A deep learning toolbox for automatic segmentation of subcortical limbic structures from MRI images
| العنوان: | A deep learning toolbox for automatic segmentation of subcortical limbic structures from MRI images |
|---|---|
| المؤلفون: | Bruce Fischl, Juan Eugenio Iglesias, Devani Cordero, Jean C. Augustinack, Douglas N. Greve, Adrian V. Dalca, Benjamin Billot, Malte Hoffmann, Andrew Hoopes |
| المصدر: | NeuroImage, Vol 244, Iss, Pp 118610-(2021) NeuroImage |
| بيانات النشر: | Elsevier, 2021. |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | Adult, Male, Adolescent, Basal Forebrain, Mammillary body, Computer science, Cognitive Neuroscience, Fornix, Brain, Neurosciences. Biological psychiatry. Neuropsychiatry, Article, Nucleus Accumbens, Young Adult, Deep Learning, Limbic system, Limbic System, medicine, Humans, Aged, Aged, 80 and over, Basal forebrain, business.industry, Deep learning, Fornix, Reproducibility of Results, Septal nuclei, Pattern recognition, Middle Aged, Magnetic Resonance Imaging, Toolbox, Data set, medicine.anatomical_structure, Neurology, Female, Septal Nuclei, Artificial intelligence, business, RC321-571 |
| الوصف: | A tool was developed to automatically segment several subcortical limbic structures (nucleus accumbens, basal forebrain, septal nuclei, hypothalamus without mammillary bodies, the mammillary bodies, and fornix) using only a T1-weighted MRI as input. This tool fills an unmet need as there are few, if any, publicly available tools to segment these clinically relevant structures. A U-Net with spatial, intensity, contrast, and noise augmentation was trained using 39 manually labeled MRI data sets. In general, the Dice scores, true positive rates, false discovery rates, and manual-automatic volume correlation were very good relative to comparable tools for other structures. A diverse data set of 698 subjects were segmented using the tool; evaluation of the resulting labelings showed that the tool failed in less than 1% of cases. Test-retest reliability of the tool was excellent. The automatically segmented volume of all structures except mammillary bodies showed effectiveness at detecting either clinical AD effects, age effects, or both. This tool will be publicly released with FreeSurfer (surfer.nmr.mgh.harvard.edu/fswiki/ScLimbic). Together with the other cortical and subcortical limbic segmentations, this tool will allow FreeSurfer to provide a comprehensive view of the limbic system in an automated way. Graphical Abstract |
| اللغة: | English |
| تدمد: | 1095-9572 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e7b693fa3ef63de5d08b4b8aeffd854b http://www.sciencedirect.com/science/article/pii/S1053811921008831 |
| Rights: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....e7b693fa3ef63de5d08b4b8aeffd854b |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 10959572 |
|---|