Santa Maria da Feira, Aveiro, Portugal
I became passionate about programming, data science and machine learning. It began in 2013 with my Master in Medical Physics developing a classifier (SVM) for gastroenterological examinations of Barret's oesophagus using DSIFT features. In 2014, I became a Medical Physicist at Instituto Português de Oncologia do Porto (IPO-Porto). I regularly perform quality control procedures on ionizing radiation-emitting equipment. I am also a researcher at Centro de Investigação do IPO-Porto (CI-IPOP), participating actively in several projects. Since then, I have improved my programming skills (mainly python). Developed scripts for task optimization. Built web applications with Django. Performed image registration and visualization.Applied image processing techniques, segmentation and computer vision. Some libraries I feel comfortable with are: NumPy, pandas, scikit-learn, scikit-image, OpenCV, PyTorch, PyQt5 and Django. Also, Matplotlib and seaborn for visualization and VTK, ITK, SimpleITK and Pydicom for medical images (DICOM). In 2020, I enrolled on the Doctoral Program in Biomedical Engineering (PRODEB) at Faculdade de Engenharia da Universidade do Porto (FEUP). I am currently developing a framework to assess the effectiveness of radiotherapy treatments for prostate cancer. To do so, I am using machine learning methods with radiomics to build models for CT and CBCT and also deep learning for prostate and organs at risk segmentation. I have been actively publishing and presenting work in the field.
Implement quality control procedures on radiotherapy and radiology equipment, which implies data analysis, building regression models and applying tolerance levels. Developed and deployed 2 web applications (Django - Python + SQLite3) one for for daily input and monitoring of linear accelerators' dose rates with graphical visualization and another as an inventory tracking system (barcodes) for personal x-ray protective equipmen. Optimize image processing procedures and reports and manage personal dosimetry logistics.
Performed annual quality control procedures on fluoroscopy, mammography and CT equipment at IPO-Porto, supervised by a Medical Physics Expert. Optimized adult and pediatric CT protocols by adjusting automatic current modulation parameters reducing the dose to patients by about 20%. Developed python scripts to extract DICOM tags from medical images (Big Data) and conducted computations, analyses and visualizations. Collaborated in the logistics of personal dosimetry of 400 controlled professionals at the institution.
Provided information about exhibits. Conducted guided tours to groups of up to 100 visitors. Participated in the organization of 2 workshops at the museum. Managed visiting hours and appointments.