CNC. IBILI

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Publications

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”.

2022Journal article

Restricted access

The method of fundamental solutions for the direct elastography problem in the human retina

Publication . Barbeiro, Sílvia; Serranho, Pedro

This paper addresses the numerical simulation of the mechanical waves propagation and induced displacements in the human retina, for the elastography imaging modality. In this way, we use a model for the human eye and numerically approximate the propagation of time-harmonic acoustic waves through the different media of the eye and the respective elastic excitation in the retina, through a layered representation approach based on the method of fundamental solutions. We present numerical results showing the feasibility of the method.

2020Book part

Restricted access

Retinal aging in 3× Tg-AD mice model of Alzheimer's disease

Publication . Guimarães, Pedro; Serranho, Pedro; Martins, João; Moreira, Paula I.; Ambrósio, António Francisco; Castelo-Branco, Miguel; Bernardes, Rui

The retina, as part of the central nervous system (CNS), can be the perfect target for in vivo, in situ, and noninvasive neuropathology diagnosis and assessment of therapeutic efficacy. It has long been established that several age-related brain changes are more pronounced in Alzheimer’s disease (AD). Nevertheless, in the retina such link is still under-explored. This study investigates the differences in the aging of the CNS through the retina of 3×Tg-AD and wild-type mice. A dedicated optical coherence tomograph imaged mice’s retinas for 16 months. Two neural networks were developed to model independently each group’s ages and were then applied to an independent set containing images fromboth groups. Our analysis shows amean absolute error of 0.875±1.1×10−2 and 1.112 ± 1.4 × 10−2 months, depending on training group. Our deep learning approach appears to be a reliable retinal OCT aging marker. We show that retina aging is distinct in the two classes: the presence of the three mutated human genes in the mouse genome has an impact on the aging of the retina. For mice over 4 months-old, transgenic mice consistently present a negative retina age-gap when compared to wildtype mice, regardless of training set. This appears to contradict AD observations in the brain. However, the ‘black-box” nature of deep-learning implies that one cannot infer reasoning. We can only speculate that some healthy age-dependent neural adaptations may be altered in transgenic animals.

2022Journal article

Open access

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.

2022Journal article

Open access