The OSI system is capable of detecting 0.1 +/- 0.1 mm 1D spatial displacement of a phantom in near real time and useful in head-motion monitoring. This new frameless SRS procedure using the mask-less head-fixation system provides immobilization similar to that of conventional frame-based SRS. Head-motion monitoring using near-real-time surface imaging provides adequate accuracy and is necessary for frameless SRS in case of unexpected head motion that exceeds a set tolerance.

To identify drought-tolerant crop cultivars or achieve a balance between water use and yield, accurate measurements of crop water stress are needed. In this study, the canopy temperature (Tc) of maize at the late vegetative stage was extracted from high-resolution red–green–blue (RGB, 1.25 cm) and thermal (7.8 cm) images taken by an unmanned aerial vehicle (UAV). To reduce the number of parameters for crop water stress monitoring, four simple methods that require only Tc were identified: Tc, degrees above non-stress, standard deviation of Tc, and variation coefficient of Tc. The ground-truth temperatures obtained using a handheld infrared thermometer were used to calibrate the temperature obtained from the UAV thermal images and to evaluate the Tc extraction results. Measured leaf stomatal conductance values were used to evaluate the performance of the four Tc-based crop water stress indicators. The results showed a strong correlation between ground-truth Tc and Tc extracted by the red–green ratio index (RGRI)-Otsu method proposed in this study, with a coefficient of determination of 0.94 (n = 15) and root mean square error value of 0.7°C. The RGRI-Otsu method was most accurate for estimating temperatures around 32.9°C, but the magnitude of residuals increased above and below this value. This phenomenon may be attributable to changes in canopy cover (leaf curling) under water stress, resulting in changes in the proportion of exposed sunlit soil in UAV thermal orthophotographs. Therefore, to improve the accuracy of maize canopy detection and extraction, optimal methods and better strategies for eliminating mixed pixels are needed. This study demonstrates the potential of using high-resolution UAV RGB images to supplement UAV thermal images for the accurate extraction of maize Tc.

We consider assortment and price optimization problems under the d-level nested logit model. In the assortment optimization problem, the goal is to find the revenue-maximizing assortment of products to offer, when the prices of the products are fixed. Using a novel formulation of the d-level nested logit model as a tree of depth d, we provide an efficient algorithm to find the optimal assortment. For a d-level nested logit model with n products, the algorithm runs in O(d n log n) time. In the price optimization problem, the goal is to find the revenue-maximizing prices for the products, when the assortment of offered products is fixed. Although the expected revenue is not concave in the product prices, we develop an iterative algorithm that generates a sequence of prices converging to a stationary point. Numerical experiments show that our method converges faster than gradient-based methods, by many orders of magnitude. In addition to providing solutions for the assortment and price optimization problems, we give support for the d-level nested logit model by demonstrating that it is consistent with the random utility maximization principle and equivalent to the elimination by aspects model.

River systems are valuable to human beings; meanwhile, they are intensively influenced by human activities, especially urbanization. In this study, based on the data derived from topographic maps and remote sensing images, the temporal and spatial change of river system geomorphology in the Taihu Region over the past 50 years was investigated in conjunction with urbanization. Results demonstrated that the number of river systems decreased drastically, that the morphology of river channels changed into wider and straighter and that the structure of river network tended to simplify in the Taihu Region in recent 50 years. Meanwhile, the changes in river density, the water surface ratio, the river development coefficient, the main river area length ratio and the box dimension in the rapid urbanization period were much greater than those in the slow urbanization period, but the decrease of river sinuosity in the slow urbanization period was more intense. Moreover, the spatial differences of the changes in the river development coefficient were the largest, and the changes in the river indicators in the low-urbanized regions were the most intense. In addition, the changes in the water surface ratio had the closest correlation with urbanization, and the relational degrees between population urbanization and the changes in river systems were the largest. The results can provide a reliable basis to determine reasonable management and conservation strategies of river systems in the Taihu Region. OPEN ACCESSWater 2015, 7 1341

Purpose: Localizing lung tumors during treatment delivery is critical for managing respiratory motion, ensuring tumor coverage, and reducing toxicities. The purpose of this project is to develop a real-time system that performs markerless tracking of lung tumors using simultaneously acquired MV and kV images during radiotherapy of lung cancer with volumetric modulated arc therapy. Method: Continuous MV/kV images were simultaneously acquired during dose delivery. In the subsequent analysis, a gantry angle-specific region of interest was defined according to the treatment aperture. After removing imaging artifacts, processed MV/kV images were directly registered to the corresponding daily setup cone-beam CT (CBCT) projections that served as reference images. The registration objective function consisted of a sum of normalized cross-correlation, weighted by the contrast-to-noise ratio of each MV and kV image. The calculated 3D shifts of the tumor were corrected by the displacements between the CBCT projections and the planning respiratory correlated CT (RCCT) to generate motion traces referred to a specific respiratory phase. The accuracy of the algorithm was evaluated on both anthropomorphic phantom and patient studies. The phantom consisted of localizing a 3D printed tumor, embedded in a thorax phantom, in an arc delivery. In an IRB-approved study, data were obtained from VMAT treatments of two lung cancer patients with three electromagnetic (Calypso) beacon transponders implanted in airways near the lung tumor. Result: In the phantom study, the root mean square error (RMSE) between the registered and actual (programmed couch movement) target position was 1.2 mm measured by the MV/kV imaging system, which was smaller compared to the MV or kV alone, of 4.1 and 1.3 mm, respectively. In the patient study, the mean and standard deviation discrepancy between electromagnetic-based tumor position and the MV/KV-markerless approach was –0.2 ± 0.6 mm, 0.2 ± 1.0 mm, and – 1.2 ± 1.5 mm along the superior-inferior, anterior-posterior, and left-right directions, respectively; resulting in a 3D displacement discrepancy of 2.0 ± 1.1 mm. Poor contrast around the tumor was the main contribution to registration uncertainties. Conclusion: The combined MV/kV imaging system can provide real-time 3D localization of lung tumor, with comparable accuracy to the electromagnetic-based system when features of tumors are detectable. Careful design of a registration algorithm and a VMAT plan that maximizes the tumor visibility are key elements for a successful MV/KV localization strategy.

No abstract

The purpose of this study was to evaluate performance of the third generation of model‐based iterative reconstruction (MBIR) system, Veo 3.0, based on noise power spectrum (NPS) analysis with various clinical presets over a wide range of clinically applicable dose levels. A CatPhan 600 surrounded by an oval, fat‐equivalent ring to mimic patient size/shape was scanned 10 times at each of six dose levels on a GE HD 750 scanner. NPS analysis was performed on images reconstructed with various Veo 3.0 preset combinations for comparisons of those images reconstructed using Veo 2.0, filtered back projection (FBP) and adaptive statistical iterative reconstruction (ASiR). The new Target Thickness setting resulted in higher noise in thicker axial images. The new Texture Enhancement function achieved a more isotropic noise behavior with less image artifacts. Veo 3.0 provides additional reconstruction options designed to allow the user choice of balance between spatial resolution and image noise, relative to Veo 2.0. Veo 3.0 provides more user selectable options and in general improved isotropic noise behavior in comparison to Veo 2.0. The overall noise reduction performance of both versions of MBIR was improved in comparison to FBP and ASiR, especially at low‐dose levels.PACS number(s): 87.57.‐s, 87.57.Q‐, 87.57.C‐, 87.57.nf, 87.57.C‐, 87.57.cm

The magnetic tensor gradiometer, which is used for measuring the spatial derivatives of three orthogonal magnetic field components, is an important magnetic field characterization tool. Here, the construction of a magnetic full-tensor gradiometer is described, which utilizes four fluxgates arranged on a planar cross structure, and a single, triaxial, spherical feedback coil assembly. In this arrangement, one of the fluxgates is used as a reference, controlling the currents through the feedback coils. Since the fluxgates are working in the near-zero magnetic field environment, the magnetic tensor gradiometer is stable and of an improved accuracy. This design avoids the crosstalk normally caused by individual feedback coils for each fluxgate, and reduces the orthogonality and orientation errors. Moreover, the calibration parameters can be directly inferred using the spherical feedback coil. The measured gradient tensor magnitude can reach 0.52 nT/m/Hz(1/2) @ 1 Hz in unshielded laboratory conditions, while exhibiting good noise immunity. The functionality of the system is verified by locating a small, single, permanent, and dipole magnet in space. The gradiometer is compact, while employing global feedback, and therefore it is especially suitable for deployment on space-constrained moving platforms.