Evaluation of Image Registration Accuracy for Tumor and Organs at Risk in the Thorax for Compliance With TG 132 Recommendations

Purpose To evaluate accuracy for 2 deformable image registration methods (in-house B-spline and MIM freeform) using image pairs exhibiting changes in patient orientation and lung volume and to assess the appropriateness of registration accuracy tolerances proposed by the American Association of Physicists in Medicine Task Group 132 under such challenging conditions via assessment by expert observers. Methods and Materials Four-dimensional computed tomography scans for 12 patients with lung cancer were acquired with patients in prone and supine positions. Tumor and organs at risk were delineated by a physician on all data sets: supine inhale (SI), supine exhale, prone inhale, and prone exhale. The SI image was registered to the other images using both registration methods. All SI contours were propagated using the resulting transformations and compared with physician delineations using Dice similarity coefficient, mean distance to agreement, and Hausdorff distance. Additionally, propagated contours were anonymized along with ground-truth contours and rated for quality by physician-observers. Results Averaged across all patients, the accuracy metrics investigated remained within tolerances recommended by Task Group 132 (Dice similarity coefficient \u3e0.8, mean distance to agreement \u3c3 \u3emm). MIM performed better with both complex (vertebrae) and low-contrast (esophagus) structures, whereas the in-house method performed better with lungs (whole and individual lobes). Accuracy metrics worsened but remained within tolerances when propagating from supine to prone; however, the Jacobian determinant contained regions with negative values, indicating localized nonphysiologic deformations. For MIM and in-house registrations, 50% and 43.8%, respectively, of propagated contours were rated acceptable as is and 8.2% and 11.0% as clinically unacceptable. Conclusions The deformable image registration methods performed reliably and met recommended tolerances despite anatomically challenging cases exceeding typical interfraction variability. However, additional quality assurance measures are necessary for complex applications (eg, dose propagation). Human review rather than unsupervised implementation should always be part of the clinical registration workflow

Dataset of "A multiscale dataset for understanding complex eco-hydrological processes in a heterogeneous oasis system"

<p>This dataset is prepared for the paper "A multiscale dataset for understanding complex eco-hydrological processes in a heterogeneous oasis system" on Scientific Data.</p><p>HiWATER is designed to be a comprehensive eco-hydrological experiment in the framework of the “Integrated research on the eco-hydrological process of the Heihe River Basin” , based on the diverse needs of the interdisciplinary studies of the research plan and the existing observing infrastructures in the basin. The overall objective of HiWATER is to improve the observability of hydrological and ecological processes, to build a world-class watershed observing system and to enhance the applicability of remote sensing in integrated eco-hydrological studies and water recourse management at the basin scale. HiWATER was formally initialized in May 2012 and will last four years until 2015.</p><p>HiWATER is jointly supported by two project groups titled “Heihe Watershed Allied Telemetry Experimental Research” (grant numbers: 91125001, 91125002, 91125003, 91125004) and “Remote Sensing Data Products in the Heihe River Basin: Algorithm Development, Data Products Generation and Application Experiments” (KZCX2-XB3-15), which are funded by the NSFC and Chinese Academy of Sciences, respectively.<br></p

The Heihe Integrated Observatory Network: A Basin-Scale Land Surface Processes Observatory in China

Research on land surface processes at the catchment scale has drawn much attention over the past few decades, and a number of watershed observatories have been established worldwide. The Heihe River Basin (HRB), which contains the second largest inland river in China, is an ideal natural field experimental area for investigation of land surface processes involving diverse landscapes and the coexistence of cold and arid regions. The Heihe Integrated Observatory Network was established in 2007. For long-term observations, a hydrometeorological observatory, ecohydrological wireless sensor network, and satellite remote sensing are now in operation. In 2012, a multiscale observation experiment on evapotranspiration over heterogeneous land surfaces was conducted in the midstream region of the HRB, which included a flux observation matrix, wireless sensor network, airborne remote sensing, and synchronized ground measurements. Under an open data policy, the datasets have been publicly released following careful data processing and quality control. The outcomes highlight the integrated research on land surface processes in the HRB and include observed trends, scaling methods, high spatiotemporal resolution remote sensing products, and model–data integration in the HRB, all of which are helpful to other endorheic basins in the “Silk Road Economic Belt.” Henceforth, the goal of the Heihe Integrated Observatory Network is to develop an intelligent monitoring system that incorporates ground-based observatory networks, unmanned aerial vehicles, and multi-source satellites through the Internet of Things technology. Furthermore, biogeochemical processes observation will be improved, and the study of integrating ground observations, remote sensing, and large-scale models will be promoted further