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Ferreira, Hugo Rafael

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  • Shedding light on early central nervous system changes for Alzheimer’s disease through the retina: an animal study
    Publication . Bernardes, Rui; Ferreira, Hugo; Guimarães, Pedro; Serranho, Pedro
    The World Health Organization (WHO) 2015 projections estimated 75.6 million people living with dementia in 2030, an update from the 66 million estimated in 2013. These figures account for all types of dementia, but Alzheimer’s disease stands out as the most common estimated type, representing 60% to 80% of the cases. An increasing number of research groups adopted the approach of using the retina as a window to the brain. Besides being the visible part of the central nervous system, the retina is readily available through non-invasive imaging techniques such as optical coherence tomography (OCT). Moreover, cumulative evidence indicates that neurodegenerative diseases can also affect the retina. In the work reported herein, we imaged the retina of wild-type and the triple-transgenic mouse model of Alzheimer’s disease, at the ages of one-, two-, three-, four-, eight-, twelve- and sixteen-months-old, by OCT and segmented gathered data using a developed convolutional neural network into distinct layers. Group differences through texture analysis of computed fundus images for five layers of the retina, normative retinal thickness data throughout the observation period of the ageing mice, and findings related to the estimation of the ageing effect of the human genes present in the transgenic group, as well as the classification of individual fundus images through convolutional neural networks, will be presented and thoroughly discussed in the Special Session on ”New Developments in Imaging for Ocular and Neurodegenerative Disorders”.
  • Texture analysis and Its applications in biomedical imaging: a survey
    Publication . Khaksar Ghalati, Maryam; Nunes, Ana; Ferreira, Hugo; Serranho, Pedro; Bernardes, Rui
    Texture analysis describes a variety of image analysis techniques that quantify the variation in intensity and pattern. This paper provides an overview of several texture analysis approaches addressing the rationale supporting them, their advantages, drawbacks, and applications. This survey’s emphasis is in collecting and categorising over five decades of active research on texture analysis.Brief descriptions of different approaches are presented along with application examples. From a broad range of texture analysis applications, this survey’s final focus is on biomedical image analysis. An up-to-date list of biological tissues and organs in which disorders produce texture changes that may be used to spot disease onset and progression is provided. Finally, the role of texture analysis methods as biomarkers of disease is summarised.