Publications by authors named "B E Tendler"
Pheochromocytoma patients with high levels of circulating catecholamines are at risk of cardiovascular complications related to hypertensive emergencies and subsequent organ damage. A patient with concomitant aortic stenosis and pheochromocytoma has compounded risk of cardiovascular complications, especially during surgery, which complicates medical decision-making. We report a patient with Turner syndrome and congenital heart defects (CHDs) who was incidentally discovered to have a pheochromocytoma during workup of symptomatic severe bioprosthetic aortic stenosis.
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- 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.
Article Synopsis
- A lab handbook serves as a guide that defines the values and expectations within a research group.
- It details the roles of lab members and promotes a supportive culture that fosters their development as researchers.
- The text also offers a framework and resources for other labs to create their own effective handbooks.
Background: Accurate registration between microscopy and MRI data is necessary for validating imaging biomarkers against neuropathology, and to disentangle complex signal dependencies in microstructural MRI. Existing registration methods often rely on serial histological sampling or significant manual input, providing limited scope to work with a large number of stand-alone histology sections. Here we present a customisable pipeline to assist the registration of stand-alone histology sections to whole-brain MRI data.
View Article and Find Full Text PDFThe acquisition of MRI and histology in the same post-mortem tissue sample enables direct correlation between MRI and histologically-derived parameters. However, there still lacks a standardised automated pipeline to process histology data, with most studies relying on manual intervention. Here, we introduce an automated pipeline to extract a quantitative histological measure for staining density (stain area fraction, SAF) from multiple immunohistochemical (IHC) stains.
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