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About

About

João Teixeira was born in Porto, Portugal, in 1991. He received his M.Sc. in Electrical and Computers Engineering at the Faculty of Engineering of University of Porto, Portugal, in 2014. In 2014, he started his Ph.D. studies at Faculty of Sciences, University of Porto, Portugal, under the joint program in Informatics (MAP-i). He has been working since 2015 as a researcher at INESC TEC, an R&D institute affiliated to University of Porto, in the Visual Computing and Machine Intelligence Group (VCMI), and the Breast Research Group. João Teixeira has a standing collaboration and has been consulting for a R&D department of the Faculty of Medicine (FMUP), the Center for Health Technology and Services Research (CINTESIS), since 2013.
His main research interests include computer vision, image processing, signal processing, with particular interest in medical applications (Breast cancer and Respiratory conditions) and m-health initiatives.

For further information please consult the CV:
http://www.degois.pt/visualizador/curriculum.jsp?key=3395739315417314 

Interest
Topics
Details

Details

002
Publications

2019

School mobility management case study: German School of Oporto (Deutsche Schule zu Porto)

Authors
Teixeira, JF; Silva, C; Neves, JV;

Publication
CASE STUDIES ON TRANSPORT POLICY

Abstract
In recent years we have witnessed an increase in the number of parents driving children to school in several developed countries, with increases of, for instance, 35% in the USA, 12% in the United Kingdom and 44% in Australia. These changes have been responsible for several negative impacts ranging from the general increase of Greenhouse Gas emissions and traffic congestion, to more individualized impacts on the health and safety of students. In this context, special attention has been given to introducing mobility management strategies for school trips aimed at creating healthier and more sustainable travel behaviours in students and their parents. Regardless of the vast research, the knowledge on the effects of mobility management measures is still limited, particularly for the soft measures aimed at voluntary travel behaviour change. This paper aims to assess the effects of soft mobility management measures in the travel patterns of pre-university students, namely, Carpooling, Park & Stride, School Route Map, Safe Parking Banners, and the Tree of Life Contest. The assessment of such effects is developed in a particular context, in which the school implementing the measures does not benefit from any institutional or financial support. The research followed the implementation phase during one semester using before and after surveys to assess effects on travel behaviour. This research displayed the difficulties of a school lacking funding and technical expertise in successfully implementing soft mobility measures when compared with other case-studies where government support was provided. Although a direct influence on the mobility patterns due to the implemented measures was not clear, the results suggest that they were able to create awareness and intentions of change, strengthening the role of such measures in increasing sustainable mobility within the student community.

2018

A Regression Model for Predicting Shape Deformation after Breast Conserving Surgery

Authors
Zolfagharnasab, H; Bessa, S; Oliveira, SP; Faria, P; Teixeira, JF; Cardoso, JS; Oliveira, HP;

Publication
Sensors

Abstract

2018

Three-dimensional planning tool for breast conserving surgery: A technological review

Authors
Oliveira, SP; Morgado, P; Gouveia, PF; Teixeira, JF; Bessa, S; Monteiro, JP; Zolfagharnasab, H; Reis, M; Silva, NL; Veiga, D; Cardoso, MJ; Oliveira, HP; Ferreira, MJ;

Publication
Critical Reviews in Biomedical Engineering

Abstract
Breast cancer is one of the most common malignanciesaffecting women worldwide. However, despite its incidence trends have increased, the mortality rate has significantly decreased. The primary concern in any cancer treatment is the oncological outcome but, in the case of breast cancer, the surgery aesthetic result has become an important quality indicator for breast cancer patients. In this sense, an adequate surgical planning and prediction tool would empower the patient regarding the treatment decision process, enabling a better communication between the surgeon and the patient and a better understanding of the impact of each surgical option. To develop such tool, it is necessary to create complete 3D model of the breast, integrating both inner and outer breast data. In this review, we thoroughly explore and review the major existing works that address, directly or not, the technical challenges involved in the development of a 3D software planning tool in the field of breast conserving surgery. © 2018 by Begell House, Inc.

2018

Automatic Quality Assessment of Smart Device Microphone Spirometry

Authors
Pinho, B; Almeida, R; Jácome, C; P. Teixeira, J; Amaral, R; Lopes, F; Jacinto, T; Guedes, R; Pereira, M; Gonçalves, I; A. Fonseca, J;

Publication
Proceedings of the 8th International Joint Conference on Pervasive and Embedded Computing and Communication Systems

Abstract

2017

Multi-modal Complete Breast Segmentation

Authors
Zolfagharnasab, H; Monteiro, JP; Teixeira, JF; Borlinhas, F; Oliveira, HP;

Publication
Pattern Recognition and Image Analysis - 8th Iberian Conference, IbPRIA 2017, Faro, Portugal, June 20-23, 2017, Proceedings

Abstract
Automatic segmentation of breast is an important step in the context of providing a planning tool for breast cancer conservative treatment, being important to segment completely the breast region in an objective way; however, current methodologies need user interaction or detect breast contour partially. In this paper, we propose a methodology to detect the complete breast contour, including the pectoral muscle, using multi-modality data. Exterior contour is obtained from 3D reconstructed data acquired from low-cost RGB-D sensors, and the interior contour (pectoral muscle) is obtained from Magnetic Resonance Imaging (MRI) data. Quantitative evaluation indicates that the proposed methodology performs an acceptable detection of breast contour, which is also confirmed by visual evaluation. © Springer International Publishing AG 2017.

Supervised
thesis

2017

Automated Detection of Bone structur keypoints on Magnetic Resonance Imaging - Sternum and Clavicules

Author
Beatriz Gonçalves Rocha

Institution
UP-FEUP

2017

Automated Detection of Anatomical structure keypoints on medical imaging algorithms directed for X-Ray Mammography

Author
Hugo Manuel Soares Oliveira

Institution
UP-FCUP

2015

Conceção e desenvolvimento de uma aplicação móvel para monitoramento da tosse em crianças

Author
José Manuel da Silva Fernandes

Institution
UP-FMUP