3 citations · 7 across the 6 of their papers we have counts for
7 papers · 1 filter
FOD-Swin-Net: angular super resolution of fiber orientation distribution using a transformer-based deep model
Mateus Oliveira da Silva, Caio Pinheiro Santana, Diedre Santos do Carmo +1
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 us…
MEDPSeg: Hierarchical polymorphic multitask learning for the segmentation of ground-glass opacities, consolidation, and pulmonary structures on computed tomography
Diedre S. Carmo, Jean A. Ribeiro, Alejandro P. Comellas +4
The COVID-19 pandemic response highlighted the potential of deep learning methods in facilitating the diagnosis, prognosis and understanding of lung diseases through automated segm…
Automatic segmentation of lung findings in CT and application to Long COVID
Diedre S. Carmo, Rosarie A. Tudas, Alejandro P. Comellas +4
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 me…
Automated computed tomography and magnetic resonance imaging segmentation using deep learning: a beginner's guide
Diedre Carmo, Gustavo Pinheiro, Lívia Rodrigues +3
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…
Open-source tool for Airway Segmentation in Computed Tomography using 2.5D Modified EfficientDet: Contribution to the ATM22 Challenge
Diedre Carmo, Leticia Rittner, Roberto Lotufo
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 ma…
Hippocampus Segmentation on Epilepsy and Alzheimer's Disease Studies with Multiple Convolutional Neural Networks
Diedre Carmo, Bruna Silva, Clarissa Yasuda +2
Hippocampus segmentation on magnetic resonance imaging is of key importance for the diagnosis, treatment decision and investigation of neuropsychiatric disorders. Automatic segment…