Networked Intelligent Systems

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    ( 2017) Guilherme Moreira Aresta ; António Cunha ; Aurélio Campilho
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    ( 2017) Teresa Finisterra Araújo ; Ana Maria Mendonça ; Aurélio Campilho
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    ( 2017) Ana Maria Mendonça ; Beatriz Remeseiro López ; Dashtbozorg,B ; Aurélio Campilho
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    100 km-Ultralong Raman Fiber Laser using a Distributed Rayleigh Mirror for Sensing Applications
    ( 2012) Manuel Joaquim Marques ; Hugo Fidalgo Martins ; Orlando Frazão
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    2017 Wireless Days, Porto, Portugal, March 29-31, 2017
    ( 2017) Manuel Ricardo ; Campos,Rui ; Ruela,Jose ; Ricardo Morla ; Teixeira,Filipe ; Luís Manuel Pessoa ; Salgado,Henrique
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    250 km ultra long sensor system based on a Fiber Loop Mirror interrogated by an OTDR
    ( 2011) M. Lopez-Amo ; José Manuel Baptista ; José Luís Santos ; Orlando Frazão ; M. Bravo
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    2D computational modeling of optical trapping effects on malaria-infected red blood cells
    ( 2017) Joana Isabel Paiva ; Ribeiro,RSR ; Pedro Jorge ; Carla Carmelo Rosa ; Guerreiro,A ; João Paulo Cunha
    A computational method for optical fiber trapping of healthy and Malariainfected blood cells characterization is proposed. A trapping force relation with the infection stage was found, which could trigger the development of a diagnostic sensor. © OSA 2017.
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    300 km-Ultralong Raman Fiber Lasers using a Distributed Mirror for Sensing Applications
    ( 2011) Manuel Joaquim Marques ; Hugo Fidalgo Martins ; Orlando Frazão
    H. Martins, M. B. Marques, O. Frazão, 300 km-Ultralong Raman Fiber Lasers using a Distributed Mirror for Sensing Applications, Opt. Express, 19 (19), 18149-18154, September 2011.
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    A 3D low-cost solution for the aesthetic evaluation of breast cancer conservative treatment
    ( 2014) Hélder Filipe Oliveira ; Jaime Cardoso ; Magalhães,A ; Cardoso,MJ
    Breast cancer conservative treatment (BCCT) is now the preferred technique for breast cancer treatment. The limited reproducibility of standard aesthetic evaluation methods led to the development of objective methods, such as the software tool Breast Cancer Conservative Treatment.cosmetic results (BCCT.core). Although results are satisfying, there are still limitations concerning complete automation and the inability to measure volumetric information. With the fundamental premise of maintaining the system a low-cost tool, this work studies the incorporation of the Microsoft Kinect sensor in BCCT evaluations. The aim is to enable the automatic joint detection of prominent points, both on depth and RGB images. Afterwards, using those prominent points, it is possible to obtain two-dimensional and volumetric features. Finally, the aesthetic result is achieved using machine learning techniques converted automatically from the set of measures defined. Experimental results show that the proposed algorithm is accurate and robust for a wide number of patients. In addition, comparing with previous research, the procedure for detecting prominent points was automated. © 2013 © 2013 Taylor & Francis.
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    3D lung nodule candidate detection in multiple scales
    ( 2015) Novo,J ; Goncalves,L ; Ana Maria Mendonça ; Aurélio Campilho
    Lung cancer is mainly diagnosed by the identification of malignant nodules in the lung parenchyma. For that purpose, the identification of all the possible structures that could be suspicious of lung nodules became a crucial task in any lung cancer computer aided diagnosis (CAD) system. In this paper, a new approach for lung nodule candidate identification is proposed. This method uses a 3D medialness Hessian-based filtering to identify round shape structures that could be identified as nodules. This technique, that demonstrated its accuracy in lung vesselness extraction, provides clearer candidates than other approaches, providing less response in the presence of noise artifacts and returns a better continuity in vessels, mostly responsible for false positives. That way, they will be better distinguishable from the nodules in posterior analysis. This approach was validated in 120 scans from the LIDC/IDRI image database. They include 212 nodules with diameters in the range 3 mm to 30 mm. The results demonstrate that our approach is capable of identifying most of the nodules and include less false positives than other approaches, facilitating a posterior task for false positive removal.
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    3D mapping of choroidal thickness from OCT B-scans
    ( 2018) Simão Pedro Faria ; Penas,S ; Mendonça,L ; Silva,JA ; Ana Maria Mendonça
    The choroid is the middle layer of the eye globe located between the retina and the sclera. It is proven that choroidal thickness is a sign of multiple eye diseases. Optical Coherence Tomography (OCT) is an imaging technique that allows the visualization of tomographic images of near surface tissues like those in the eye globe. The automatic calculation of the choroidal thickness reduces the subjectivity of manual image analysis as well as the time of large scale measurements. In this paper, a method for the automatic estimation of the choroidal thickness from OCT images is presented. The pre-processing of the images is focused on noise reduction, shadow removal and contrast adjustment. The inner and outer boundaries of the choroid are delineated sequentially, resorting to a minimum path algorithm supported by new dedicated cost matrices. The choroidal thickness is given by the distance between the two boundaries. The data are then interpolated and mapped to an infrared image of the eye fundus. The method was evaluated by calculating the error as the distance from the automatically estimated boundaries to the boundaries delineated by an ophthalmologist. The error of the automatic segmentation was low and comparable to the differences between manual segmentations from different ophthalmologists. © 2018, Springer International Publishing AG.
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    3D Model for Aesthetic Objective Evaluation after Breast Cancer Surgery using Infrared Laser Projector
    ( 2011) Jaime Cardoso ; André T. Magalhaes ; Hélder Filipe Oliveira ; João Soares ; Anténio José Moura ; Maria João Cardoso
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    3D Models for Leg Prothesis - The first step to measure the stub's fitting into a prosthetic device
    ( 2012) Pedro Costa ; Hélder Filipe Oliveira ; Filipe Magalhães ; Frederico Carpinteiro
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    A 3D multimodal approach to precisely locate DBS electrodes in the basal ganglia brain region
    ( 2015) Nádia Moreira Silva ; Rozanski,VE ; João Paulo Cunha
    Deep Brain Stimulation (DBS) is the effective surgical treatment for drug-refractory movement disorders. In order to improve the therapeutic outcome precise anatomic location of electrodes must be achieved. Thus, neurologists can achieve better clinical decisions and take a more careful selection of the best stimulation parameters for DBS. In this paper, we present a system that accurately obtains the 3D positions of DBS electrodes relative to anatomical structures. The latter is based on the segmentation of deep brain structures and on a multimodal imaging approach. In this study, we examined 16 patients undergoing DBS (8 with Parkinson's disease and 8 with dystonia). A 'neuroscientist friendly' graphic user interface (GUI) was designed to support the processing pipeline to precisely detect the electrodes from the DBS lead. Using this system, we obtained the electrodes position and compared them with the ones manually calculated by an experienced physician. The differences observed were less than a voxel size for 89.9% of the cases and the automated procedure takes less 97.5% time than the manual procedure (1min vs 40min). The resulting masks were congruent in shape and position with the corresponding areas in the individuals' space. Using our automatic segmentation pipeline, clinicians save 77% of their time when compared with a manual segmentation (1.20min vs 5.26min). Both structures and electrodes masks were warped to the MNI space in order to provide a common reference space, for the clinical interpretations. © 2015 IEEE.
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    3D Multimodal Visualization of Subdural Electrodes with Cerebellum Removal to Guide Epilepsy Resective Surgery Procedures
    ( 2014) Nádia Moreira Silva ; Rego,R ; João Paulo Cunha
    Patients with medically refractory epilepsy may benefit from surgical resection of the epileptic focus. Subdural electrodes are implanted to accurately locate the seizure onset and locate the eloquent areas to be spared. However, the visualization of the subdural electrodes may be limited by the current methods. The aim of this work was to assist physicians in the localization of subdural electrodes in relation to anatomical landmarks using co-registration methods and by removing the cerebellum from MRI images. Three patients with refractory epilepsy were studied, in whom subdural electrodes were implanted. All electrodes were correctly localized in a 3D view over the cortex and their visualization was improved by the removal of cerebellum. This method promises to be useful in the optimization of the surgical plan.
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    3D Reconstruction of Body Parts Using RGB-D Sensors: Challenges from a Biomedical Perspective
    ( 2014) Costa,P ; Zolfagharnasab,H ; João Pedro Monteiro ; Cardoso,JS ; Hélder Filipe Oliveira
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    A 3D Simulation Framework for Safe Ambient-Assisted Home Care
    ( 2011) José Manuel Torres ; Ricardo Morla ; Rui Moreira ; Pedro Sobral ; Carlos Velasquez ; Christophe Soares
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    5.36 Gbit/s OFDM optical wireless communication link over the underwater channel
    ( 2020) João Henrique Araújo ; Luís Manuel Pessoa ; Henrique Salgado ; Pereira,F ; Joana Santos Tavares ; Kraemer,R ; 7658 ; 4760 ; 296 ; 5686
    An OFDM transmission system is reported based on a directly modulated blue LASER diode, for high bit rate under-water optical communication applications. The 256 subcarriers 16-QAM signal is transmitted over a total distance of 2.4 m underwater with an EVM lower than -28.5 dB for a 250 MHz bandwidth and -16.5 dB for a 2 GHz bandwidth, the BER being lower than the forward error corrector limit. At the maximum bandwidth of 2 GHz a transmission rate of 5.36 Gbit/s is achieved. © 2020 IEEE.
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    802.11 wireless simulation and anomaly detection using HMM and UBM
    ( 2020) Anisa Allahdadidastjerdi ; Ricardo Morla ; Jaime Cardoso ; 5587 ; 3645 ; 3889
    Despite the growing popularity of 802.11 wireless networks, users often suffer from connectivity problems and performance issues due to unstable radio conditions and dynamic user behavior, among other reasons. Anomaly detection and distinction are in the thick of major challenges that network managers encounter. The difficulty of monitoring broad and complex Wireless Local Area Networks, that often requires heavy instrumentation of the user devices, makes anomaly detection analysis even harder. In this paper we exploit 802.11 access point usage data and propose an anomaly detection technique based on Hidden Markov Model (HMM) and Universal Background Model (UBM) on data that is inexpensive to obtain. We then generate a number of network anomalous scenarios in OMNeT /INET network simulator and compare the detection outcomes with those in baseline approaches—RawData and Principal Component Analysis. The experimental results show the superiority of HMM and HMM-UBM models in detection precision and sensitivity.
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    a-GIZO TFT neural modeling, circuit simulation and validation
    ( 2015) Bahubalindruni,PG ; Vítor Grade Tavares ; Barquinha,P ; Manuel Cândido Santos ; Cardoso,N ; de Oliveira,PG ; Martins,R ; Fortunato,E
    Development time and accuracy are measures that need to be taken into account when devising device models for a new technology. If complex circuits need to be designed immediately, then it is very important to reduce the time taken to realize the model. Solely based on data measurements, artificial neural networks (ANNs) modeling methodologies are capable of capturing small and large signal behavior of the transistor, with good accuracy, thus becoming excellent alternatives to more strenuous modeling approaches, such as physical and semi-empirical. This paper then addresses a static modeling methodology for amorphous Gallium-Indium-Zinc-Oxide - Thin Film Transistor (a-GIZO TFT), with different ANNs, namely: multilayer perceptron (MLP), radial basis functions (RBF) and least squares-support vector machine (LS-SVM). The modeling performance is validated by comparing the model outcome with measured data extracted from a real device. In case of a single transistor modeling and under the same training conditions, all the ANN approaches revealed a very good level of accuracy for large- and small-signal parameters (g(m) and g(d)), both in linear and saturation regions. However, in comparison to RBF and LS-SVM, the MLP achieves a very acceptable degree of accuracy with lesser complexity. The impact on simulation time is strongly related with model complexity, revealing that MLP is the most suitable approach for circuit simulations among the three ANNs. Accordingly, MLP is then extended for multiple TFTs with different aspect ratios and the network implemented in Verilog-A to be used with electric simulators. Further, a simple circuit (inverter) is simulated from the developed model and then the simulation outcome is validated with the fabricated circuit response.