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Apresentação

Centro de Investigação em Engenharia Biomédica

No C-BER os nossos objetivos vão desde a criação de conhecimento interdisciplinar que permita a inovação e a transferência de tecnologia com impacto económico até ao desenvolvimento de produtos, ferramentas e métodos para a prevenção e deteção precoce de diferentes tipos de doenças, problemas relacionados com o envelhecimento, reabilitação humana, fisioterapia ou avaliação funcional.

Pretendemos ainda contribuir para o desenvolvimento de neuro-tecnologias avançadas na fronteira entre a engenharia e a neurologia, assim como promover parcerias estratégicas com parceiros clínicos, institutos de investigação e fomentar a cooperação internacional.

Desenvolvemos investigação em três áreas distintas: Imagem Biomédica, Bioinstrumentação e Neuroengenharia.

Últimas Notícias
Redes de Sistemas inteligentes

E-book entre os mais descarregados da SpringerLink em 2016

O e-book “Image Analysis and Recognition”, do coordenador do Centro de Investigação em Engenharia Biomédica (C-BER) Aurélio Campilho, está entre os 25% mais descarregados da SpringerLink eBook Collection no ano de 2016.

08 agosto 2017

Redes de Sistemas inteligentes

Inovação na classificação do diagnóstico do cancro da mama publicada pelo INESC TEC

O cancro da mama é atualmente uma das principais causas de morte devido a doença oncológica a nível mundial. Como tal, o diagnóstico e o tratamento precoces são essenciais para combater a progressão da doença e reduzir a sua taxa de mortalidade.

18 junho 2017

Trabalho de investigadores INESC TEC sobre deteção de retinopatia diabética em destaque no Japão

Pedro Costa, CMU-Portugal, e Aurélio Campilho, Coordenador do Centro de Investigação em Engenharia Biomédica (CBER) do INESC TEC, apresentaram um artigo na International Conference on Image Analysis Applications (IAPR MVA 2017), que foi alvo de algumas referências de destaque.

24 maio 2017

Investigadores do INESC TEC lideram descoberta que ajuda à identificação de subestruturas cerebrais com relevância neurocirúrgica

Uma equipa liderada por investigadores do INESC TEC desenvolveu métodos de neuro-computação que permitiram identificar subestruturas cerebrais com diferentes perfis de conectividade com a parte motora e não-motora do ser humano e que, por isso, podem ajudar as equipas médicas a melhorar os alvos dos procedimentos neurocirúrgicos de estimulação cerebral profunda para obter melhores resultados em doenças como a distonia ou a doença de Parkinson.

30 janeiro 2017

Artigo do INESC TEC nomeado “esteemed paper” em revista internacional

O artigo "Optic disc segmentation using the sliding band filter”, da autoria de Aurélio Campilho e Ana Maria Mendonça, investigadores do Centro de Investigação em Engenharia Biomédica (C-BER), e de Behdad Dashtbozorg, na altura da publicação estudante do Programa Doutoral em Engenharia Eletrotécnica e de Computadores da Faculdade de Engenharia da Universidade do Porto (FEUP), foi nomeado esteemed paper (artigo de valor) pela revista internacional Computers in Biology and Medicine Journal.

07 julho 2016

Tópicos de interesse
013

Projetos Selecionados

LNDetector

Sistema Automático de Deteção, Segmentação e Classificação de Nódulos Pulmonares em Imagens Tomografia Computadorizada

2016-2019

SCREEN-DR

Plataforma de Análise de Imagem e de Aprendizagem Computacional para a Inovação no Rastreio da Retinopatia Diabética

2016-2020

Bio-Early

Projeto Vital Sticker no âmbito do Contrato Programa

2015-2017

NanoStima-RL5

NanoSTIMA - Advanced Methodologies for Computer-Aided Detection and Diagnosis

2015-2018

NanoStima-RL1

NanoSTIMA - Macro-to-Nano Human Sensing Technologies

2015-2018

SMILES

TEC4Growth - RL SMILES - Smart, Mobile, Intelligent and Large scale Sensing and analytics

2015-2018

VR2Market

VR2Market: Desenvolvimento dum Produto para Monitorização Móvel e Vestível da Saúde de Profissionais de Primeira Resposta e de outras Profissões de Risco

2014-2018

STePMotion

Componentes espácio-temporais do processamento de informação motora e sensorial

2014-2015

EcoDrive

Condução Ecológica e Gestão Inteligente de Frotas

2014-2015

Re-Learning

Re-aprendizagem motora através do uso da fusão de informação de sensores

2014-2015

VitalResponder2

Gestão inteligente de eventos críticos de stress, fadiga e intoxicação pelo fumo no combate a fogos florestais

2013-2015

ASD-MD

Doenças do Movimento na Perturbação do Espetro Autista

2013-2015

HERMES

Sistema de interactividade entre consumidores de conteúdos digitais

2013-2015

Equipa
003

Laboratórios

Laboratório de Imagem Biomédica

Laboratório Avançado de Neuroengenharia e Deteção Humana

Laboratório de BioInstrumentação

Publicações

C-BER Publicações

Ler todas as publicações

2018

Skin temperature of the foot: A comparative study between familial amyloid polyneuropathy and diabetic foot patients

Autores
Seixas, A; do Carmo Vilas Boas, M; Carvalho, R; Coelho, T; Ammer, K; Vilas Boas, JP; Vardasca, R; Cunha, JPS; Mendes, J;

Publicação
Lecture Notes in Computational Vision and Biomechanics

Abstract
Skin temperature regulation is dependant of the autonomic nervous system function, which may be impaired in patients with neuropathy. Studies reporting thermographic assessment of patients with established diagnosis of Diabetic Foot (DF) are scarce but this information is completely absent in patients suffering from Transthyretin Familial Amyloid Polyneuropathy (TTR-FAP). The aim of this study is to compare skin temperature distribution in patients with DF and TTR-FAP. Thermograms of the dorsal and plantar surfaces were compared. Skin temperature was higher in the diabetic foot group and differences were statistically significant (p < 0.05) in both regions of interest. © 2018, Springer International Publishing AG.

2018

Retinal image quality assessment by mean-subtracted contrast-normalized coefficients

Autores
Galdran, A; Araújo, T; Mendonça, AM; Campilho, A;

Publicação
Lecture Notes in Computational Vision and Biomechanics

Abstract
The automatic assessment of visual quality on images of the eye fundus is an important task in retinal image analysis. A novel quality assessment technique is proposed in this paper. We propose to compute Mean-Subtracted Contrast-Normalized (MSCN) coefficients on local spatial neighborhoods of a given image and analyze their distribution. It is known that for natural images, such distribution behaves normally, while distortions of different kinds perturb this regularity. The combination of MSCN coefficients with a simple measure of local contrast allows us to design a simple but effective retinal image quality assessment algorithm that successfully discriminates between good and low-quality images, while delivering a meaningful quality score. The proposed technique is validated on a recent database of quality-labeled retinal images, obtaining results aligned with state-of-the-art approaches at a low computational cost. © 2018, Springer International Publishing AG.

2018

Supervised learning methods for pathological arterial pulse wave differentiation: A SVM and neural networks approach

Autores
Paiva, JS; Cardoso, J; Pereira, T;

Publicação
INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS

Abstract
Objective: The main goal of this study was to develop an automatic method based on supervised learning methods, able to distinguish healthy from pathologic arterial pulse wave (APW), and those two from noisy waveforms (non-relevant segments of the signal), from the data acquired during a clinical examination with a novel optical system. Materials and methods: The APW dataset analysed was composed by signals acquired in a clinical environment from a total of 213 subjects, including healthy volunteers and non-healthy patients. The signals were parameterised by means of 39 pulse features: morphologic, time domain statistics, cross-correlation features, wavelet features. Multiclass Support Vector Machine Recursive Feature Elimination (SVM RFE) method was used to select the most relevant features. A comparative study was performed in order to evaluate the performance of the two classifiers: Support Vector Machine (SVM) and Artificial Neural Network (ANN). Results and discussion: SVM achieved a statistically significant better performance for this problem with an average accuracy of 0.9917 +/- 0.0024 and a F-Measure of 0.9925 +/- 0.0019, in comparison with ANN, which reached the values of 0.9847 +/- 0.0032 and 0.9852 +/- 0.0031 for Accuracy and F-Measure, respectively. A significant difference was observed between the performances obtained with SVM classifier using a different number of features from the original set available. Conclusion: The comparison between SVM and NN allowed reassert the higher performance of SVM. The results obtained in this study showed the potential of the proposed method to differentiate those three important signal outcomes (healthy, pathologic and noise) and to reduce bias associated with clinical diagnosis of cardiovascular disease using APW.

2018

3D mapping of choroidal thickness from OCT B-scans

Autores
Faria, SP; Penas, S; Mendonça, L; Silva, JA; Mendonça, AM;

Publicação
Lecture Notes in Computational Vision and Biomechanics

Abstract
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.

2017

Analysis and quantification of upper-limb movement in motor rehabilitation after stroke

Autores
Silva, RM; Sousa, E; Fonseca, P; Pinheiro, AR; Silva, C; Correia, MV; Mouta, S;

Publicação
Biosystems and Biorobotics

Abstract
It is extremely difficult to reduce the relations between the several body parts that perform human motion to a simplified set of features. Therefore, the study of the upper-limb functionality is still in development, partly due to the wider range of actions and strategies for motor execution. This, in turn, leads to inconsistent upper-limb movement parameterization. We propose a methodology to assess and quantify the upper-limb motor execution. Extracting key variables from different sources, we intended to quantify healthy upper-limb movement and use these parameters to quantify motor execution during rehabilitation after stroke. In order to do so, we designed an experimental setup defining a workspace for the execution of the action recording kinematic data. Results reveal an effect of object and instruction on the timing of upper-limb movement, indicating that the spatiotemporal analysis of kinematic data can be used as a quantification parameter for motor rehabilitation stages and methods. © Springer International Publishing AG 2017.

Factos & Números

6Docentes do Ensino Superior

2017

2Contratados de I&D

2017

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