All Outputs (3)

Diagnostic utility of artificial intelligence for left ventricular scar identification using cardiac magnetic resonance imaging—A systematic review (2021)
Journal Article
Jathanna, N., Podlasek, A., Sokol, A., Auer, D., Chen, X., & Jamil-Copley, S. (2021). Diagnostic utility of artificial intelligence for left ventricular scar identification using cardiac magnetic resonance imaging—A systematic review. Cardiovascular Digital Health Journal, 2(6), S21-S29. https://doi.org/10.1016/j.cvdhj.2021.11.005

Background: Accurate, rapid quantification of ventricular scar using cardiac magnetic resonance imaging (CMR) carries importance in arrhythmia management and patient prognosis. Artificial intelligence (AI) has been applied to other radiological chall... Read More about Diagnostic utility of artificial intelligence for left ventricular scar identification using cardiac magnetic resonance imaging—A systematic review.

Dynamic metabolic patterns tracking neurodegeneration and gliosis following 26S proteasome dysfunction in mouse forebrain neurons (2018)
Journal Article
Geiszler, P. C., Ugun-Klusek, A., Lawler, K., Pardon, M.-C., Yuchun, D., Bai, L., Daykin, C., Auer, D. P., & Bedford, L. (in press). Dynamic metabolic patterns tracking neurodegeneration and gliosis following 26S proteasome dysfunction in mouse forebrain neurons. Scientific Reports, 8, Article 4833. https://doi.org/10.1038/s41598-018-23155-2

Metabolite profiling is an important tool that may better capture the multiple features of neurodegeneration. With the considerable parallels between mouse and human metabolism, the use of metabolomics in mouse models with neurodegenerative pathology... Read More about Dynamic metabolic patterns tracking neurodegeneration and gliosis following 26S proteasome dysfunction in mouse forebrain neurons.

Novel Methods for Microglia Segmentation, Feature Extraction, and Classification (2016)
Journal Article
Ding, Y., Pardon, M. C., Agostini, A., Faas, H., Duan, J., Ward, W. O., …Bai, L. (2016). Novel Methods for Microglia Segmentation, Feature Extraction, and Classification. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 14(6), 1366-1377. https://doi.org/10.1109/TCBB.2016.2591520

© 2017 IEEE. Segmentation and analysis of histological images provides a valuable tool to gain insight into the biology and function of microglial cells in health and disease. Common image segmentation methods are not suitable for inhomogeneous histo... Read More about Novel Methods for Microglia Segmentation, Feature Extraction, and Classification.