Unsupervised reconstruction of a three-dimensional left ventricular strain from parallel tagged cardiac images.

A new algorithm, called the Unsupervised Tag ExTraction and Heart strain(E) Reconstruction (UNTETHER) algorithm, is presented for quantifying three-dimensional (3D) myocardial strain in tagged cardiac MR images. Five human volunteers and five postinfarct patients were imaged. 3D strains measured by UNTETHER and a user-supervised technique were compared. Each study was analyzed in 49 +/- 8 min with UNTETHER, compared to approximately 4 hr with the user-supervised technique. For pooled human data, the correlation coefficient between the two methods for circumferential shortening (E(cc)) was r = 0.91 at the mid-wall (P < 0.0005). UNTETHER is capable of measuring wall motion abnormalities resulting from coronary artery disease, and has the potential to overcome the main limitations (time and user-supervision requirements) to routine clinical use of tagged cardiac MRI

Joint Reconstruction of 2-D Left Ventricular Displacement and Contours from Tagged Magnetic Resonance Images Using Markov Random Field Edge Prior

Magnetic Resonance (MR) tagging has been shown to be a useful method for non-invasively measuring the deformation of the left ventricle (LV), during the cardiac cycle. By reconstructing a displacement field based on the movement of the tag lines, one can compute myocardial contraction measures such as strain. Existing methods depend on user-defined LV contours, which require human intervention and are therefore the biggest bottleneck in the reconstruction process. In this paper we present a method for reconstructing 2-D LV deformation without user-defined contours. We use a compound Gauss-Markov random field to model the 2-D vector displacement field, which is parameterized by two closed and smooth contours. By iteratively optimizing the contours, the displacement field, and the parameters, we obtain an estimate of the displacement field and the contours. Experimental results on in vivo human data are presented that demonstrate the accuracy of our algorithm. 1. Introduction Magnetic r..

Global Trends in Urban Agriculture Research: A Pathway toward Urban Resilience and Sustainability

Urban agriculture has been proposed as an important urban element to deal with the challenges of food insecurity and environmental deterioration. In order to track current popular topics and global research trends in urban agriculture, we used bibliometric analysis and visualization mapping to evaluate and analyze the developments in the knowledge of urban agriculture based on 605 papers from the core collection database Web of Science from 2001&ndash;2021. The results were as follows. (1) The number of urban agriculture publications increased substantially year by year, indicating that the field is attracting increasing attention. The University of Kassel, Chinese Academy of Sciences, and University of Freiburg are the most productive research institutions in the field of urban agriculture. The top-five most influential countries are the Unites States, Germany, the United Kingdom, Italy, and China, of which the Unites States plays a central role in the cooperative linkage between countries. (2) Research on urban agriculture focuses not only on food production and different styles but also on how to realize the various functions of urban agriculture. In addition, UA-related sustainability and the water-energy-food nexus have become two emerging research topics. (3) Urban agriculture does not necessarily mean a resource-conserving and environmentally friendly food system. To achieve sustainable development, a transition based on technological innovation is needed. How to improve the sustainable development level of the food system while fully considering the resilience, sustainability, and versatility of urban agriculture is the main direction of future research