23 citations · 45 across the 15 of their papers we have counts for
5 papers · 1 filter
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…
Extended 2D Consensus Hippocampus Segmentation
Diedre Carmo, Bruna Silva, Clarissa Yasuda +2
Hippocampus segmentation plays a key role in diagnosing various brain disorders such as Alzheimer's disease, epilepsy, multiple sclerosis, cancer, depression and others. Nowadays,…
Silver Standard Masks for Data Augmentation Applied to Deep-Learning-Based Skull-Stripping
Oeslle Lucena, Roberto Souza, Letícia Rittner +2
The bottleneck of convolutional neural networks (CNN) for medical imaging is the number of annotated data required for training. Manual segmentation is considered to be the "gold-s…