Publications by authors named "L Griffanti"

Cerebral microbleeds (CMBs) are small, hypointense hemosiderin deposits in the brain measuring 2-10 mm in diameter. As one of the important biomarkers of small vessel disease, they have been associated with various neurodegenerative and cerebrovascular diseases. Hence, automated detection, and subsequent extraction of clinically useful metrics (e.

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The ageing process is associated with reduced emotional recognition (ER) performance. The ER ability is an essential part of non-verbal communication, and its role is crucial for proper social functioning. Here, using the 'Cambridge Centre for Ageing and Neuroscience cohort sample', we investigated when ER, measured using a facial emotion recognition test, begins to consistently decrease along the lifespan.

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Introduction: Despite major advances in the field of neuroscience over the last three decades, the quality of assessments available to patients with memory problems in later life has barely changed. At the same time, a large proportion of dementia biomarker research is conducted in selected research samples that often poorly reflect the demographics of the population of patients who present to memory clinics. The Oxford Brain Health Clinic (BHC) is a newly developed clinical assessment service with embedded research in which all patients are offered high-quality clinical and research assessments, including MRI, as standard.

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In this work we present BIANCA-MS, a novel tool for brain white matter lesion segmentation in multiple sclerosis (MS), able to generalize across both the wide spectrum of MRI acquisition protocols and the heterogeneity of manually labeled data. BIANCA-MS is based on the original version of BIANCA and implements two innovative elements: a harmonized setting, tested under different MRI protocols, which avoids the need to further tune algorithm parameters to each dataset; and a cleaning step developed to improve consistency in automated and manual segmentations, thus reducing unwanted variability in output segmentations and validation data. BIANCA-MS was tested on three datasets, acquired with different MRI protocols.

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Article Synopsis
  • Cerebral microbleeds (CMBs) are small brain lesions linked to various diseases and are visualized differently on certain imaging methods, prompting the need for accurate detection to derive imaging biomarkers.
  • This study introduces a fully automated, three-step deep learning algorithm that detects CMBs using different imaging modalities, improving detection sensitivity and reducing false positives.
  • Results showed that the algorithm achieved over 90% true positive rate in detecting CMBs within datasets, significantly enhancing detection accuracy compared to existing methods, and demonstrated good generalizability across varied datasets.
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