scholarly journals EZcalcium: Open Source Toolbox for Analysis of Calcium Imaging Data

2020 ◽  
Author(s):  
Daniel A. Cantu ◽  
Bo Wang ◽  
Michael W. Gongwer ◽  
Cynthia X. He ◽  
Anubhuti Goel ◽  
...  
Keyword(s):  
Data Analysis ◽  
Open Source ◽  
User Interfaces ◽  
Calcium Imaging ◽  
Unmet Need ◽  
Brain Slices ◽  
Relevant Information ◽  
Imaging Data ◽  
Action Potential Firing ◽  
Pixel Intensity

AbstractFluorescence calcium imaging using a range of microscopy approaches, such as 2-photon excitation or head-mounted ‘miniscopes’, is one of the preferred methods to record neuronal activity and glial signals in various experimental settings, including acute brain slices, brain organoids, and behaving animals. Because changes in the fluorescence intensity of genetically encoded or chemical calcium indicators correlate with action potential firing in neurons, data analysis is based on inferring such spiking from changes in pixel intensity values across time within different regions of interest. However, the algorithms necessary to extract biologically relevant information from these fluorescent signals are complex and require significant expertise in programming to develop robust analysis pipelines. For decades, the only way to perform these analyses was for individual laboratories to write their own custom code. These routines were typically not well annotated and lacked intuitive graphical user interfaces (GUIs), which made it difficult for scientists in other laboratories to adopt them. Although the panorama is changing with recent tools like CaImAn, Suite2P and others, there is still a barrier for many laboratories to adopt these packages, especially for potential users without sophisticated programming skills. As 2-photon microscopes are becoming increasingly affordable, the bottleneck is no longer the hardware, but the software used to analyze the calcium data in an optimal manner and consistently across different groups. We addressed this unmet need by incorporating recent software solutions for motion correction, segmentation, signal extraction and deconvolution of calcium imaging data into an open-source, easy to use, GUI-based, intuitive and automated data analysis software, which we named EZcalcium.

scholarly journals CaImAn an open source tool for scalable calcium imaging data analysis

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Andrea Giovannucci ◽  
Johannes Friedrich ◽  
Pat Gunn ◽  
Jérémie Kalfon ◽  
Brandon L Brown ◽  
...  
Keyword(s):  
Data Analysis ◽  
Open Source ◽  
Calcium Imaging ◽  
High Performance ◽  
Human Performance ◽  
Streaming Data ◽  
Imaging Data ◽  
Two Photon ◽  
Real Time Analysis

Advances in fluorescence microscopy enable monitoring larger brain areas in-vivo with finer time resolution. The resulting data rates require reproducible analysis pipelines that are reliable, fully automated, and scalable to datasets generated over the course of months. We present CaImAn, an open-source library for calcium imaging data analysis. CaImAn provides automatic and scalable methods to address problems common to pre-processing, including motion correction, neural activity identification, and registration across different sessions of data collection. It does this while requiring minimal user intervention, with good scalability on computers ranging from laptops to high-performance computing clusters. CaImAn is suitable for two-photon and one-photon imaging, and also enables real-time analysis on streaming data. To benchmark the performance of CaImAn we collected and combined a corpus of manual annotations from multiple labelers on nine mouse two-photon datasets. We demonstrate that CaImAn achieves near-human performance in detecting locations of active neurons.

scholarly journals CalmAn: An open source tool for scalable Calcium Imaging data Analysis

2018 ◽  
Author(s):  
Andrea Giovannucci ◽  
Johannes Friedrich ◽  
Pat Gunn ◽  
Jérémie Kalfon ◽  
Sue Ann Koay ◽  
...  
Keyword(s):  
Data Analysis ◽  
Open Source ◽  
Calcium Imaging ◽  
High Performance ◽  
Human Performance ◽  
Ground Truth ◽  
Streaming Data ◽  
Imaging Data ◽  
Two Photon

AbstractAdvances in fluorescence microscopy enable monitoring larger brain areas in-vivo with finer time resolution. The resulting data rates require reproducible analysis pipelines that are reliable, fully automated, and scalable to datasets generated over the course of months. Here we present CaImAn, an open-source library for calcium imaging data analysis. CaImAn provides automatic and scalable methods to address problems common to pre-processing, including motion correction, neural activity identification, and registration across different sessions of data collection. It does this while requiring minimal user intervention, with good performance on computers ranging from laptops to high-performance computing clusters. CaImAn is suitable for two-photon and one-photon imaging, and also enables real-time analysis on streaming data. To benchmark the performance of CaImAn we collected a corpus of ground truth annotations from multiple labelers on nine mouse two-photon datasets. We demonstrate that CaImAn achieves near-human performance in detecting locations of active neurons.

scholarly journals Author response: CaImAn an open source tool for scalable calcium imaging data analysis

2018 ◽  
Author(s):  
Andrea Giovannucci ◽  
Johannes Friedrich ◽  
Pat Gunn ◽  
Jérémie Kalfon ◽  
Brandon L Brown ◽  
...  
Keyword(s):  
Data Analysis ◽  
Open Source ◽  
Calcium Imaging ◽  
Author Response ◽  
Imaging Data ◽  
Open Source Tool

scholarly journals An open source tool for automatic spatiotemporal assessment of calcium transients and local ‘signal-close-to-noise’ activity in calcium imaging data

2018 ◽  
Vol 14 (3) ◽  
pp. e1006054 ◽  
Author(s):  
Juan Prada ◽  
Manju Sasi ◽  
Corinna Martin ◽  
Sibylle Jablonka ◽  
Thomas Dandekar ◽  
...  
Keyword(s):  
Open Source ◽  
Calcium Imaging ◽  
Calcium Transients ◽  
Imaging Data ◽  
Open Source Tool

scholarly journals EZcalcium: Open-Source Toolbox for Analysis of Calcium Imaging Data

2020 ◽  
Vol 14 ◽  
Author(s):  
Daniel A. Cantu ◽  
Bo Wang ◽  
Michael W. Gongwer ◽  
Cynthia X. He ◽  
Anubhuti Goel ◽  
...  
Keyword(s):  
Open Source ◽  
Calcium Imaging ◽  
Imaging Data

scholarly journals An open-source method for analysis of confocal calcium imaging with sparse cells

2021 ◽  
Author(s):  
Alisa A. Omelchenko ◽  
Lina Ni
Keyword(s):  
Animal Models ◽  
Single Cell ◽  
Open Source ◽  
Calcium Imaging ◽  
Human Error ◽  
Cell Types ◽  
List Type ◽  
Imaging Data ◽  
Source Method ◽  
Programming Knowledge

AbstractBackgroundThe research in the neuroscience field has evolved to use complex imaging and computational tools to extract comprehensive information from data sets. Calcium imaging is a widely used technique that requires sophisticated software to get precise and reproducible results. Many laboratories struggle to adopt computational methods due to the lack of computational knowledge and paywalls for software.New MethodHere we propose a calcium imaging analysis method using TrackMate, an open-source Fiji plugin, to track neurons at single-cell resolution, detect regions of interest (ROIs), and extract fluorescence intensities. For confocal images, this method uses the maximal value to represent the cell intensity for each z stack. This method can be done without coding or be combined with Python or Jupyter Notebook scripts to accelerate the analysis.ResultsThis method is validated in fly larval cool neurons, whose calcium changes in these neurons respond to temperature fluctuation. It also identifies potential problems in approaches that extract signals from maximal projection images.Comparison with existing methodsThis method does not depend on programming knowledge and/or commercial software but uses open-source software and requires no coding abilities. Since TrackMate automatically defines ROIs, this method greatly avoids human error and increases reproducibility. In addition, practice images and a step-by-step guide are provided to help users adopt this method in their experiments.ConclusionsTherefore, this open-source method allows for the analysis of calcium imaging data at single-cell resolution with high reproducibility and has the potential to be applied in various cell types and animal models by researchers with different programming abilities.HighlightsTrackMate is applied to analyze calcium changes at single-cell resolution.This method depends on an open-source Fiji software, ensures reproducibility, and requires no coding ability.Practice images and a step-by-step guide are provided to implement this method in various cell types and animal models.

scholarly journals Implementation of a Six-Layer Smart Factory Architecture with Special Focus on Transdisciplinary Engineering Education

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 2944
Author(s):  
Benjamin James Ralph ◽  
Marcel Sorger ◽  
Benjamin Schödinger ◽  
Hans-Jörg Schmölzer ◽  
Karin Hartl ◽  
...  
Keyword(s):  
Open Source ◽  
User Interfaces ◽  
Industrial Revolution ◽  
Low Cost ◽  
Material Behavior ◽  
Sensor Data ◽  
Management Tool ◽  
Special Focus ◽  
Programming Environments ◽  
Metal Processing

Smart factories are an integral element of the manufacturing infrastructure in the context of the fourth industrial revolution. Nevertheless, there is frequently a deficiency of adequate training facilities for future engineering experts in the academic environment. For this reason, this paper describes the development and implementation of two different layer architectures for the metal processing environment. The first architecture is based on low-cost but resilient devices, allowing interested parties to work with mostly open-source interfaces and standard back-end programming environments. Additionally, one proprietary and two open-source graphical user interfaces (GUIs) were developed. Those interfaces can be adapted front-end as well as back-end, ensuring a holistic comprehension of their capabilities and limits. As a result, a six-layer architecture, from digitization to an interactive project management tool, was designed and implemented in the practical workflow at the academic institution. To take the complexity of thermo-mechanical processing in the metal processing field into account, an alternative layer, connected with the thermo-mechanical treatment simulator Gleeble 3800, was designed. This framework is capable of transferring sensor data with high frequency, enabling data collection for the numerical simulation of complex material behavior under high temperature processing. Finally, the possibility of connecting both systems by using open-source software packages is demonstrated.

scholarly journals ESR white paper: blockchain and medical imaging

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
◽  
Elmar Kotter ◽  
Luis Marti-Bonmati ◽  
Adrian P. Brady ◽  
Nandita M. Desouza
Keyword(s):  
Medical Imaging ◽  
Image Data ◽  
Distributed Database ◽  
Relevant Information ◽  
White Paper ◽  
Imaging Data ◽  
Data Set ◽  
Blockchain Technology ◽  
Potential Applications ◽  
Basic Technology

AbstractBlockchain can be thought of as a distributed database allowing tracing of the origin of data, and who has manipulated a given data set in the past. Medical applications of blockchain technology are emerging. Blockchain has many potential applications in medical imaging, typically making use of the tracking of radiological or clinical data. Clinical applications of blockchain technology include the documentation of the contribution of different “authors” including AI algorithms to multipart reports, the documentation of the use of AI algorithms towards the diagnosis, the possibility to enhance the accessibility of relevant information in electronic medical records, and a better control of users over their personal health records. Applications of blockchain in research include a better traceability of image data within clinical trials, a better traceability of the contributions of image and annotation data for the training of AI algorithms, thus enhancing privacy and fairness, and potentially make imaging data for AI available in larger quantities. Blockchain also allows for dynamic consenting and has the potential to empower patients and giving them a better control who has accessed their health data. There are also many potential applications of blockchain technology for administrative purposes, like keeping track of learning achievements or the surveillance of medical devices. This article gives a brief introduction in the basic technology and terminology of blockchain technology and concentrates on the potential applications of blockchain in medical imaging.

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