Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Journals

Article Types

Countries / Regions

Search Results (3)

Search Parameters:
Authors = Nuno Canto Moreira

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
21 pages, 5998 KiB  
Article
Assessment of Regional Brain Volume Measurements with Different Brain Extraction and Bias Field Correction Methods in Neonatal MRI
by Tânia F. Vaz, Nima Naseh, Lena Hellström-Westas, Nuno Canto Moreira, Nuno Matela and Hugo A. Ferreira
Appl. Sci. 2024, 14(24), 11575; https://doi.org/10.3390/app142411575 - 11 Dec 2024
Viewed by 1503
Abstract
Proper selection and application of preprocessing steps are crucial for obtaining accurate segmentation in brain Magnetic Resonance Imaging (MRI). The aim of this study is to evaluate the impact brain extraction (BE) and bias field correction (BFC) methods have on regional brain volume [...] Read more.
Proper selection and application of preprocessing steps are crucial for obtaining accurate segmentation in brain Magnetic Resonance Imaging (MRI). The aim of this study is to evaluate the impact brain extraction (BE) and bias field correction (BFC) methods have on regional brain volume (RBV) measurements of preterm neonates’ T2w MRI at term-equivalent age (TEA). Five BE methods (Manual, BET2, SWS, HD-BET, SynthStrip) were applied together with two BFC methods (SPM-BFC and N4ITK), before segmenting the neonatal brain into eight tissue classes (cortical grey matter, white matter, cerebral spinal fluid, deep nuclear grey matter, hippocampus, amygdala, cerebellum, and brainstem) using an automated segmentation software (MANTiS). Quantitative assessments were conducted, including the coefficient of variation (CV), coefficient of joint variation (CJV), Dice coefficient (DC), and RBV. HD-BET, together with N4ITK, showed the highest performance (mean ± standard deviation) regarding CV of 0.047 ± 0.005 (white matter) and 0.070 ± 0.005 (grey matter), CJV of 0.662 ± 0.095, DC of 0.942 ± 0.063, and RBV without significant differences (except in the brainstem) from the manual segmentation. Therefore, such combination of methods is recommended for improved skull-stripping accuracy, intensity homogeneity, and reproducibility of RBV of T2w MRI at TEA. Full article
Show Figures

Figure 1

21 pages, 4269 KiB  
Article
Brain Extraction Methods in Neonatal Brain MRI and Their Effects on Intracranial Volumes
by Tânia F. Vaz, Nuno Canto Moreira, Lena Hellström-Westas, Nima Naseh, Nuno Matela and Hugo A. Ferreira
Appl. Sci. 2024, 14(4), 1339; https://doi.org/10.3390/app14041339 - 6 Feb 2024
Cited by 4 | Viewed by 2704
Abstract
Magnetic resonance imaging (MRI) plays an important role in assessing early brain development and injury in neonates. When using an automated volumetric analysis, brain tissue segmentation is necessary, preceded by brain extraction (BE) to remove non-brain tissue. BE remains challenging in neonatal brain [...] Read more.
Magnetic resonance imaging (MRI) plays an important role in assessing early brain development and injury in neonates. When using an automated volumetric analysis, brain tissue segmentation is necessary, preceded by brain extraction (BE) to remove non-brain tissue. BE remains challenging in neonatal brain MRI, and despite the existence of several methods, manual segmentation is still considered the gold standard. Therefore, the purpose of this study was to assess different BE methods in the MRI of preterm neonates and their effects on the estimation of intracranial volumes (ICVs). This study included twenty-two premature neonates (mean gestational age ± standard deviation: 28.4 ± 2.1 weeks) with MRI brain scans acquired at term, without detectable lesions or congenital conditions. Manual segmentation was performed for T2-weighted scans to establish reference brain masks. Four automated BE methods were used: Brain Extraction Tool (BET2); Simple Watershed Scalping (SWS); HD Brain Extraction Tool (HD-BET); and SynthStrip. Regarding segmentation metrics, HD-BET outperformed the other methods with median improvements of +0.031 (BET2), +0.002 (SWS), and +0.011 (SynthStrip) points for the dice coefficient; and −0.786 (BET2), −0.055 (SWS), and −0.124 (SynthStrip) mm for the mean surface distance. Regarding ICVs, SWS and HD-BET provided acceptable levels of agreement with manual segmentation, with mean differences of −1.42% and 2.59%, respectively. Full article
(This article belongs to the Special Issue Methods, Applications and Developments in Biomedical Informatics)
Show Figures

Figure 1

3 pages, 381 KiB  
Article
Superficial Siderosis: A Case Report
by Nuno Canto Moreira, Rūta Nylander, Inesa Briaukaitė, Severina Vėlyvytė, Rymantė Gleiznienė and Eglė Monastyreckienė
Medicina 2011, 47(6), 45; https://doi.org/10.3390/medicina47060045 - 28 Jun 2011
Cited by 2 | Viewed by 1202
Abstract
Superficial siderosis of the central nervous system is the result of chronic recurrent hemorrhages (e.g., arteriovenous malformations, tumors, or trauma), which leads to the accumulation of cytotoxic hemosiderin and presents with hearing loss, cerebellar dysfunction, and myelopathy. This article presents a clinical case [...] Read more.
Superficial siderosis of the central nervous system is the result of chronic recurrent hemorrhages (e.g., arteriovenous malformations, tumors, or trauma), which leads to the accumulation of cytotoxic hemosiderin and presents with hearing loss, cerebellar dysfunction, and myelopathy. This article presents a clinical case of an 11-year-old boy in whom the diagnosis of medulloblastoma was established. He underwent surgery, and after a few years, he began to complain of hearing loss. Magnetic resonance imaging revealed the cause of the hearing disturbance. The aim of this article is to review the recent literature related to the etiology, clinical and radiologic features of superficial siderosis, emphasizing the role of magnetic resonance imaging. Full article
Back to TopTop