Effects Of Geometric Distortion Research Articles

Optimisation of b-values for the accurate estimation of the apparent diffusion coefficient (ADC) in whole-body diffusion-weighted MRI in patients with metastatic melanoma

ObjectiveTo establish optimised diffusion weightings (‘b-values’) for acquisition of whole-body diffusion-weighted MRI (WB-DWI) for estimation of the apparent diffusion coefficient (ADC) in patients with metastatic melanoma (MM). Existing recommendations for WB-DWI have not been optimised for the tumour properties in MM; therefore, evaluation of acquisition parameters is essential before embarking on larger studies.MethodsRetrospective clinical data and phantom experiments were used. Clinical data comprised 125 lesions from 14 examinations in 11 patients with multifocal MM, imaged before and/or after treatment with immunotherapy at a single institution. ADC estimates from these data were applied to a model to estimate the optimum b-value. A large non-diffusing phantom was used to assess eddy current–induced geometric distortion.ResultsConsidering all tumour sites from pre- and post-treatment examinations together, metastases exhibited a large range of mean ADC values, [0.67–1.49] × 10−3 mm2/s, and the optimum high b-value (bhigh) for ADC estimation was 1100 (10th–90th percentile: 740–1790) s/mm2. At higher b-values, geometric distortion increased, and longer echo times were required, leading to reduced signal.ConclusionsTheoretical optimisation gave an optimum bhigh of 1100 (10th–90th percentile: 740–1790) s/mm2 for ADC estimation in MM, with the large range of optimum b-values reflecting the wide range of ADC values in these tumours. Geometric distortion and minimum echo time increase at higher b-values and are not included in the theoretical optimisation; bhigh in the range 750–1100 s/mm2 should be adopted to maintain acceptable image quality but performance should be evaluated for a specific scanner.Key Points• Theoretical optimisation gave an optimum high b-value of 1100 (10th–90th percentile: 740–1790) s/mm2for ADC estimation in metastatic melanoma.• Considering geometric distortion and minimum echo time (TE), a b-value in the range 750–1100 s/mm2is recommended.• Sites should evaluate the performance of specific scanners to assess the effect of geometric distortion and minimum TE.

Sar2color: Learning Imaging Characteristics of SAR Images for SAR-to-Optical Transformation

Optical images are rich in spectral information, but difficult to acquire under all-weather conditions, while SAR images can overcome adverse meteorological conditions, but geometric distortion and speckle noise will reduce the quality of SAR images and thus make image interpretation more challenging. Therefore, transforming SAR images to optical images to assist SAR image interpretation will bring opportunities for SAR image application. With the advancement of deep learning technology, the ability of SAR-to-optical transformation has been greatly improved. However, most of the current mainstream transformation methods do not consider the imaging characteristics of SAR images, and there will be failures such as noisy color spots and regional landform deformation in the generated optical images. Moreover, since the SAR image itself does not contain color information, there also exist many color errors in these results. Aiming at the above problems, Sar2color, an end-to-end general SAR-to-optical transformation model, is proposed based on a conditional generative adversarial network (CGAN). The model uses DCT residual block to reduce the effect of coherent speckle noise on the generated optical images, and constructs the Light atrous spatial pyramid pooling (Light-ASPP) module to mitigate the negative effect of geometric distortion on the generation of optical images. These two designs ensure the precision of texture details when the SAR image is transformed into an optical image, and use the correct color memory block (CCMB) to improve the color accuracy of transformation results. Towards the Sar2color model, we have carried out evaluations on the homologous heterogeneous SAR image and optical image pairing dataset SEN1-2. The experimental results show that, compared with other mainstream transformation models, Sar2color achieves the state-of-the-art effect on all three objective and one subjective evaluation metrics. Furthermore, we have carried out various ablation experiments, and the results show the effectiveness of each designed module of Sar2color.

Geocoding of ground-based SAR data for infrastructure objects using the Maximum A Posteriori estimation and ray-tracing

Ground-Based Synthetic Aperture Radar (GB-SAR) enables to monitor a scene in a distance up to a few km and with an accuracy of around one mm. It is mainly used for landslide monitoring but also used to monitor man-made structures such as bridges and dams. Due to the particular distance-dependent imaging concept and related geometric distortion effects, the interpretation of the SAR images can be difficult, especially in the case of complex man-made structures. The geocoding of the SAR data enables to project the 2D SAR image on a 3D digital elevation model (DEM) or a 3D terrain model and highly improves the interpretation of the observed deformation. It also allows to fuse SAR-based observations with other data sources. The purpose of this paper is to present a new algorithm to geocode GB-SAR data in complex scenarios. The method introduces two new components, a Bayesian statistical approach and a ray-tracing algorithm. The first one uses an a priori function on the received intensity to improve the geocoding in case of strong layover, while the latter considers areas in the radar shadow to be excluded from geocoding. Moreover, ray-tracing provides the starting point for the analysis of signals with multiple reflections which are also discussed in this paper. Our algorithm is applied to and evaluated with two case studies. The first one demonstrates the improved geocoding of GB-SAR data on the Linach dam in the Black Forest in Germany, which is characterized by a rather complex architecture. The second case study shows the application of the method at the Enguri dam in Georgia, which is characterized by its large dimensions and a dam height over 270m.

Tiny-BDN: An Efficient and Compact Barcode Detection Network

This paper presents a novel approach for accurate barcodes detection in real and challenging environments using compact deep neural networks. Our approach is based on Convolutional Neural Network (CNN) and neural network compression, which can detect the four vertexes coordinates of a barcode accurately and quickly. Our approach consists of four stages: (i) feature extraction by a base network, (ii) region proposal network (RPN) training, (iii) barcode classification and coordinates regression, and (iv) weights pruning and recoding. The model is trained in the first three stages and then compressed in the fourth stage to reduce the size of the trained model. In order to remove the effect of geometric distortion during barcode decoding, we add a distortion removal module to the end of the trained model. In experiments, we validate our approach on a challenging large-scale dataset. Compared with previous methods, our method can locate the coordinates of a barcode accurately and quickly and enhance decoding rate through distortion removal. In addition, the storage and memory overheads of our model are reduced through model compression, which shows great potential in industrial applications.

Geometric distortions in FMCW SAR images due to inaccurate knowledge of electronic radar parameters: analysis and correction by means of corner reflectors

In the last years the Frequency Modulated Continuous Wave (FMCW) technology has been playing an ever greater role in the realization of compact, light and cheap Synthetic Aperture Radar (SAR) systems to be mounted onboard small, low altitude platforms such as airplanes, helicopters and drones.To correctly focus FMCW SAR images, it is necessary to accurately know some system parameters, including the frequency sweep rate of the signal transmitted by the radar. It may happen, however, that this frequency sweep rate is not very accurately measured by the radar provider, and thus an incorrect value of this parameter is used during the SAR data focusing procedure. This may produce serious geometric distortion effects in the focused FMCW SAR images. To circumvent these problems, in this work we present a procedure that estimates the frequency sweep rate actually employed by the FMCW radar, thus providing a key information that can be then profitably used to achieve the correct focusing of the SAR data acquired by the radar system at hand. More specifically, we propose an algorithm that exploits on one side the focused SAR images corrupted by the geometric distortion effects induced by the inaccurate knowledge of this radar parameter, and on the other side the very precise in-situ measurements of the positions of a limited number of Corner Reflectors (CRs) properly deployed over the observed scene.The effectiveness of the proposed algorithm has been tested on real data acquired by an airborne X-band FMCW SAR system.

Optimization of Ground Control Point (GCP) and Independent Control Point (ICP) on Orthorectification of High Resolution Satellite Imagery

In the rapidly evolving technology era, various survey methods have been widely used one of them by remote sensing using satellite. It is known that the satellite image recording process is covered by rides (satellites) moving over the Earth's surface at hundreds of kilometers, causing satellite imagery to have geometric distortion. To reduce the effect of geometric distortion of objects on the image, geometric correction by orthorectification is done. Pleiades is a satellite of high resolution satellite image producer made by Airbus Defense & Space company. The resulting satellite imagery has a 0.5 meter spatial resolution. As a reference for the more detailed space utilization activities of space utilization arranged in the Regional Spatial Plans, Detailed Spatial Plans was created with the 1: 5000 scale map which has been governed by the Geospatial Information Agency. In the process of orthorectifying satellite imagery for this 1: 5000 scale map, ground control or Ground Control Point (GCP) is used for geometric correction and Digital Elevation Model (DEM) data. In this research, the optimal number of GCP usage for orthorectification process in Rational Function method is 21 GCP using 2nd order polynomial

Dose evaluation of MRI-based synthetic CT generated using a machine learning method for prostate cancer radiotherapy

Magnetic resonance imaging (MRI)-only radiotherapy treatment planning is attractive since MRI provides superior soft tissue contrast over computed tomographies (CTs), without the ionizing radiation exposure. However, it requires the generation of a synthetic CT (SCT) from MRIs for patient setup and dose calculation. In this study, we aim to investigate the accuracy of dose calculation in prostate cancer radiotherapy using SCTs generated from MRIs using our learning-based method. We retrospectively investigated a total of 17 treatment plans from 10 patients, each having both planning CTs (pCT) and MRIs acquired before treatment. The SCT was registered to the pCT for generating SCT-based treatment plans. The original pCT-based plans served as ground truth. Clinically-relevant dose volume histogram (DVH) metrics were extracted from both ground truth and SCT-based plans for comparison and evaluation. Gamma analysis was performed for the comparison of absorbed dose distributions between SCT- and pCT-based plans of each patient. Gamma analysis of dose distribution on pCT and SCT within 1%/1 mm at 10% dose threshold showed greater than 99% pass rate. The average differences in DVH metrics for planning target volumes (PTVs) were less than 1%, and similar metrics for organs at risk (OAR) were not statistically different. The SCT images created from MR images using our proposed machine learning method are accurate for dose calculation in prostate cancer radiation treatment planning. This study also demonstrates the great potential for MRI to completely replace CT scans in the process of simulation and treatment planning. However, MR images are needed to further analyze geometric distortion effects. Digitally reconstructed radiograph (DRR) can be generated within our method, and their accuracy in patient setup needs further analysis.

Technical challenges of quantitative chest MRI data analysis in a large cohort pediatric study

ObjectivesThis study was conducted in order to evaluate the effect of geometric distortion (GD) on MRI lung volume quantification and evaluate available manual, semi-automated, and fully automated methods for lung segmentation.MethodsA phantom was scanned with MRI and CT. GD was quantified as the difference in phantom’s volume between MRI and CT, with CT as gold standard. Dice scores were used to measure overlap in shapes. Furthermore, 11 subjects from a prospective population-based cohort study each underwent four chest MRI acquisitions. The resulting 44 MRI scans with 2D and 3D Gradwarp were used to test five segmentation methods. Intraclass correlation coefficient, Bland–Altman plots, Wilcoxon, Mann–Whitney U, and paired t tests were used for statistics.ResultsUsing phantoms, volume differences between CT and MRI varied according to MRI positions and 2D and 3D Gradwarp correction. With the phantom located at the isocenter, MRI overestimated the volume relative to CT by 5.56 ± 1.16 to 6.99 ± 0.22% with body and torso coils, respectively. Higher Dice scores and smaller intraobject differences were found for 3D Gradwarp MR images. In subjects, semi-automated and fully automated segmentation tools showed high agreement with manual segmentations (ICC = 0.971–0.993 for end-inspiratory scans; ICC = 0.992–0.995 for end-expiratory scans). Manual segmentation time per scan was approximately 3–4 h and 2–3 min for fully automated methods.ConclusionsVolume overestimation of MRI due to GD can be quantified. Semi-automated and fully automated segmentation methods allow accurate, reproducible, and fast lung volume quantification. Chest MRI can be a valid radiation-free imaging modality for lung segmentation and volume quantification in large cohort studies.Key Points• Geometric distortion varies according to MRI setting and patient positioning.• Automated segmentation methods allow fast and accurate lung volume quantification.• MRI is a valid radiation-free alternative to CT for quantitative data analysis.

A MATCHING METHOD TO REDUCE THE INFLUENCE OF SAR GEOMETRIC DEFORMATION

Abstract. There are large geometrical deformations in SAR image, including foreshortening, layover, shade，which leads to SAR Image matching with low accuracy. Especially in complex terrain area, the control points are difficult to obtain, and the matching is difficult to achieve. Considering the impact of geometric distortions in SAR image pairs, a matching algorithm with a combination of speeded up robust features (SURF) and summed of normalize cross correlation (SNCC) was proposed, which can avoid the influence of SAR geometric deformation. Firstly, SURF algorithm was utilized to predict the search area. Then the matching point pairs was selected based on summed of normalized cross correlation. Finally, false match points were eliminated by the bidirectional consistency. SURF algorithm can control the range of matching points, and the matching points extracted from the deformation area are eliminated, and the matching points with stable and even distribution are obtained. The experimental results demonstrated that the proposed algorithm had high precision, and can effectively avoid the effect of geometric distortion on SAR image matching. Meet accuracy requirements of the block adjustment with sparse control points.

Effects of geometric distortions, Gaussian blur, and contrast negation on recognition of familiar faces

ABSTRACTIt is assumed that “configural processing” is important for recognizing people whom we know. Studies have shown better discrimination of relational changes between facial features when faces are presented upright than upside down and when presented as photographic negatives. However, studies have also demonstrated tolerance for complex changes to facial configuration of familiar faces when images are geometrically distorted. In two experiments, we explored effects of linear stretching, Gaussian blur, and contrast negation on recognition of familiar or unfamiliar faces (Experiment 1) and familiar or unfamiliar company brand logos (Experiment 2). Only contrast negation severely impaired recognition of familiar faces but not unfamiliar faces or company brand logos. Effects of contrast negation were additional to linear stretching, whereas linear stretching independently had no impact on recognition. These findings highlight an important deficit in the recognition of familiar faces caused by contrast negation.

An ultra-high field strength MR image-guided robotic needle delivery system for in-bore small animal interventions.

The purpose of this study was to develop and validate an image-guided robotic needle delivery system for accurate and repeatable needle targeting procedures in mouse brains inside the 12 cm inner diameter gradient coil insert of a 9.4 T MR scanner. Many preclinical research techniques require the use of accurate needle deliveries to soft tissues, including brain tissue. Soft tissues are optimally visualized in MR images, which offer high-soft tissue contrast, as well as a range of unique imaging techniques, including functional, spectroscopy and thermal imaging, however, there are currently no solutions for delivering needles to small animal brains inside the bore of an ultra-high field MR scanner. This paper describes the mechatronic design, evaluation of MR compatibility, registration technique, mechanical calibration, the quantitative validation of the in-bore image-guided needle targeting accuracy and repeatability, and demonstrated the system's ability to deliver needles in situ. Our six degree-of-freedom, MR compatible, mechatronic system was designed to fit inside the bore of a 9.4 T MR scanner and is actuated using a combination of piezoelectric and hydraulic mechanisms. The MR compatibility and targeting accuracy of the needle delivery system are evaluated to ensure that the system is precisely calibrated to perform the needle targeting procedures. A semi-automated image registration is performed to link the robot coordinates to the MR coordinate system. Soft tissue targets can be accurately localized in MR images, followed by automatic alignment of the needle trajectory to the target. Intra-procedure visualization of the needle target location and the needle were confirmed through MR images after needle insertion. The effects of geometric distortions and signal noise were found to be below threshold that would have an impact on the accuracy of the system. The system was found to have negligible effect on the MR image signal noise and geometric distortion. The system was mechanically calibrated and the mean image-guided needle targeting and needle trajectory accuracies were quantified in an image-guided tissue mimicking phantom experiment to be 178 ± 54 μm and 0.27 ± 0.65°, respectively. An MR image-guided system for in-bore needle deliveries to soft tissue targets in small animal models has been developed. The results of the needle targeting accuracy experiments in phantoms indicate that this system has the potential to deliver needles to the smallest soft tissue structures relevant in preclinical studies, at a wide variety of needle trajectories. Future work in the form of a fully-automated needle driver with precise depth control would benefit this system in terms of its applicability to a wider range of animal models and organ targets.

EFFECTS OF X-RAY BEAM ANGLE AND GEOMETRIC DISTORTION ON WIDTH OF EQUINE THORACOLUMBAR INTERSPINOUS SPACES USING RADIOGRAPHY AND COMPUTED TOMOGRAPHY-A CADAVERIC STUDY.

The widths of spaces between the thoracolumbar processi spinosi (interspinous spaces) are frequently assessed using radiography in sports horses; however effects of varying X-ray beam angles and geometric distortion have not been previously described. The aim of this prospective, observational study was to determine whether X-ray beam angle has an effect on apparent widths of interspinous spaces. Thoracolumbar spine specimens were collected from six equine cadavers and left-right lateral radiographs and sagittal and dorsal reconstructed computed tomographic (CT) images were acquired. Sequential radiographs were acquired with each interspinous space in focus. Measurements were performed for each interspinous space in the focus position and up to eight angled positions as the interspinous space moved away from focus (±). Focus position measurements were compared to matching sagittal CT measurements. Effect of geometric distortion was evaluated by comparing the interspinous space in radiographs with sagittal and dorsal reconstructed CT images. A total of 49 interspinous spaces were sampled, yielding 274 measurements. X-ray beam angle significantly affected measured width of interspinous spaces in position +3 (P = 0.038). Changes in width did not follow a consistent pattern. Interspinous space widths in focus position were significantly smaller in radiographs compared to matching reconstructed CT images for backs diagnosed with kissing spine syndrome (P < 0.001). Geometric distortion markedly affected appearance of interspinous space width between planes. In conclusion, X-ray beam angle and geometric distortion influence radiographically measured widths of interspinous spaces in the equine thoracolumbar spine, and this should be taken into consideration when evaluating sport horses.

Simulation on the Measurement Method of Geometric Distortion of Telescopes

The accurate measurement on the effect of telescope geometric distortion is conducive to improving the astrometric positioning accuracy of telescopes, which is of significant importance for many disciplines of astronomy, such as stellar clusters, natural satellites, asteroids, comets, and other celestial bodies in the solar system. For this reason, the predecessors have developed an iterative self-calibration method to measure the telescope geometric distortion by dithering observations in a dense star field, and achieved fine results. However, the previous work did not make constraints on the density of star field, and the dithering mode, but chose empirically some good conditions (for example, a denser star field and a larger dithering number) to observe, which took up much observing time, and caused a rather low efficiency. In order to explore the validity of the self-calibration method, and optimize its observational conditions, it is necessary to carry out the corresponding simulations. In this paper, we introduce first the self-calibration method in detail, then by the simulation method, we verify the effectiveness of the self-calibration method, and make further optimizations on the observational conditions, such as the density of star field and the dithering number, to achieve a higher accuracy of geometric distortion measurement. Finally, taking consideration of the practical application for correcting the geometric distortion effect, we have analyzed the relationship between the number of reference stars in the field of view and the astrometric accuracy by virtue of the simulation method.

Image-based general-relativistic visualization

Ego-centric, or first-person, visualization is a valuable tool for an introductory course in general relativity as well as for public outreach to provide a deeper understanding of the geometric distortion effects due to curved spacetime. To enhance this process, interactive visualization allows us to scrutinize the effects in more detail, as the student can change the parameters and see how they influence the visual result without delays. The image-based technique, borrowed from special relativity, is restricted to scenes where all objects can be considered to be infinitely far away, such that one has to deal only with panorama images. While the accompanying Java application can be used already in beginning classes to teach general relativity, the underlying technical details are addressed to the more advanced student who is also interested in implementation details.

SU‐E‐J‐205: Dose Distribution Differences Caused by System Related Geometric Distortion in MRI‐Guided Radiation Treatment System

Purpose:MRI has superb soft tissue contrast but is also known for geometric distortions. The concerns and uncertainty about MRI's geometric distortion have contributed to the hesitation of using only MRI for simulation in radiation therapy. There are two major categories of geometric distortion in MRI; system related and patient related. In this presentation, we studied the impact of system‐related geometric distortion on dose distribution in a digital body phantom under an MR‐Linac environment.Methods:Residual geometric distortion (after built‐in geometric correction) was modeled based on phantom measurements of the system‐related geometric distortions of a MRI scanner of a combined MR guided Radiation Therapy (MRgRT) system. A digital oval shaped phantom (40×25 cm) as well as one ellipsoid shaped tumor volume was created to simulate a simplified human body. The simulated tumor volume was positioned at several locations between the isocenter and the body surface. CT numbers in HUs that approximate soft tissue and tumor were assigned to the respective regions in the digital phantom. To study the effect of geometric distortion caused by system imperfections, an IMRT plan was optimized with the distorted image set with the B field. Dose distributions were re‐calculated on the undistorted image set with the B field (as in MR‐Linac).Results:The maximum discrepancies in both body contour and tumor boundary was less than 2 mm, which leads to small dose distribution change. For the target in the center, coverage was reduced from 98.8% (with distortion) to 98.2%; for the other peripheral target coverage was reduced from 98.4% to 95.9%.Conclusion:System related geometric distortions over the 40×25 area were within 2mm and the resulted dosimetric effects were minor for the two tumor locations in the phantom. Patient study will be needed for further investigation.The authors received a corporate research grant from Elekta

Theoretical Study of HOCl-Catalyzed Keto–Enol Tautomerization of β-Cyclopentanedione in an Explicit Water Environment

The mechanism of acid-catalyzed keto-enol tautomerization of β-cyclopentanedione (CPD) in solution is studied computationally. Reaction profiles are first calculated for a limited solvation environment using ab initio and density functional methods. Barrier heights for systems including up to one hydration shell of explicit water molecules depend strongly on the number of waters involved in proton transfer and to a lesser but significant extent on the number of waters forming hydrogen bonds with waters in the proton-transfer chain (each such water reduces the barrier by 4.4 kcal/mol on average). Barriers of 8-13 kcal/mol were obtained when a full or nearly full hydration shell was present, consistent with calculations for nonacid-catalyzed keto-enol tautomerization of related molecules. The presence of HOCl reduced the barrier by 4.5 kcal/mol in relation to the gas phase, consistent with the well-known principle that keto-enol tautomerization can be acid- or base-catalyzed. The reaction was also modeled beginning with snapshots of reactant conformations taken from a 300 K molecular dynamics simulation of CPD, HOCl, and 324 explicit waters. Reaction profiles were calculated at a QM/MM level with waters in the first hydration shell either fixed or energy-minimized at each step along the reaction coordinate. A substantial variation in barrier height was observed in both cases, depending primarily on electrostatic interactions (hydrogen bonding) with first-hydration-shell waters and, to a lesser extent, on electrostatic interactions with more distant waters and geometric distortion effects. For the lowest barriers, the extent of barrier reduction by waters involved in proton transfer is consistent with the limited solvation results, but further barrier reduction due to hydrogen bonding to waters involved in proton transfer is not observed. It is postulated that this is because highly flexible structures such as extensive hydrogen bonding networks optimal for reaction are entropically disfavored and so may not contribute significantly to the observed reaction rate.

Experimental study on effects of geometric distortion upon suspended sediments in bending channels

Different geometries of bending channels are set up without distortion and with distortion ratios of 2, 4, 6, 8 and 10 in order to study its influence on bed deformation induced by suspended sediment transport in these channels. Experiment results show that the kinematics of suspended sediment is inversely proportional to the distortion ratio of the physical model, but proportional to the width–depth ratio and curvature ratio. The similar bed deformation to that of the non-distorted model is only observed in the distorted models with distortion ratios of not more than 4 and width–depth ratios of not less than 6.3. It is recommended that the geometric distortion ratio be less than 4 in order to meet the similarity requirements of river bed deformation in bending channels. With the same distortion ratio, deviation of bed deformation was observed more in the bending reaches than in the straight ones and more with a fixed convex bank than with a mobile convex bank. The geometric distortion affects the river bed deformation in the model, i.e., the amount of deposition and erosion and the profiles of river bed deformation in longitude and transverse directions.

A theoretical analysis of chemical bonding, vibronic coupling, and magnetic anisotropy in linear iron(ii) complexes with single-molecule magnet behavior

The electronic structure and magnetic anisotropy of six complexes of high-spin FeII with linear FeX2 (X = C, N, O) cores, Fe[N(SiMe3)(Dipp)]2 (1), Fe[C(SiMe3)3]2 (2), Fe[N(H)Ar′]2 (3), Fe[N(H)Ar*]2 (4), Fe[O(Ar′)]2 (5), and Fe[N(t-Bu)2]2 (7) [Dipp = C6H3-2,6-Pri2; Ar′ = C6H3-2,6-(C6H3-2,6-Pri2)2; Ar* = C6H3-2,6-(C6H2-2,4,6-Pri2)2; Ar# = C6H3-2,6-(C6H2-2,4,6-Me3)2], and one bent (FeN2) complex, Fe[N(H)Ar#]2 (6), have been studied theoretically using complete active space self-consistent field (CASSCF) wavefunctions in conjunction with N-Electron Valence Perturbation Theory (NEVPT2) and quasidegenerate perturbation theory (QDPT) for the treatment of magnetic field and spin-dependent relativistic effects. Mossbauer studies on compound 2 indicate an internal magnetic field of unprecedented magnitude (151.7 T) at the FeII nucleus. This has been interpreted as arising from first order angular momentum of the 5Δ ground state of FeII center (J. Am. Chem. Soc. 2004, 126, 10206). Using geometries from X-ray structural data, ligand field parameters for the Fe-ligand bonds were extracted using a 1 : 1 mapping of the angular overlap model onto multireference wavefunctions. The results demonstrate that the metal–ligand bonding in these complexes is characterized by: (i) strong 3dz2–4s mixing (in all complexes), (ii) π-bonding anisotropy involving the strong π-donor amide ligands (in 1, 3–4, 6, and 7) and (iii) orbital mixings of the σ–π type for Fe–O bonds (misdirected valence in 5). The interplay of all three effects leads to an appreciable symmetry lowering and splitting of the 5Δ (3dxy, 3dx2−y2) ground state. The strengths of the effects increase in the order 1 < 5 < 7 ∼ 6. However, the differential bonding effects are largely overruled by first-order spin–orbit coupling, which leads to a nearly non-reduced orbital contribution of L = 1 to yield a net magnetic moment of about 6 μB. This unique spin–orbital driven magnetism is significantly modulated by geometric distortion effects: static distortions for the bent complex 6 and dynamic vibronic coupling effects of the Renner–Teller type of increasing strength for the series 1–5.Ab initio calculations based on geometries from X-ray data for 1 and 2 reproduce the magnetic data exceptionally well. Magnetic sublevels and wavefunctions were calculated employing a dynamic Renner–Teller vibronic coupling model with vibronic coupling parameters adjusted from the ab initio results on a small Fe(CH3)2 truncated model complex. The model reproduces the observed reduction of the orbital moments and quantitatively reproduces the magnetic susceptibility data of 3–5 after introduction of the vibronic coupling strength (f) as a single adjustable parameter. Its value varies in a narrow range (f = 0.142 ± 0.015) across the series. The results indicate that the systems are near the borderline of the transition from a static to a dynamic Renner–Teller effect. Renner–Teller vibronic activity is used to explain the large reduction of the spin-reversal barrier Ueff along the series from 1 to 5. Based upon the theoretical analysis, guidelines for generating new single-molecule magnets with enhanced magnetic anisotropies and longer relaxation times are formulated.

Preliminary results of solving the problem of geometric distortion for the 2.4 m telescope at Yunnan Observatory

We observed the open clusters NGC 1664 (43 exposures) and M35 (42 exposures) by the Yunnan Faint Object Spectrograph and Camera in the 2.4 m telescope at Yunnan Astronomical Observatory on 2011 January 3, and processed them by a method recently proposed by us. The result shows that there is a geometric distortion effect in the field of view and the maximum distortion is ∼ 0.25″ (i.e. 1 pixel). After correcting the geometric distortion, the precision of stellar positional measurement is significantly improved. The best precision in each direction is 6 mas for well-exposed stars.

The dual-aspect geometric correction method based on DEM using Radarsat-2 data

Synthetic Aperture Radar(SAR) images reveal serious geometric distortions that are caused by terrain undulations.This paper presents a newly developed method on SAR image geometric correction which is the dual-aspect geometric correction based on digital elevation model(DEM) to overcome the inherent shortages of SAR image such as foreshortening,shadow and layover and correct the distorted or lost backscatter coefficient values in mountainous area.The Radarsat-2 SAR images were used in this study.The results show that this method can effectively eliminate the effect of geometric distortions and compensate the lost or distorted backscatter coefficients,especially is useful for eliminating layover and shadow distortions in SAR images.This method solves the geometric correction problem that cannot be solved with single SAR image.