scholarly journals QuickStitch for seamless stitching of confocal mosaics through high-pass filtering and recursive normalization

2016 ◽  
Author(s):  
Pavel A. Brodskiy ◽  
Paulina M. Eberts ◽  
Cody Narciso ◽  
Jochen Kursawe ◽  
Alexander Fletcher ◽  
...  
Keyword(s):  
Open Source ◽  
Large Scale ◽  
Imaging System ◽  
Tissue Level ◽  
Cellular Level ◽  
Specific Information ◽  
Open Source Tool ◽  
The Individual ◽  
User Friendly ◽  
High Pass

ABSTRACTFluorescence micrographs naturally exhibit darkening around their edges (vignetting), which makes seamless stitching challenging. If vignetting is not corrected for, a stitched image will have visible seams where the individual images (tiles) overlap, introducing a systematic error into any quantitative analysis of the image. Although multiple vignetting correction methods exist, there remains no open-source tool that robustly handles large 2D immunofluorescence-based mosaic images. Here, we develop and validate QuickStitch, a tool that applies a recursive normalization algorithm to stitch large-scale immunofluorescence-based mosaics without incurring vignetting seams. We demonstrate how the tool works successfully for tissues of differing size, morphology, and fluorescence intensity. QuickStitch requires no specific information about the imaging system. It is provided as an open-source tool that is both user friendly and extensible, allowing straightforward incorporation into existing image processing pipelines. This enables studies that require accurate segmentation and analysis of high-resolution datasets when parameters of interest include both cellular-level phenomena and larger tissue-level regions of interest.

scholarly journals An individual-based mechanical model of cell movement in heterogeneous tissues and its coarse-grained approximation

2018 ◽  
Author(s):  
R. J. Murphy ◽  
P. R. Buenzli ◽  
R. E. Baker ◽  
M. J. Simpson
Keyword(s):  
Mechanical Model ◽  
Numerical Solutions ◽  
Cell Movement ◽  
Biological Tissues ◽  
Tissue Level ◽  
Cellular Level ◽  
Coarse Grained ◽  
Mechanical Heterogeneity ◽  
Single Scale ◽  
The Individual

AbstractMechanical heterogeneity in biological tissues, in particular stiffness, can be used to distinguish between healthy and diseased states. However, it is often difficult to explore relationships between cellular-level properties and tissue-level outcomes when biological experiments are performed at a single scale only. To overcome this difficulty we develop a multi-scale mathematical model which provides a clear framework to explore these connections across biological scales. Starting with an individual-based mechanical model of cell movement, we subsequently derive a novel coarse-grained system of partial differential equations governing the evolution of the cell density due to heterogeneous cellular properties. We demonstrate that solutions of the individual-based model converge to numerical solutions of the coarse-grained model, for both slowly-varying-in-space and rapidly-varying-in-space cellular properties. Applications of the model are discussed, including determining relative cellular-level properties and an interpretation of data from a breast cancer detection experiment.

scholarly journals BrainIAK tutorials: User-friendly learning materials for advanced fMRI analysis

2019 ◽  
Author(s):  
Manoj Kumar ◽  
Cameron Thomas Ellis ◽  
Qihong Lu ◽  
Hejia Zhang ◽  
Mihai Capota ◽  
...  
Keyword(s):  
Machine Learning ◽  
Functional Connectivity ◽  
Open Source ◽  
Programming Languages ◽  
High Performance ◽  
Large Scale ◽  
Markov Models ◽  
Matrix Analysis ◽  
Fmri Analysis ◽  
User Friendly

Advanced brain imaging analysis methods, including multivariate pattern analysis (MVPA), functional connectivity, and functional alignment, have become powerful tools in cognitive neuroscience over the past decade. These tools are implemented in custom code and separate packages, often requiring different software and language proficiencies. Although usable by expert researchers, novice users face a steep learning curve. These difficulties stem from the use of new programming languages (e.g., Python), learning how to apply machine-learning methods to high-dimensional fMRI data, and minimal documentation and training materials. Furthermore, most standard fMRI analysis packages (e.g., AFNI, FSL, SPM) focus on preprocessing and univariate analyses, leaving a gap in how to integrate with advanced tools. To address these needs, we developed BrainIAK (brainiak.org), an open-source Python software package that seamlessly integrates several cutting-edge, computationally efficient techniques with other Python packages (e.g., Nilearn, Scikit-learn) for file handling, visualization, and machine learning. To disseminate these powerful tools, we developed user-friendly tutorials (in Jupyter format; https://brainiak.org/tutorials/) for learning BrainIAK and advanced fMRI analysis in Python more generally. These materials cover techniques including: MVPA (pattern classification and representational similarity analysis); parallelized searchlight analysis; background connectivity; full correlation matrix analysis; inter-subject correlation; inter-subject functional connectivity; shared response modeling; event segmentation using hidden Markov models; and real-time fMRI. For long-running jobs or large memory needs we provide detailed guidance on high-performance computing clusters. These notebooks were successfully tested at multiple sites, including as problem sets for courses at Yale and Princeton universities and at various workshops and hackathons. These materials are freely shared, with the hope that they become part of a pool of open-source software and educational materials for large-scale, reproducible fMRI analysis and accelerated discovery.

scholarly journals Parameterized and automated assessment on an introductory programming course

2020 ◽  
Author(s):  
Francisco De Assis Zampirolli ◽  
Paulo Henrique Pisani ◽  
João Marcelo Josko ◽  
Guiou Kobayashi ◽  
Francisco Fraga ◽  
...  
Keyword(s):  
Blended Learning ◽  
Open Source ◽  
Programming Language ◽  
Test Generation ◽  
Large Scale ◽  
Automatic Generation ◽  
Automated Assessment ◽  
Open Source Tool ◽  
Reliable Assessment ◽  
Innovative Solution

The generation of individualized exams can contribute to a more reliable assessment of the students. Manually performing this procedure may not be feasible, even more on a large scale. An alternative to deal with it is the automatic generation of questions. This paper discusses an innovative solution to simplify test generation and correction through parameterized questions in the context of a four-month Introduction to Programming course under a blended- learning (IP-BL) approach. It combines the open-source tool MCTest with Moodle and VPL plugin to generate and also automatically evaluate parameterized programming language questions. We applied an intervention based on this solution in two IP-BL groups (a total of 171 enrolled students) using Java.

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 Cell-type-specific resolution epigenetics without the need for cell sorting or single-cell biology

2018 ◽  
Author(s):  
Elior Rahmani ◽  
Regev Schweiger ◽  
Brooke Rhead ◽  
Lindsey A. Criswell ◽  
Lisa F. Barcellos ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Sorting ◽  
Cell Biology ◽  
Large Scale ◽  
Tissue Level ◽  
Cell Type ◽  
Validation Data ◽  
Cell Type Specific ◽  
Disease Associated Genes ◽  
The Individual

AbstractHigh costs and technical limitations of cell sorting and single-cell techniques currently restrict the collection of large-scale, cell-type-specific DNA methylation data. This, in turn, impedes our ability to tackle key biological questions that pertain to variation within a population, such as identification of disease-associated genes at a cell-type-specific resolution. Here, we show mathematically and empirically that cell-type-specific methylation levels of an individual can be learned from its tissue-level bulk data, conceptually emulating the case where the individual has been profiled with a single-cell resolution and then signals were aggregated in each cell population separately. Provided with this unprecedented way to perform powerful large-scale epigenetic studies with cell-type-specific resolution, we revisit previous studies with tissue-level bulk methylation and reveal novel associations with leukocyte composition in blood and with rheumatoid arthritis. For the latter, we further show consistency with validation data collected from sorted leukocyte sub-types. Corresponding software is available from: https://github.com/cozygene/TCA.

scholarly journals Chipper: Open-source software for semi-automated segmentation and analysis of birdsong and other natural sounds

2019 ◽  
Author(s):  
Abigail M. Searfoss ◽  
James C. Pino ◽  
Nicole Creanza
Keyword(s):  
Open Source ◽  
Large Scale ◽  
List Type ◽  
Natural Sounds ◽  
Science Data ◽  
Field Recordings ◽  
Multiple User ◽  
Cross Platform ◽  
Multiple Species ◽  
User Friendly

AbstractAudio recording devices have changed significantly over the last 50 years, making large datasets of recordings of natural sounds, such as birdsong, easier to obtain. This increase in digital recordings necessitates an increase in high-throughput methods of analysis for researchers. Specifically, there is a need in the community for open-source methods that are tailored to recordings of varying qualities and from multiple species collected in nature.We developed Chipper, a Python-based software to semi-automate both the segmentation of acoustic signals and the subsequent analysis of their frequencies and durations. For avian recordings, we provide widgets to best determine appropriate thresholds for noise and syllable similarity, which aid in calculating note measurements and determining syntax. In addition, we generated a set of synthetic songs with various levels of background noise to test Chipper’s accuracy, repeatability, and reproducibility.Chipper provides an effective way to quickly generate reproducible estimates of birdsong features. The cross-platform graphical user interface allows the user to adjust parameters and visualize the resulting spectrogram and signal segmentation, providing a simplified method for analyzing field recordings.Chipper streamlines the processing of audio recordings with multiple user-friendly tools and is optimized for multiple species and varying recording qualities. Ultimately, Chipper supports the use of citizen-science data and increases the feasibility of large-scale multi-species birdsong studies.

scholarly journals An open source tool to compute measures of inpatient glycemic control: translating from healthcare analytics research to clinical quality improvement

JAMIA Open ◽  
2021 ◽  
Vol 4 (2) ◽  
Author(s):  
Ying Chen ◽  
Yilin Ning ◽  
Prem Thomas ◽  
Mark Salloway ◽  
Maudrene Luor Shyuan Tan ◽  
...  
Keyword(s):  
Glycemic Control ◽  
Open Source ◽  
Graphical Interface ◽  
Prior Work ◽  
Healthcare Analytics ◽  
Privacy Concerns ◽  
Open Source Tool ◽  
Extended Code ◽  
User Friendly

Abstract Objectives The objective of this study is to facilitate monitoring of the quality of inpatient glycemic control by providing an open-source tool to compute glucometrics. To allay regulatory and privacy concerns, the tool is usable locally; no data are uploaded to the internet. Materials and Methods We extended code, initially developed for healthcare analytics research, to serve the clinical need for quality monitoring of diabetes. We built an application, with a graphical interface, which can be run locally without any internet connection. Results We verified that our code produced results identical to prior work in glucometrics. We extended the prior work by including additional metrics and by providing user customizability. The software has been used at an academic healthcare institution. Conclusion We successfully translated code used for research methods into an open source, user-friendly tool which hospitals may use to expedite quality measure computation for the management of inpatients with diabetes.

scholarly journals A one-dimensional individual-based mechanical model of cell movement in heterogeneous tissues and its coarse-grained approximation

2019 ◽  
Vol 475 (2227) ◽  
pp. 20180838 ◽  
Author(s):  
R. J. Murphy ◽  
P. R. Buenzli ◽  
R. E. Baker ◽  
M. J. Simpson
Keyword(s):  
Mechanical Model ◽  
Numerical Solutions ◽  
Cell Movement ◽  
Biological Tissues ◽  
Tissue Level ◽  
Cellular Level ◽  
Coarse Grained ◽  
Mechanical Heterogeneity ◽  
Single Scale ◽  
The Individual

Mechanical heterogeneity in biological tissues, in particular stiffness, can be used to distinguish between healthy and diseased states. However, it is often difficult to explore relationships between cellular-level properties and tissue-level outcomes when biological experiments are performed at a single scale only. To overcome this difficulty, we develop a multi-scale mathematical model which provides a clear framework to explore these connections across biological scales. Starting with an individual-based mechanical model of cell movement, we subsequently derive a novel coarse-grained system of partial differential equations governing the evolution of the cell density due to heterogeneous cellular properties. We demonstrate that solutions of the individual-based model converge to numerical solutions of the coarse-grained model, for both slowly-varying-in-space and rapidly-varying-in-space cellular properties. We discuss applications of the model, such as determining relative cellular-level properties and an interpretation of data from a breast cancer detection experiment.

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