Data adaptive regularization with reference tissue constraints for liver quantitative susceptibility mapping.

Purpose: To improve repeatability and reproducibility across acquisition parameters and reduce bias in quantitative susceptibility mapping (QSM) of the liver, through development of an optimized regularized reconstruction algorithm for abdominal QSM.

Methods: An optimized approach to estimation of magnetic susceptibility distribution is formulated as a constrained reconstruction problem that incorporates estimates of the input data reliability and anatomical priors available from chemical shift-encoded imaging. The proposed data-adaptive method was evaluated with respect to bias, repeatability, and reproducibility in a patient population with a wide range of liver iron concentration (LIC).

Automated MR Image Prescription of the Liver Using Deep Learning: Development, Evaluation, and Prospective Implementation.

Background: There is an unmet need for fully automated image prescription of the liver to enable efficient, reproducible MRI.

Purpose: To develop and evaluate artificial intelligence (AI)-based liver image prescription.

Study Type: Prospective.

Evaluating the performance of temporal and spatial early warning statistics of algal blooms.

Regime shifts have large consequences for ecosystems and the services they provide. However, understanding the potential for, causes of, proximity to, and thresholds for regime shifts in nearly all settings is difficult. Generic statistical indicators of resilience have been proposed and studied in a wide range of ecosystems as a method to detect when regime shifts are becoming more likely without direct knowledge of underlying system dynamics or thresholds.

A synthesis of modern organic carbon accumulation rates in coastal and aquatic inland ecosystems.

Organic carbon accumulation in the sediments of inland aquatic and coastal ecosystems is an important process in the global carbon budget that is subject to intense human modification. To date, research has focused on quantifying accumulation rates in individual or groups of aquatic ecosystems to quantify the aquatic carbon sinks. However, there hasn't been a synthesis of rates across aquatic ecosystem to address the variability in rates within and among ecosystems types.