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About

About

I’m an Assistant Professor at the University of Trás-os-Montes and Alto Douro (UTAD), Portugal since 1996 and I teach  Networks and Security. I graduated in 1993 and started working at STCP, the Public Transport's operator of Porto. I finish my master's thesis in 1998, and obtained my doctorate in 2005, in the area of computer vision related to control of automated guided vehicles.  I’m a member of Centre for Biomedical Engineering Research (C-BER), in the research center INESC TEC since 2014. My investigation is in Electrical Engineering, Electronics & Computers, with a particular focus in machine learning and biomedical image processing.

Interest
Topics
Details

Details

Publications

2018

Learning Lung Nodule Malignancy Likelihood from Radiologist Annotations or Diagnosis Data

Authors
Goncalves, L; Novo, J; Cunha, A; Campilho, A;

Publication
Journal of Medical and Biological Engineering

Abstract

2018

A Deep Learning Approach for Red Lesions Detection in Video Capsule Endoscopies

Authors
Coelho, P; Pereira, A; Leite, A; Salgado, M; Cunha, A;

Publication
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Abstract
The wireless capsule endoscopy has revolutionized early diagnosis of small bowel diseases. However, a single examination has up to 10 h of video and requires between 30–120 min to read. Computational methods are needed to increase both efficiency and accuracy of the diagnosis. In this paper, an evaluation of deep learning U-Net architecture is presented, to detect and segment red lesions in the small bowel. Its results were compared with those obtained from the literature review. To make the evaluation closer to those used in clinical environments, the U-Net was also evaluated in an annotated sequence by using the Suspected Blood Indicator tool (SBI). Results found that detection and segmentation using U-Net outperformed both the algorithms used in the literature review and the SBI tool. © 2018, Springer International Publishing AG, part of Springer Nature.

2018

Towards modern cost-effective and lightweight Augmented Reality setups

Authors
Pádua, L; Adão, T; Narciso, D; Cunha, A; Magalhães, L; Peres, E;

Publication
Virtual and Augmented Reality: Concepts, Methodologies, Tools, and Applications

Abstract
Augmented Reality (AR) has been widely used in areas such as medicine, education, entertainment and cultural heritage to enhance activities that include (but are not limited to) teaching, training and amusement, through the completion of the real world with viewable and usually interactive virtual data (e.g. 3D models, geo-markers and labels). Despite the already confirmed AR benefits in the referred areas, many of the existing AR systems rely on heavy and obsolete hardware bundles composed of several devices and numerous cables that usually culminate in considerably expensive solutions. This issue is about to be tackled through the recent technological developments which currently enable the production of small-sized boards with remarkable capabilities - such as processing, visualization and storage - at relatively low prices. Following this line of reasoning, this paper proposes and compares five different multi-purpose AR mobile units, running Windows or Android operating systems, having in mind low-cost and lightweight requirements and different levels of immersion: a laptop computer, two tablets, a smartphone and smartglasses. A set of tests was carried out to evaluate the proposed unit performance. Moreover, a set of users' assessments was also conducted, highlighting an overall acceptance regarding the use of the proposed units in AR applications. This paper is an extension of a previous work (Pádua et al., 2015) in which a conceptual architecture for mobile units - complying with AR requirements (including visualization, processing, location and communication) for indoor or outdoor utilization - was presented, along with a shorter set of lightweight and cost-effective AR mobile units and respective performance tests. © 2018, IGI Global.

2018

Towards an Automatic Lung Cancer Screening System in Low Dose Computed Tomography

Authors
Aresta, G; Araújo, T; Jacobs, C; Ginneken, Bv; Cunha, A; Ramos, I; Campilho, A;

Publication
Image Analysis for Moving Organ, Breast, and Thoracic Images - Third International Workshop, RAMBO 2018, Fourth International Workshop, BIA 2018, and First International Workshop, TIA 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16 and 20, 2018, Proceedings

Abstract

2017

Detection of juxta-pleural lung nodules in computed tomography images

Authors
Aresta, G; Cunha, A; Campilho, A;

Publication
Medical Imaging 2017: Computer-Aided Diagnosis

Abstract

Supervised
thesis

2017

Desenvolvimento de uma aplicação android para o Jardim Botanico da UTAD

Author
João Carlos Trindade Moreira

Institution
UTAD

2017

Visual odometer on videos of endoscopic capsules (VEC)

Author
Gil Martins Pinheiro

Institution
UTAD

2017

Deteção e segmentação de sangramentos em imagens gastrointestinais de cápsulas endoscópicas

Author
Paulo Jorge Simões Coelho

Institution
UTAD

2017

Detection of lung nodules in computed tomography images

Author
Guilherme Moreira Aresta (aluno FEUP)

Institution
UTAD

2016

Aplicações de ajuda em Smartphones

Author
Evandro Machado Cunha

Institution
UTAD