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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

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Publications

2020

3D Digital Breast Cancer Models with Multimodal Fusion Algorithms

Authors
Bessa, S; Gouveia, PF; Carvalho, PH; Rodrigues, C; Silva, NL; Cardoso, F; Cardoso, JS; Oliveira, HP; Cardoso, MJ;

Publication
The Breast

Abstract

2020

A Framework for Fusion of T1-Weighted and Dynamic MRI Sequences

Authors
Teixeira, JF; Bessa, S; Gouveia, PF; Oliveira, HP;

Publication
Lecture Notes in Computer Science - Image Analysis and Recognition

Abstract

2019

REGISTRATION OF BREAST MRI AND 3D SCAN DATA BASED ON SURFACE MATCHING

Authors
Bessa, S; Carvalho, PH; Oliveira, HP;

Publication
2019 IEEE 16TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI 2019)

Abstract
The creation of 3D complete models of the woman breast that aggregate radiological and surface information is a crucial step for the development of surgery planning tools in the context of breast cancer. This requires the registration of interior and surface data of the breast, which has to recover large breast deformations caused by the different poses of the patient during data acquisition and has to deal with the lack of landmarks between both modalities, apart from the nipple. In this paper, the registration of Magnetic Resonance Imaging exams and 3D surface data reconstructed from Kinect (TM) acquisitions is explored using a biomechanical modelling of breast pose transformations combined with a free form deformation to finely match the data. The results are promising, with an average euclidean distance between the matched data of 0.81 +/- 0.09 mm being achieved.

2019

Estimation of Sulfonamides Concentration in Water Based on Digital Colourimetry

Authors
Carvalho, PH; Bessa, S; Silva, ARM; Peixoto, PS; Segundo, MA; Oliveira, HP;

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

Abstract
Overuse of antibiotics is causing the environment to become polluted with them. This is a major threat to global health, with bacteria developing resistance to antibiotics because of it. To monitor this threat, multiple antibiotic detection methods have been developed; however, they are normally complex and costly. In this work, an affordable, easy to use alternative based on digital colourimetry is proposed. Photographs of samples next to a colour reference target were acquired to build a dataset. The algorithm proposed detects the reference target, based on binarisation algorithms, in order to standardise the collected images using a colour correction matrix converting from RGB to XYZ, providing a necessary colour constancy between photographs from different devices. Afterwards, the sample is extracted through edge detection and Hough transform algorithms. Finally, the sulfonamide concentration is estimated resorting to an experimentally designed calibration curve, which correlates the concentration and colour information. Best performance was obtained using Hue colour, achieving a relative standard deviation value of less than 3.5%. © 2019, Springer Nature Switzerland AG.

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

Supervised
thesis

2017

Digital image colorimetry for determination of sulfonamides in water

Author
Paulo Jorge Teixeira Silva

Institution
UP-FEUP

2017

Multimodal Breast Image Registration: Mapping MRI and Surface Data

Author
Pedro Henrique Moreira Queirós Carvalho

Institution
UP-FEUP

2017

Breast Modelling Towards an Educational Tool for Breast Cancer Surgeons

Author
Daniela do Vale Afonso

Institution
UP-FEUP