ArticleProceedings of SPIE--the International Society for Optical Engineering2019
Reproducibility Evaluation of SLANT Whole Brain Segmentation Across Clinical Magnetic Resonance Imaging Protocols.
Article in Proceedings of SPIE--the International Society for Optical Engineering, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 13 citations in OpenAlex.
- Volumetric brain MRI signatures of heart failure with preserved ejection fraction in the setting of dementia.Magnetic resonance imaging · 2024Article
- Neuronal microstructural changes in the human brain are associated with neurocognitive aging.bioRxiv : the preprint server for biology · 2024Article
- Variability of multidimensional diffusion-relaxation MRI estimates in the human brain.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Increased microglia activation in late non-central nervous system cancer survivors links to chronic systemic symptomatology.Human brain mapping · 2023Article
- Reproducibility evaluation of the effects of MRI defacing on brain segmentation.Journal of medical imaging (Bellingham, Wash.) · 2023Article
- Mapping the impact of nonlinear gradient fields with noise on diffusion MRI.Magnetic resonance imaging · 2023Article
- Deep whole brain segmentation of 7T structural MRI.Proceedings of SPIE--the International Society for Optical Engineering · 2023Article
- Generalizing deep whole-brain segmentation for post-contrast MRI with transfer learning.Journal of medical imaging (Bellingham, Wash.) · 2020Article
- Generalizing Deep Whole Brain Segmentation for Pediatric and Post- Contrast MRI with Augmented Transfer Learning.Proceedings of SPIE--the International Society for Optical Engineering · 2020Article
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
Whole brain segmentation on structural magnetic resonance imaging (MRI) is essential for understanding neuroanatomical-functional relationships. Traditionally, multi-atlas segmentation has been regarded as the standard method for whole brain segmentation. In past few years, deep convolutional neural network (DCNN) segmentation methods have demonstrated their advantages in both accuracy and computational efficiency. Recently, we proposed the spatially localized atlas network tiles (SLANT) method, which is able to segment a 3D MRI brain scan into 132 anatomical regions. Commonly, DCNN segmentation methods yield inferior performance under external validations, especially when the testing patterns were not presented in the training cohorts. Recently, we obtained a clinically acquired, multi-sequence MRI brain cohort with 1480 clinically acquired, de-identified brain MRI scans on 395 patients using seven different MRI protocols. Moreover, each subject has at least two scans from different MRI protocols. Herein, we assess the SLANT method's intra- and inter-protocol reproducibility. SLANT achieved less than 0.05 coefficient of variation (CV) for intra-protocol experiments and less than 0.15 CV for inter-protocol experiments. The results show that the SLANT method achieved high intra- and inter- protocol reproducibility.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.