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Currently, Parkinson's Disease (PD) is diagnosed primarily based on symptoms by experts clinicians. Neuroimaging exams represent an important tool to confirm the clinical diagnosis. Among them, Brain Parenchyma Sonography (BPS) is used to evaluate the hyperechogenicity of Substantia Nigra (SN), found in more than 90% of PD patients. In this article, we exploit a new dataset of BPS images to investigate an automatic segmentation approach for SN that can increase the accuracy of the exam and its practicability in clinical routine. This study achieves state-of-the-art performance in SN segmentation of BPS images. Indeed, it is found that the modified U-Net network scores a Dice coefficient of 0.859 ± 0.037. The results presented in this study demonstrate the feasibility and usefulness of SN automatic segmentation in BPS medical images, to the point that this study can be considered as the first stage of the development of an end-to-end CAD (Computer Aided Detection) system. Furthermore, the used dataset, which will be further enriched in the future, has proven to be very effective in supporting the training of CNNs and may pave the way for future studies in the field of CAD applied to PD. [ABSTRACT FROM AUTHOR]

This study presents an application that estimates all possible paths within an urban environment and proposes the optimal one according to objective criteria and individualized options. The application grounds its functionality on a Cellular Automaton (CA) that models the area of interest and provides the rule that activates the processing of input data. The model incorporates the term walkability as a discrete magnitude that integrates qualitative features of pedestrian mobility. The proposed application fosters sustainable forms of movement at a local level that undoubtedly improves the human physical status and upgrades civilian living conditions. In the context of this paper, we provide a thorough description of the operational principles of the model, and we test its validity by applying it in Xanthi, a medium size city located in northeastern Greece. Finally, we describe variants of the initial scenario to demonstrate the sensibility of the model in external assessments as well as its resilience in biasing manipulations. [ABSTRACT FROM AUTHOR]