scholarly journals ALADIN‐—An open‐source MATLAB toolbox for distributed non‐convex optimization

Author(s):  
Alexander Engelmann ◽  
Yuning Jiang ◽  
Henrieke Benner ◽  
Ruchuan Ou ◽  
Boris Houska ◽  
...  
2020 ◽  
Vol 196 ◽  
pp. 105716
Author(s):  
Zachary A. Vesoulis ◽  
Paul G. Gamble ◽  
Siddharth Jain ◽  
Nathalie M. El Ters ◽  
Steve M. Liao ◽  
...  

2017 ◽  
Vol 65 (3) ◽  
Author(s):  
Wolfgang Doneit ◽  
Ralf Mikut ◽  
Lutz Gröll ◽  
Tim Pychynski ◽  
Markus Reischl
Keyword(s):  

ZusammenfassungIn diesem Beitrag wird DaMoQ vorgestellt, eine Erweiterung zur MATLAB-Toolbox SciXMiner, um die Datenqualität von Eingangsdaten für Regressionen zu bewerten. Bei SciXMiner handelt es sich um eine Open-Source-MATLAB-Toolbox zur automatisierten Bild- und Datenanalyse. In DaMoQ werden verschiedene Muster ungleichmäßiger Verteilungen in Datensätzen quantifiziert und visualisiert. Während die Visualisierungen dem Anwender einen schnellen Einblick in den vorliegenden Datensatz geben, wird die Quantifizierung für eine aggregierte Bewertung der einzelnen Eingangsgrößen sowie des Datensatzes genutzt. Anhand Benchmark-Datensätze und einer Anwendung für Labyrinthdichtungen wird gezeigt, dass die Kriterien und Visualisierungen von DaMoQ nicht nur ähnliche Ergebnisse wie eine visuelle Analyse der Streuwolkendiagramme liefern, sondern auch visuell schwer erkennbare Phänomene identifizieren.


2018 ◽  
Vol 159 (4) ◽  
pp. 1105-1111 ◽  
Author(s):  
Sándor Zsebők ◽  
György Blázi ◽  
Miklós Laczi ◽  
Gergely Nagy ◽  
Éva Vaskuti ◽  
...  

2015 ◽  
Vol 192 ◽  
pp. 348-362 ◽  
Author(s):  
Bertrand Thierry ◽  
Xavier Antoine ◽  
Chokri Chniti ◽  
Hasan Alzubaidi

Cells ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 397
Author(s):  
Boyoung Kim

To investigate the cellular structure, biomedical researchers often obtain three-dimensional images by combining two-dimensional images taken along the z axis. However, these images are blurry in all directions due to diffraction limitations. This blur becomes more severe when focusing further inside the specimen as photons in deeper focus must traverse a longer distance within the specimen. This type of blur is called depth-variance. Moreover, due to lens imperfection, the blur has asymmetric shape. Most deconvolution solutions for removing blur assume depth-invariant or x-y symmetric blur, and presently, there is no open-source for depth-variant asymmetric deconvolution. In addition, existing datasets for deconvolution microscopy also assume invariant or x-y symmetric blur, which are insufficient to reflect actual imaging conditions. DVDeconv, that is a set of MATLAB functions with a user-friendly graphical interface, has been developed to address depth-variant asymmetric blur. DVDeconv includes dataset, depth-variant asymmetric point spread function generator, and deconvolution algorithms. Experimental results using DVDeconv reveal that depth-variant asymmetric deconvolution using DVDeconv removes blurs accurately. Furthermore, the dataset in DVDeconv constructed can be used to evaluate the performance of microscopy deconvolution to be developed in the future.


2021 ◽  
Author(s):  
Lindsey M Brier ◽  
Joseph P Culver

Wide-field optical imaging (WOI) produces concurrent hemodynamic and cell-specific calcium recordings across the entire cerebral cortex. There have been multiple studies using WOI to image mouse models with various environmental or genetic manipulations to understand various diseases. Despite the obvious utility of pursuing mouse WOI alongside human functional magnetic resonance imaging (fMRI), and the multitude of analysis toolboxes in the fMRI literature, there is not an available open-source, user-friendly data processing and statistical analysis toolbox for WOI data. Here, we present our MATLAB toolbox for pre-processing WOI data, as described and adapted to combine processing techniques from multiple WOI groups. Additionally, we provide multiple data analysis packages and translate two commonly used statistical approaches from the fMRI literature to the WOI data. To illustrate the utility, we demonstrate the ability of the processing and analysis framework to detect a well-established deficit in a mouse model of stroke. Additionally, we evaluate resting state data in healthy mice.


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