Assessment of Regional Brain Volume Measurements with Different Brain Extraction and Bias Field Correction Methods in Neonatal MRI
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) measure...
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MDPI AG
2024-12-01
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| author | Tânia F. Vaz Nima Naseh Lena Hellström-Westas Nuno Canto Moreira Nuno Matela Hugo A. Ferreira |
| author_facet | Tânia F. Vaz Nima Naseh Lena Hellström-Westas Nuno Canto Moreira Nuno Matela Hugo A. Ferreira |
| author_sort | Tânia F. Vaz |
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| description | 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. |
| format | Article |
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| institution | Kabale University |
| issn | 2076-3417 |
| language | English |
| publishDate | 2024-12-01 |
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| spelling | doaj-art-82b30fbbc6c54c8d82a148f6210c36f52024-12-27T14:07:43ZengMDPI AGApplied Sciences2076-34172024-12-0114241157510.3390/app142411575Assessment of Regional Brain Volume Measurements with Different Brain Extraction and Bias Field Correction Methods in Neonatal MRITânia F. Vaz0Nima Naseh1Lena Hellström-Westas2Nuno Canto Moreira3Nuno Matela4Hugo A. Ferreira5Instituto de Biofísica e Engenharia Biomédica, Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisbon, PortugalDepartment of Women’s and Children’s Health, Uppsala University, 751 85 Uppsala, SwedenDepartment of Women’s and Children’s Health, Uppsala University, 751 85 Uppsala, SwedenDepartment of Neuroradiology, Karolinska University Hospital, 171 76 Stockholm, SwedenInstituto de Biofísica e Engenharia Biomédica, Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisbon, PortugalInstituto de Biofísica e Engenharia Biomédica, Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisbon, PortugalProper 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.https://www.mdpi.com/2076-3417/14/24/11575bias field correctionbrain extractionneonatal MRIregional brain volumesegmentation |
| spellingShingle | Tânia F. Vaz Nima Naseh Lena Hellström-Westas Nuno Canto Moreira Nuno Matela Hugo A. Ferreira Assessment of Regional Brain Volume Measurements with Different Brain Extraction and Bias Field Correction Methods in Neonatal MRI Applied Sciences bias field correction brain extraction neonatal MRI regional brain volume segmentation |
| title | Assessment of Regional Brain Volume Measurements with Different Brain Extraction and Bias Field Correction Methods in Neonatal MRI |
| title_full | Assessment of Regional Brain Volume Measurements with Different Brain Extraction and Bias Field Correction Methods in Neonatal MRI |
| title_fullStr | Assessment of Regional Brain Volume Measurements with Different Brain Extraction and Bias Field Correction Methods in Neonatal MRI |
| title_full_unstemmed | Assessment of Regional Brain Volume Measurements with Different Brain Extraction and Bias Field Correction Methods in Neonatal MRI |
| title_short | Assessment of Regional Brain Volume Measurements with Different Brain Extraction and Bias Field Correction Methods in Neonatal MRI |
| title_sort | assessment of regional brain volume measurements with different brain extraction and bias field correction methods in neonatal mri |
| topic | bias field correction brain extraction neonatal MRI regional brain volume segmentation |
| url | https://www.mdpi.com/2076-3417/14/24/11575 |
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