Pedro Martins Moreira Neto

Idiomas

Áreas de atuação

Projetos de pesquisa

• 2016 - 2017

  Extracting Lungs from CT Images using Fully Convolutional Networks, Descrição: Analysis of cancer and other pathological diseases, like the interstitial lung diseases (ILDs), is usually possible through Computed Tomography (CT) scans. To aid this, a preprocessing step of segmentation is performed to reduce the area to be analyzed, segmenting the lungs and removing unimportant regions. Generally, complex methods are developed to extract the lung region, also using hand-made feature extractors to enhance segmentation. With the popularity of deep learning techniques and its automated feature learning, we propose a lung segmentation approach using fully convolutional networks (FCNs) combined with fully connected conditional random fields (CRF), employed in many stateof- the-art segmentation works. Aiming to develop a generalized approach, the publicly available datasets from University Hospitals of Geneva (HUG) and VESSEL12 challenge were studied, including many healthy and pathological CT scans for evaluation. Experiments using the dataset individually, its trained model on the other dataset and a combination of both datasets were employed. Dice scores of 98.67% 0.94% for the HUG-ILD dataset and 99.19% 0.37% for the VESSEL12 dataset were achieved, outperforming works in the former and obtaining similar state-of-the-art results in the latter dataset, showing the capability in using deep learning approaches.. , Situação: Concluído; Natureza: Pesquisa. , Alunos envolvidos: Graduação: (1) / Doutorado: (2) . , Integrantes: Pedro Martins Moreira Neto - Integrante / Jeovane Honório Alves - Integrante / LUCAS FERRARI DE OLIVEIRA - Coordenador.

• 2015 - 2015

  iDECIDE Smartphone App for Personalized Messages for Nutrition and Fitness Goals, Descrição: Development of a smartphone application able to collect data from the user and store it in a server in which is possible to retrieve and analyze this data. The app is developed using the cross-platform technology Adobe PhoneGap, NodeJS, HTML5, Javascript, CSS, and jQuery.. , Situação: Concluído; Natureza: Pesquisa. , Integrantes: Pedro Martins Moreira Neto - Integrante / Adela Maria Grando - Coordenador / Irene van Woerden - Integrante / Lauren Spano - Integrante / Danielle L. Groat - Integrante.