science Cloud workshop

The Euro-BioImaging Industry Board,  supported by the EOSC-Life project, organized this 1.5-day workshop with more than 85 participants online and on site in Heidelberg, Germany. We saw a great mix of attendees from our imaging facilities, companies in the imaging sector, EOSC-Life partners, policy and publishing.

The meeting kicked off with a first session on Image Data Analysis as a Service, in which several Euro-BioImaging Nodes shared insights into their capacities for offering these services to users and the workflows and pipelines they support.

Industry Board Coordinator Claudia Pfander and Industry Board Chair Herbert Schaden (ZEISS) officially opened the event, and Herbert  Schaden explained why keeping in control of the ever-increasing amount of imaging data is important for quality research and of high interest for industry. His talk was followed by presentations from different organizations supporting the road towards FAIRification, from the BioImage Archive to national initiatives such as I3D:bio. Speakers then joined the panel discussion on how to facilitate FAIR data generation.

After lunch and a tour of the Imaging Centre, speakers from the Euro-BioImaging Nodes and industry presented challenges & solutions for research data management at core facilities. Martin Tewinkel, EVIDENT Olympus & Industry Board Co-Chair, explored challenges from his perspective on (big) data management.

The next session was dedicated to the European Open Science Cloud, with talks from Ilaria Nardello of the EOSC Association, and presentations on specific Open Science developments that image analysts can use to make it easier to take their data & metadata to the cloud. These tools include the BAND virtual desktop, OME.Zarr and other next generation file formats (NGFF), as well Galaxy and other developments to link the user with different data (analysis) resources. Industry partners also shared some of their big data tools and developments. The day closed with a great panel discussion on how to bring image analysis tools into the cloud and connect to EOSC.

Day 2 opened with use cases from EOSC-Life, sharing results from different cloud-based solutions and tools developed with funding from the project, including success stories from EOSC-Life open calls. Presenters highlighted other EC projects in the wider EOSC landscape that will bring Open Imaging Data sets and tools such as machine learning and BioImage models to researchers.

The concluding panel discussion highlighted the efforts made on the level of the scientific community and policy makers to implement EOSC and explored how institutions, research infrastructures and journals could step up their game to support long-term sustainability.

We were lucky to see so many FAIR data and open science enthusiasts, witness the many fruitful discussion and explore future avenues for collaboration. We would like to thank all the speakers, chairs, participants and organizers for making this such a great event!

This meeting and EOSC-Life have received funding from the European Union’s Horizon 2020 programme under grant agreement number 824087.

Online participation still possible: “BioImaging and the European Open Science Cloud”, 19-20 April 2023

Online participation still possible: “BioImaging and the European Open Science Cloud”, 19-20 April 2023

WS_Header_remote

This exciting 1.5-day workshop, organized by Euro-BioImaging and its Industry Board in collaboration with EOSC-Life, brings together the EOSC-Life community with imaging facilities and companies in the imaging field, to exchange on tools, workflows, data resources and data services with a specific focus on image data.

Topics will include:

  • Image Analysis as a service
  • Image Data Management for imaging facilities
  • FAIR image data and data services
  • Transitioning cloud-compatible tools and services to the EOSC
  • Imaging-related projects and initiative in the wider EOSC landscape

and discuss sustainability, funding models and opportunities for industry in our panel discussion. There will also be an opportunity to join some of the session remotely.

Download the full agenda.

You can now join this meeting remotely! 

09:00 – 10:30

Providing Image Data Analysis as a Service

User projects and access models for image analysis service provision

Coffee Break
11:00 – 11:15 Image data and why it matters to industry
11:15 – 12:30

FAIR data and image data services

Open Image Data repositories, Image Data Infrastructures and Services

Lunch Break
13:00 – 15:15

Image Data Management for facilities

Challenges and solutions for research data management at imaging facilities

Coffee Break
15:45 – 18:30 (incl. break)

Transitioning cloud-compatible tools and services to the EOSC

File formats, workflows, tools and commercial solutions in the cloud

Dinner

all times are CEST

09:00 – 10:15

Imaging in the EOSC landscape – projects and initiatives

EOSC-Life use cases, open call projects and image data projects in the wider EOSC landscape

Coffee Break and poster session
11:00 – 12:30

Panel discussion

Sustainability and long-term perspective for Imaging and EOSC

Lunch and departure

all times are CEST

EU flag
This meeting and EOSC-Life have received funding from the European Union’s Horizon 2020 programme under grant agreement number 824087.
Workshop on “BioImaging and the European Open Science Cloud” 19-20 April 2023

Workshop on “BioImaging and the European Open Science Cloud” 19-20 April 2023

This exciting 1.5-day workshop, organized by Euro-BioImaging and its Industry Board in collaboration with EOSC-Life, brings together the EOSC-Life community with imaging facilities and companies in the imaging field, to exchange on tools, workflows, data resources and data services with a specific focus on image data.

The meeting will be organized as an in person event at Euro-BioImaging in Heidelberg, Germany.

We will hear about topics such as

  • Image Analysis as a service
  • Image Data Management for imaging facilities
  • FAIR image data and data services
  • Transitioning cloud-compatible tools and services to the EOSC
  • Imaging-related projects and initiative in the wider EOSC landscape

and discuss sustainability, funding models and opportunities for industry in our panel discussion. There will also be an opportunity to join some of the session remotely.

Download the draft agenda: Agenda_BioImaging_and_EOSC_v5

 

This meeting requires registration. Please sign up for the event here.

Deadline 1 March!

09:00 – 09:15 Welcome and opening
09:15 – 10:35 Providing Image Data Analysis as a Service

User projects and access models for image analysis service provision

Coffee Break
11:20 – 11:35 Image data and why it matters to industry
11:35 – 13:00 Image Data Management for facilities

Challenges and solutions for research data management at imaging facilities

Lunch Break
14:00 – 15:30 FAIR data and image data services

Open Image Data repositories, Image Data Infrastructures and Services

Coffee Break
16:00 – 18:30 (incl. break) Transitioning cloud-compatible tools and services to the EOSC

File formats, workflows, tools and commercial solutions in the cloud

Dinner

all times are CEST

09:00 – 10:15

Imaging in the EOSC landscape – projects and initiatives

EOSC-Life use cases, open call projects and image data projects in the wider EOSC landscape

Coffee Break and poster session
11:00 – 12:30

Panel discussion

Sustainability and long-term perspective for Imaging and EOSC

Lunch and departure

all times are CEST

EU flag
This meeting and EOSC-Life have received funding from the European Union’s Horizon 2020 programme under grant agreement number 824087.
Virtual Pub Special “Data” Edition – September 9, 2022

Virtual Pub Special “Data” Edition – September 9, 2022

Data is THE hot topic in imaging these days. That’s why we’ve planned a two-part Special Edition of the Virtual Pub to cover the topic of “DATA” in Biological & Biomedical Imaging. These events will each be 2-hours long and will feature short presentations from academics and industry showcasing a range of image data management and analysis solutions for Biological & Biomedical imaging.

Part 1 on 9th July was a great success, and Frances Wong from University of Dundee won the prize for best presentation (as voted by the audience) for her talk “Making BioImage Data FAIR on a Global Scale: The Image Data Resource”. 

Part 2 of our Special Edition Virtual Pub Part 1 on the topic of “DATA in biological and biomedical imaging” will take place on Friday 9th September 2022.

From visualising 3D and 4D data to autonomous microscopy to deep learning – there is something for everyone, so don’t miss out!

With speakers from academia and industry and again a prize for the best short presentation voted for by our audience!

 

13:00-13:10 Welcome and Intro
13:10-13:25 Kinetically consistent data assimilation for plant PET sparse Time Activity Curve signals – Nicola D’Ascenzo, Instituto Neurologico Mediterraneo NEUROMED IRCCS
13:25-13:40 Nucleome Browser: An integrative and multimodal data navigation platform for 4D Nucleome – Yang Zhang, Carnegie Mellon University
13:40-13:55 Exploring high-content microscopic data  – Mike Woerdemann, Olympus Soft Imaging Solutions
13:55-14:10 Learning from users how to gain insights from microscopy images – a case study for applied AI towards autonomous image analysis – Luciano Lucas, Leica Microsystems
14:10-14:25 Spatial plot – new way to understand your microscopy data – Anna Paszulewicz, Imaris – Oxford Instruments
14:25-14:40 Piximi – a deep learning images to discovery tool – Beth Cimini, Broad Institute
14:40-14:45 Voting on the best presentation and Wrap-Up

all times are CEST

 

13:00-13:10

Welcome and Intro

13:10-13:25

Cloud-based interactive image data exploration with the Image Data Explorer – Jean-Karim Hériché, EMBL

13:25-13:40

Making BioImage Data FAIR on a Global Scale: The Image Data Resource – Frances Wong, University of Dundee

13:40-13:55

Multi-beam EM revolution – more data to insight Gerard Rauwerda, Technolution B.V.

13:55-14:10

HIVE- Efficient image data workflows – Peter Zehetmayer, ACQUIFER Imaging GmbH

14:10-14:25

Development and evaluation of an automatic approach for identification and assessment of Tumor-Infiltrating Lymphocytes in Breast Cancer – Valentina Brancato, IRCCS Synlab SDN

14:25-14:40

XNAT-PIC: Extending XNAT to Preclinical Imaging Centers – Riccardo Gambino, Universita degli Studi di Torino

14:40-14:50

Voting for the best presenter & Wrap-up

all times are CEST

Recordings

Virtual Pub Special “Data” Edition – July 8, 2022

Virtual Pub Special “Data” Edition – July 8, 2022

Data is THE hot topic in imaging these days. That’s why we’ve planned a two-part Special Edition of the Virtual Pub to cover the topic of “DATA” in Biological & Biomedical Imaging. These events will each be 2-hours long and will feature short presentations from academics and industry showcasing a range of image data management and analysis solutions for Biological & Biomedical imaging.

From visualising large data sets, storing, managing, curating & sharing data and metadata – to image analysis tools and data repositories, there is something for everyone, so don’t miss out!

Join us this Friday 8th July 2022 for our Special Edition Virtual Pub Part 1 on the topic of “DATA in biological and biomedical imaging”.

With speakers from academia and industry and a prize for the best short presentation voted for by our audience!

Part 2 will take place on 9th September!

 

13:00-13:10

Welcome and Intro

13:10-13:25

Cloud-based interactive image data exploration with the Image Data Explorer – Jean-Karim Hériché, EMBL

13:25-13:40

Making BioImage Data FAIR on a Global Scale: The Image Data Resource – Frances Wong, University of Dundee

13:40-13:55

Multi-beam EM revolution – more data to insight Gerard Rauwerda, Technolution B.V.

13:55-14:10

HIVE- Efficient image data workflows – Peter Zehetmayer, ACQUIFER Imaging GmbH

14:10-14:25

Development and evaluation of an automatic approach for identification and assessment of Tumor-Infiltrating Lymphocytes in Breast Cancer – Valentina Brancato, IRCCS Synlab SDN

14:25-14:40

XNAT-PIC: Extending XNAT to Preclinical Imaging Centers – Riccardo Gambino, Universita degli Studi di Torino

14:40-14:50

Voting for the best presenter & Wrap-up

all times are CEST

 

13:00-13:10

Welcome and Intro

13:10-13:25

Kinetically consistent data assimilation for plant PET sparse Time Activity Curve signals – Nicola D’Ascenzo, Instituto Neurologico Mediterraneo NEUROMED IRCCS

13:25-13:40

Nucleome Browser: An integrative and multimodal data navigation platform for 4D Nucleome – Yang Zhang, Carnegie Mellon University

13:40-13:55

Exploring high-content microscopic data  – Mike Woerdemann, Olympus Soft Imaging Solutions

13:55-14:10

Learning from users how to gain insights from microscopy images – a case study for applied AI towards autonomous image analysis – Luciano Lucas, Leica Microsystems

14:10-14:25

Spatial plot – new way to understand your microscopy data – Anna Paszulewicz, Imaris – Oxford Instruments

14:25-14:40

GliaMorph: A data analysis toolkit to quantify 3D glial cell morphology – Elisabeth Kugler, University College London

14:40-14:55

Piximi – a deep learning images to discovery tool – Beth Cimini, Broad Institute

14:55-15:00

Voting on the best presentation and Wrap-Up

all times are CEST