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Sobre

Sobre

Sara Oliveira nasceu em Coimbra, Portugal, em 1992.

Obteve o grau de Mestre em Engenharia Biomédica pela Faculdade de Ciências e Tecnologia da Universidade de Coimbra, Portugal, em 2016. Desde 2016 que é bolseira de investigação no INESC TEC, um instituto de I&D afiliado à Universidade do Porto, pertencendo ao grupo Visual Computing and Machine Intelligence Group (VCMI) e ao Breast Research Group. Atualmente, faz parte de um projeto de investigação financiado, BCCT.plan, relacionado com o planeamento do tratamento conservador do cancro da mama. Está também a frequentar o Programa Doutoral em Engenharia Eletrotécnica e de Computadores (PDEEC), na Faculdade de Engenharia da Universidade do Porto.

Os seus principais interesses de investigação incluem visão por computador, processamento de imagem, imagem médica, modelação 3D, machine learning e inteligência artificial.

Tópicos
de interesse
Detalhes

Detalhes

003
Publicações

2018

A Regression Model for Predicting Shape Deformation after Breast Conserving Surgery

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

Publicação
Sensors

Abstract

2018

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

Autores
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;

Publicação
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.

2017

Segmentation of Eye Fundus Images by density clustering in diabetic retinopathy

Autores
Furtado, P; Travassos, C; Monteiro, R; Oliveira, S; Baptista, C; Carrilho, F;

Publicação
2017 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2017

Abstract
Early diagnosis is crucial in Diabetic Retinopathy (DR), to avoid further complications. The disease can be classified into one of two stages (an early stage of non-proliferative and a later stage of proliferative diabetic retinopathy), diagnosed based on existence and quantity of a characteristic set of lesions, such as micro-aneurysms, hemorrhages or exudates, in Eye Fundus Images (EFI). It is therefore important to segment adequately regions of potential lesions, to highlight and classify the lesions and the degree of DR. Density clustering methods are promising candidates to isolate individual lesions, and should be used together with effective techniques for vascular tree removal, feature extraction and classification. In this work we report on our approach, results, tradeoffs and conclusions for segmenting and detecting individual lesions. © 2017 IEEE.

Teses
supervisionadas

2018

Design of a software system for processes improvement in a technology start-up

Autor
Joana Raquel da Silva Rodrigues

Instituição
UP-FEUP