Publications by authors named "Gregory G Slabaugh"
Aims: Automated algorithms are regularly used to analyse cardiac magnetic resonance (CMR) images. Validating data output reliability from this method is crucial for enabling widespread adoption. We outline a visual quality control (VQC) process for image analysis using automated batch processing.
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- Osteocytes are crucial cells in bone tissue, responsible for maintaining the balance between bone formation and resorption, particularly as bones age and their network integrity declines.
- Research has shown that analyzing the connectivity of osteocytes within their lacunar canalicular network (LCN) is vital for understanding bone physiology, but traditional methods of studying this network are slow and subjective.
- This study utilizes deep learning and computer vision techniques, specifically an Attention U-Net model, to automate the segmentation of osteocytes, achieving high accuracy in distinguishing between young and aged mice bones and advancing the analysis of osteocyte degeneration.
Phenotyping left ventricular systolic dysfunction in asymptomatic individuals for improved risk stratification.
Eur Heart J Cardiovasc Imaging
September 2023
Aims: Left ventricular systolic dysfunction (LSVD) is a heterogeneous condition with several factors influencing prognosis. Better phenotyping of asymptomatic individuals can inform preventative strategies. This study aims to explore the clinical phenotypes of LVSD in initially asymptomatic subjects and their association with clinical outcomes and cardiovascular abnormalities through multi-dimensional data clustering.
View Article and Find Full Text PDFBackground: Ischemic heart disease (IHD) has been linked with poor brain outcomes. The brain magnetic resonance imaging-derived difference between predicted brain age and actual chronological age (brain-age delta in years, positive for accelerated brain aging) may serve as an effective means of communicating brain health to patients to promote healthier lifestyles.
Objectives: The authors investigated the impact of prevalent IHD on brain aging, potential underlying mechanisms, and its relationship with dementia risk, vascular risk factors, cardiovascular structure, and function.