3/10/2024 0 Comments ImagejfijiAnother advantage of 1D analysis is its directional sensitivity. Interestingly, 1D morphological analysis is also highly relevant in oncology, mainly because of the full compatibility of 1D analysis with irregularly shaped tumour regions of interest (ROI) in medical images. However, the outcome of such nonlinear dynamical systems can be investigated by their morphological characteristics with 2D images and/or 3D image volumes. In other scientific fields, such as oncology or geology, dynamical systems cannot be studied directly in the time domain because the time periods are too long for experimental measurements. Other examples from medicine include electroencephalogram or postural sway recordings and their analyses. Cardiac autonomic neuropathy is an example of a neuropathology that manifests as an arrhythmia and therefore can be identified using linear or nonlinear 1D signal analysis. Therefore, the electrocardiogram itself or beat-to-beat intervals can be successfully investigated by nonlinear 1D signal analysis. The rhythm of the human heart, for example, is a consequence of the nonlinear interaction of electrical excitations of a huge number of cardiac muscle cells that are modulated by the autonomic nervous system via a cardiac pacemaker. Physiological processes, such as phenomena in nature, are complex systems. Recently, the Nobel Prize in Physics 2021 was awarded for research on complex systems with a focus on climate and climate change. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Ĭompeting interests: The authors have declared that no competing interests exist.Ĭomplex systems arise in nature through nonlinear and often repetitive interactions of physical parameters. FLS was supported by a grant from the Health Research Council of New Zealand (HRC 20/1126). IA is grateful for the support of the Ministry of Research, Innovation and Digitization (CNCS/CCCDI-UEFISCDI PN-III-P2-2.-0084). This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.ĭata Availability: All relevant data are within the paper.įunding: The authors acknowledge the following organizations and programs: MAR acknowledges the Austrian Science Fund (FWF P34437). Received: JAccepted: SeptemPublished: October 5, 2023Ĭopyright: © 2023 Ahammer et al. PLoS ONE 18(10):Įditor: Mohamed Hammad, Menoufia University, EGYPT (2023) ComsystanJ: A collection of Fiji/ImageJ2 plugins for nonlinear and complexity analysis in 1D, 2D and 3D. Future enhancements of the project will include the implementation of parallel computing for image stacks and volumes and the integration of artificial intelligence methods to improve feature recognition and parameter calculation.Ĭitation: Ahammer H, Reiss MA, Hackhofer M, Andronache I, Radulovic M, Labra-Spröhnle F, et al. ComsystanJ includes effective surrogate analysis in all dimensions to validate the features calculated by the different algorithms. ComsystanJ plugins are macro recordable and are maintained as open-source software. It is based on the framework of the open-source image processing software Fiji and ImageJ2. ComsystanJ combines already known algorithms and newer methods for generalizable analysis of 1D signals, 2D images and 3D volume data including the generation of data sets such as signals and images for testing purposes. It is platform independent, end-user friendly and extensible. We are therefore introducing ComsystanJ, a novel and user-friendly software suite, providing a comprehensive set of plugins for complex systems analysis, without the need for prior programming knowledge. Typically, evaluations can be cumbersome, necessitating specialized tools. The drawback of these complexity quantities is that their definitions are not always mathematically exact and computational algorithms provide estimates rather than exact values. These systems can be characterized by physical quantities such as entropy, information, chaoticity or fractality rather than classical quantities such as time, velocity, energy or temperature. Complex systems such as the global climate, biological organisms, civilisation, technical or social networks exhibit diverse behaviours at various temporal and spatial scales, often characterized by nonlinearity, feedback loops, and emergence.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |