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Efficient detection of cerebral microbleeds on 7.0 T MR images using the radial symmetry transform.

, , , , , , and . NeuroImage, 59 (3): 2266-2273 (2012)

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Subfields of the hippocampal formation at 7 T MRI: In vivo volumetric assessment., , , , , , and . NeuroImage, 61 (4): 1043-1049 (2012)Prior-knowledge-informed deep learning for lacune detection and quantification using multi-site brain MRI., , , , , , , and . CoRR, (2023)Automated White Matter Hyperintensity Segmentation Using Bayesian Model Selection: Assessment and Correlations with Cognitive Change., , , , , , , , , and 2 other author(s). Neuroinformatics, 18 (3): 429-449 (2020)Supervised novelty detection in brain tissue classification with an application to white matter hyperintensities., , , , , , , and . Medical Imaging: Image Processing, volume 9784 of SPIE Proceedings, page 978421. SPIE, (2016)Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities and Results of the WMH Segmentation Challenge., , , , , , , , , and 34 other author(s). CoRR, (2019)Detecting cerebral microbleeds in 7.0 T MR images using the radial symmetry transform., , , , and . ISBI, page 758-761. IEEE, (2011)Bayesian Model Selection for Pathological Neuroimaging Data Applied to White Matter Lesion Segmentation., , , , , and . IEEE Trans. Medical Imaging, 34 (10): 2079-2102 (2015)Efficient detection of cerebral microbleeds on 7.0 T MR images using the radial symmetry transform., , , , , , and . NeuroImage, 59 (3): 2266-2273 (2012)Methodological considerations on tract-based spatial statistics (TBSS)., , , , , , and . NeuroImage, (2014)Effect of Fixed-Density Thresholding on Structural Brain Networks: A Demonstration in Cerebral Small Vessel Disease., , , , , and . Brain Connect., 10 (3): 121-133 (2020)