scholarly journals Image Processing Filters for Grids of Cells Analogous to Filters Processing Grids of Pixels

2021 ◽  
Vol 3 ◽  
Author(s):  
Robert Haase
Keyword(s):  
Image Processing ◽  
Open Source ◽  
Open Source Software ◽  
Image Data ◽  
Tissue Level ◽  
General Purpose ◽  
Cellular Processes ◽  
Microscopy Image ◽  
Programming Skills ◽  
User Friendly

Intra- and extra-cellular processes shape tissues together. For understanding how neighborhood relationships between cells play a role in this process, having image processing filters based on these relationships would be beneficial. Those operations are known and their application to microscopy image data typically requires programming skills. User-friendly general purpose tools for pursuing image processing on a level of neighboring cells were yet missing. In this manuscript I demonstrate image processing filters which process grids of cells on tissue level and the analogy to their better known counter parts processing grids of pixels. The tools are available as part of free and open source software in the ImageJ/Fiji and napari ecosystems and their application does not require any programming experience.

scholarly journals Integrated open-source software for multiscale electrophysiology

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Konstantinos Nasiotis ◽  
Martin Cousineau ◽  
François Tadel ◽  
Adrien Peyrache ◽  
Richard M. Leahy ◽  
...  
Keyword(s):  
Data Analysis ◽  
Open Source ◽  
Open Source Software ◽  
Analysis Data ◽  
Open Science ◽  
Dense Array ◽  
Unrestricted Access ◽  
Research Transparency ◽  
Programming Skills ◽  
User Friendly

Abstract The methods for electrophysiology in neuroscience have evolved tremendously over the recent years with a growing emphasis on dense-array signal recordings. Such increased complexity and augmented wealth in the volume of data recorded, have not been accompanied by efforts to streamline and facilitate access to processing methods, which too are susceptible to grow in sophistication. Moreover, unsuccessful attempts to reproduce peer-reviewed publications indicate a problem of transparency in science. This growing problem could be tackled by unrestricted access to methods that promote research transparency and data sharing, ensuring the reproducibility of published results. Here, we provide a free, extensive, open-source software that provides data-analysis, data-management and multi-modality integration solutions for invasive neurophysiology. Users can perform their entire analysis through a user-friendly environment without the need of programming skills, in a tractable (logged) way. This work contributes to open-science, analysis standardization, transparency and reproducibility in invasive neurophysiology.

scholarly journals Open-source software for mouse-tracking in Qualtrics to measure category competition

2018 ◽  
Author(s):  
Maya B Mathur ◽  
David Reichling
Keyword(s):  
Data Collection ◽  
Open Source ◽  
Real Time ◽  
Cognitive Processes ◽  
Open Source Software ◽  
Online Survey ◽  
Mouse Tracking ◽  
Crowdsourced Data ◽  
Programming Skills ◽  
User Friendly

Mouse-tracking is a sophisticated tool for measuring rapid, dynamic cognitive processes in real time, particularly in experiments investigating competition between perceptual or cognitive categories. We provide user-friendly, open-source software (https://osf.io/st2ef/) for designing and analyzing such experiments online using the Qualtrics survey platform. The software consists of a Qualtrics template with embedded Javascript and CSS along with R code to clean, parse, and analyze the data. No special programming skills are required to use this software. As we discuss, this software could be readily modified for use with other online survey platforms that allow the addition of custom Javascript. We empirically validate the provided software by benchmarking its performance on previously tested stimuli in a standard category-competition experiment with realistic crowdsourced data collection.

scholarly journals Integrated Open-Source Software for Multiscale Electrophysiology

2019 ◽  
Author(s):  
Konstantinos Nasiotis ◽  
Martin Cousineau ◽  
François Tadel ◽  
Adrien Peyrache ◽  
Richard M. Leahy ◽  
...  
Keyword(s):  
Data Analysis ◽  
Open Source ◽  
Open Source Software ◽  
Analysis Data ◽  
Open Science ◽  
Dense Array ◽  
Unrestricted Access ◽  
Research Transparency ◽  
Programming Skills ◽  
User Friendly

AbstractThe methods for electrophysiology in neuroscience have evolved tremendously over the recent years with a growing emphasis on dense-array signal recordings. Such increased complexity and augmented wealth in the volume of data recorded, have not been accompanied by efforts to streamline and facilitate access to processing methods, which too are susceptible to grow in sophistication. Moreover, unsuccessful attempts to reproduce peer-reviewed publications indicate a problem of transparency in science. This growing problem could be tackled by unrestricted access to methods that promote research transparency and data sharing, ensuring the reproducibility of published results.Here, we provide a free, extensive, open-source software that provides data-analysis, data-management and multi-modality integration solutions for invasive neurophysiology. Users can perform their entire analysis through a user-friendly environment without the need of programming skills, in a tractable (logged) way. This work contributes to open-science, analysis standardization, transparency and reproducibility in invasive neurophysiology.

scholarly journals InstantDL: an easy-to-use deep learning pipeline for image segmentation and classification

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Dominik Jens Elias Waibel ◽  
Sayedali Shetab Boushehri ◽  
Carsten Marr
Keyword(s):  
Image Processing ◽  
Deep Learning ◽  
Specific Problem ◽  
State Of The Art ◽  
Image Data ◽  
Semantic Segmentation ◽  
Parameter Tuning ◽  
Cellular Processes ◽  
Minimal Effort ◽  
Instance Segmentation

Abstract Background Deep learning contributes to uncovering molecular and cellular processes with highly performant algorithms. Convolutional neural networks have become the state-of-the-art tool to provide accurate and fast image data processing. However, published algorithms mostly solve only one specific problem and they typically require a considerable coding effort and machine learning background for their application. Results We have thus developed InstantDL, a deep learning pipeline for four common image processing tasks: semantic segmentation, instance segmentation, pixel-wise regression and classification. InstantDL enables researchers with a basic computational background to apply debugged and benchmarked state-of-the-art deep learning algorithms to their own data with minimal effort. To make the pipeline robust, we have automated and standardized workflows and extensively tested it in different scenarios. Moreover, it allows assessing the uncertainty of predictions. We have benchmarked InstantDL on seven publicly available datasets achieving competitive performance without any parameter tuning. For customization of the pipeline to specific tasks, all code is easily accessible and well documented. Conclusions With InstantDL, we hope to empower biomedical researchers to conduct reproducible image processing with a convenient and easy-to-use pipeline.

scholarly journals MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation

2019 ◽  
Author(s):  
J-Donald Tournier ◽  
Robert Smith ◽  
David Raffelt ◽  
Rami Tabbara ◽  
Thijs Dhollander ◽  
...  
Keyword(s):  
Image Processing ◽  
Medical Image ◽  
Medical Image Processing ◽  
Image Data ◽  
Data Access ◽  
General Purpose ◽  
Computational Performance ◽  
Cross Platform ◽  
High Level ◽  
New Applications

AbstractMRtrix3 is an open-source, cross-platform software package for medical image processing, analysis and visualization, with a particular emphasis on the investigation of the brain using diffusion MRI. It is implemented using a fast, modular and flexible general-purpose code framework for image data access and manipulation, enabling efficient development of new applications, whilst retaining high computational performance and a consistent command-line interface between applications. In this article, we provide a high-level overview of the features of the MRtrix3 framework and general-purpose image processing applications provided with the software.

An Empirical Investigation into the Adoption of Open Source Software in Hospitals

2009 ◽  
pp. 1608-1627
Author(s):  
Gilberto Munoz-Cornejo ◽  
Carolyn B. Seaman ◽  
A. Günes Koru
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Empirical Model ◽  
Mixed Method ◽  
Empirical Investigation ◽  
Critical Factor ◽  
General Purpose ◽  
Research Approach ◽  
Mixed Method Research ◽  
Domain Specific

Open source software (OSS) has gained considerable attention recently in healthcare. Yet, how and why OSS is being adopted within hospitals in particular remains a poorly understood issue. This research attempts to further this understanding. A mixed-method research approach was used to explore the extent of OSS adoption in hospitals as well as the factors facilitating and inhibiting adoption. The findings suggest a very limited adoption of OSS in hospitals. Hospitals tend to adopt general-purpose instead of domain-specific OSS. We found that software vendors are the critical factor facilitating the adoption of OSS in hospitals. Conversely, lack of in-house development as well as a perceived lack of security, quality, and accountability of OSS products were factors inhibiting adoption. An empirical model is presented to illustrate the factors facilitating and inhibiting the adoption of OSS in hospitals.

scholarly journals Probelab ReImager: Open Source Software for Streamlining Image Processing

2020 ◽  
Vol 26 (S2) ◽  
pp. 2176-2177
Author(s):  
Noah Kraft ◽  
Anette von der Handt
Keyword(s):  
Image Processing ◽  
Open Source ◽  
Open Source Software

scholarly journals FlowCal: A User-Friendly, Open Source Software Tool for Automatically Converting Flow Cytometry Data from Arbitrary to Calibrated Units

2016 ◽  
Vol 5 (7) ◽  
pp. 774-780 ◽  
Author(s):  
Sebastian M. Castillo-Hair ◽  
John T. Sexton ◽  
Brian P. Landry ◽  
Evan J. Olson ◽  
Oleg A. Igoshin ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
Open Source ◽  
Open Source Software ◽  
Software Tool ◽  
Flow Cytometry Data ◽  
User Friendly

Applications of remote image sensing with the NASA massively parallel processor

1988 ◽  
Vol 324 (1579) ◽  
pp. 365-372 ◽  
Keyword(s):  
Image Processing ◽  
Space Station ◽  
Image Data ◽  
General Purpose ◽  
Massively Parallel ◽  
Imaging Data ◽  
Parallel Processor ◽  
Image Sensing ◽  
Faint Object ◽  
Massively Parallel Processor

Satellite observing systems are producing image observations of the Earth’s surface and atmosphere with spectral and spatial resolutions that result in data rates that current general-purpose computing systems are incapable of processing and analysing. As a result, current processing systems have been able to analyse only limited amounts of image data with less than optimal algorithms for generating high-quality geophysical parameters. A massively parallel processor (mpp) is operationally available at NASA/GSFC for routine image-analysis applications. Research studies with the mpp are being pursued in the area of interactive spatial contextual classifications for the land thematic mapper data, automatic SIR-B stereo terrain mapping, icemotion detection, faint-object image restoration and other general purpose ocean and land image-processing systems. Several applications are presented comparing the mpp products with enhancements of imaging data with standard image-processing methods. Finally, a work-station parallel processor for space station on-board image processing will be described.

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