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About

About

I received the MSc. in Bioengineering - Biomedical Engineering,  from the Faculty of Engineering of University of Porto (FEUP), Portugal, in March, 2016.

Early in my undergraduate years, I interned at National Institute of Biomedical Engineering (INEB), contributing in the NeurOn project - a project founded by FCT to conceive a new approach for regeneration and functional recovery of spinal cord injury. Here, I discovered my interest of promoting research through the use image analysis as a tool to obtain results in a faster, more reliable and less subjective way.

The leapt for medical image analysis came with the opportunity to join the Breast Cancer Survey (BCS) project, a project in a consortium of FEUP, Coimbra University (UC), Portuguese League Against Cancer (LPCC) and Emílio Azevedo Campos.SA (EAC.SA),  which aimed at developing automatic modules of screening and diagnosis of breast cancer to be implemented on PACS.

Currently, I am a PhD student in the informatics joint programme MAPi, a member of Visual Computing and Machine Learning (VCMI) and Breast Research Groups at INESC TEC, and a collaborator in the project BCCT.plan.

My main research interests are image analysis, machine learning and decision support systems, particularly in the area of breast cancer. 

Interest
Topics
Details

Details

001
Publications

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

European questionnaire on health literacy-(HLS-EU-PT) in a sample of pregnant women

Authors
Ferreira, M; Neto, S; Amaral, O; Duarte, J; Pedro, AR;

Publication
REVISTA ROL DE ENFERMERIA

Abstract
INTRODUCTION AND OBJECTIVES. The knowledge and skills that enable pregnant women to adopt healthy lifestyles is broad and complex. In addition to factual knowledge, the adoption of health behaviours also implies a set of emotional, cognitive and behavioural skills that allow the use of this knowledge in the context of pregnancy. METHODOLOGY. Cross-sectional, quantitative, descriptive-correlational study with non-probabilistic, intentional sample by convenience (n = 404 pregnant women) with a mean age of 32 years. They answered the sociodemographic, obstetrical and HLS-EU-PT questionnaire (National School of Public Health, 2014). Following the methodology used in the European Survey, four ways of dealing with relevant health information were recognized. RESULTS AND DISCUSSION. Overall, 36.9% of pregnant women presented a problematic level of health literacy, 40.1%, 39.9% and 38.4%, a sufficient level of health literacy in the area of Health Care, Disease Prevention and Health Promotion, respectively. The factorial analysis demonstrates the validity of its framework. The alpha values of the items are above 0.9.The correlations between the different domains and the overall value are all positive and above 0.8. All dimensions of the scale correlate with each other in a statistically significant way, with values for the different domains. The split-half coefficient was alpha = 0.939 in the first half and alpha = 0.930 in the second half. CONCLUSIONS. The results of the present study support the psychometric adequacy of the European Questionnaire on Health Literacy - (HLS-EU-PT) for the population of pregnant women, indicating that it could be used in future trials.

2017

Prediction of Breast Deformities: A Step Forward for Planning Aesthetic Results After Breast Surgery

Authors
Bessa, S; Zolfagharnasab, H; Pereira, E; Oliveira, HP;

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

Abstract
The development of a three-dimensional (3D) planing tool for breast cancer surgery requires the existence of proper deformable models of the breast, with parameters that can be manipulated to obtain the desired shape. However, modelling breast is a challenging task due to the lack of physical landmarks that remain unchanged after deformation. In this paper, the fitting of a 3D point cloud of the breast to a parametric model suitable for surgery planning is investigated. Regression techniques were used to learn breast deformation functions from exemplar data, resulting in comprehensive models easy to manipulate by surgeons. New breast shapes are modelled by varying the type and degree of deformation of three common deformations: ptosis, turn and top-shape. © Springer International Publishing AG 2017.

2017

Registration of Breast Surface Data Before and After Surgical Intervention

Authors
Bessa, S; Oliveira, HP;

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

Abstract
Surgery planing of breast cancer interventions is gaining importance among physicians, who recognize value in discussing the possible aesthetic outcomes of surgery with patients. Research is been propelled to create patient-specific breast models, but breast image registration algorithms are still limited, particularly for the purpose of matching pre- and post-surgical data of patient’s breast surfaces. Yet, this is a fundamental task to learn prediction models of breast healing process after surgery. In this paper, a coarse-to-fine registration strategy is proposed to match breast surface data acquired before and after surgery. Methods are evaluated in their ability to register surfaces in an anatomical reliable way, and results suggest proper alignment adequated to be used as input to train deformable models. © Springer International Publishing AG 2017.

Supervised
thesis

2017

Breast Modelling Towards an Educational Tool for Breast Cancer Surgeons

Author
Daniela do Vale Afonso

Institution
UP-FEUP

2017

Multimodal Breast Image Registration: Mapping MRI and Surface Data

Author
Pedro Henrique Moreira Queirós Carvalho

Institution
UP-FEUP

2017

Digital image colorimetry for determination of sulfonamides in water

Author
Paulo Jorge Teixeira Silva

Institution
UP-FEUP