Zobrazeno 1 - 10
of 31
pro vyhledávání: '"Carmo, Diedre"'
Identifying and characterizing brain fiber bundles can help to understand many diseases and conditions. An important step in this process is the estimation of fiber orientations using Diffusion-Weighted Magnetic Resonance Imaging (DW-MRI). However, o
Externí odkaz:
http://arxiv.org/abs/2402.11775
Autor:
Carmo, Diedre S., Ribeiro, Jean A., Comellas, Alejandro P., Reinhardt, Joseph M., Gerard, Sarah E., Rittner, Letícia, Lotufo, Roberto A.
The COVID-19 pandemic response highlighted the potential of deep learning methods in facilitating the diagnosis, prognosis and understanding of lung diseases through automated segmentation of pulmonary structures and lesions in chest computed tomogra
Externí odkaz:
http://arxiv.org/abs/2312.02365
Autor:
Carmo, Diedre S., Tudas, Rosarie A., Comellas, Alejandro P., Rittner, Leticia, Lotufo, Roberto A., Reinhardt, Joseph M., Gerard, Sarah E.
Automated segmentation of lung abnormalities in computed tomography is an important step for diagnosing and characterizing lung disease. In this work, we improve upon a previous method and propose S-MEDSeg, a deep learning based approach for accurate
Externí odkaz:
http://arxiv.org/abs/2310.09446
Autor:
Carmo, Diedre, Pinheiro, Gustavo, Rodrigues, Lívia, Abreu, Thays, Lotufo, Roberto, Rittner, Letícia
Medical image segmentation is an increasingly popular area of research in medical imaging processing and analysis. However, many researchers who are new to the field struggle with basic concepts. This tutorial paper aims to provide an overview of the
Externí odkaz:
http://arxiv.org/abs/2304.05901
Airway segmentation in computed tomography images can be used to analyze pulmonary diseases, however, manual segmentation is labor intensive and relies on expert knowledge. This manuscript details our contribution to MICCAI's 2022 Airway Tree Modelli
Externí odkaz:
http://arxiv.org/abs/2209.15094
In natural language processing (NLP), there is a need for more resources in Portuguese, since much of the data used in the state-of-the-art research is in other languages. In this paper, we pretrain a T5 model on the BrWac corpus, an extensive collec
Externí odkaz:
http://arxiv.org/abs/2008.09144
Publikováno v:
Heliyon, Volume 7, Issue 2, 2021
Hippocampus segmentation on magnetic resonance imaging is of key importance for the diagnosis, treatment decision and investigation of neuropsychiatric disorders. Automatic segmentation is an active research field, with many recent models using deep
Externí odkaz:
http://arxiv.org/abs/2001.05058
Hippocampus segmentation plays a key role in diagnosing various brain disorders such as Alzheimer's disease, epilepsy, multiple sclerosis, cancer, depression and others. Nowadays, segmentation is still mainly performed manually by specialists. Segmen
Externí odkaz:
http://arxiv.org/abs/1902.04487
Publikováno v:
In Heliyon February 2021 7(2)
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