High-resolution polarimetric SAR image decomposition of urban areas based on a POA correction method

Polarimetric decomposition in urban areas is important for monitoring the speed of city expansion and studying its ecological environmental influence. Using fully Polarimetric Synthetic Aperture Radar (PolSAR) is a way to keep large range urban change under observation. PolSAR images allow us to detect the scattering mechanisms using polarimetric target decomposition methods. Much of the research on decomposition methods has stated that the polarization orientation angle (POA) would affect the result of decomposition. The available deorientation methods cannot rotate built-up areas with large POAs. As a result, some urban areas are still misjudged as volume scattering dominant. In this paper, an algorithm for decomposition of high-resolution urban area images based on a POA correction method is proposed. First, for high-resolution images of built-up areas, the POA changes radically pixel by pixel. An approximate assessment of urban areas can be done using POA randomness. Then, in order to search out the true POAs of large dominant POA areas (most built-up regions), the linear approximation method is used to locate POAs that can minimize the cross-polarized term. Thereby, the inaccurate decomposition that occurs by the deviation of POA can be fixed, and the accuracy of the results is improved.     

A polarimetric SAR internal calibration scheme for polarization crosstalk

The system of polarimetric SAR is introduced and internal calibration schemes are discussed. The measurement method of crosstalk between horizontal (H) and vertical (V) polarization channels using internal calibration loops is proposed. Couplers at H and V polarization antennas are designed to hold different coupling factors to make the crosstalk measurable. The compensation model for the polarization scattering matrix is proposed and discussed. As a result, the crosstalk can be tracked with internal calibration and the polarization scattering matrix can be compensated. Simulations are conducted to research the measurement accuracy of crosstalk.     

Fusion of polarimetric and texture information for urban building extraction from fully polarimetric SAR imagery

Building extraction from remote sensing images is very important in many fields, such as urban planning, land use investigation, damage assessment, and so on. In polarimetric synthetic aperture radar (PolSAR) imagery, the buildings not only have typical polarimetric features but also have rich texture features. In this paper, the texture information is introduced to improve the accuracy of urban building extraction from PolSAR imagery by a new method called cross reclassification. Based on this method, the polarimetric information-based results and texture-based results can be effectively fused. The experimental results of three representative PolSAR images with different characteristics demonstrate the effectiveness of the proposed method, and the accuracy of building extraction can be improved, compared with the traditional method using only polarimetric information.     

A multi-depth convolutional neural network for SAR image classification

The convolutional neural network has been widely used in synthetic aperture radar (SAR) image classification, for it can learn discriminative features from massive amounts of data. However, it is short of distinctive learning mechanisms for different regions in SAR images. In this letter, a novel architecture called multi-depth convolutional neural network (Multi-depth CNN) is proposed which can select different levels of features for classification. Differing from classical convolutional neural network, Multi-depth CNN adopts a piecewise back-propagation method to optimize the network. Meanwhile, compared with classical convolutional neural network, the proposed network can reduce the training time effectively. Experimental results on two datasets demonstrate that the proposed network can achieve better classification accuracy compared with some state-of-art algorithms.     

A level set method for segmentation of high-resolution polarimetric SAR images using a heterogeneous clutter model

To overcome the problem of strong speckle and texture in high-resolution polarimetric synthetic aperture radar (PolSAR) images, a novel level set segmentation method that uses a heterogeneous clutter model is proposed in this article. Because the KummerU distribution has the capability to describe the statistics of PolSAR imagery in both homogeneous and heterogeneous scenes, it is used to replace the traditional Wishart distribution as the statistical model that defines the energy function for PolSAR images in order to improve the accuracy of the segmentation. Moreover, in order to reduce the computation intensity, an enhanced distance-regularized level set evolution (DRLSE-E) term is applied to improve the computational efficiency. The experimental results obtained using synthetic and real PolSAR images show that the method described has an accuracy 10% better than level set methods based on Wishart distributions. It is also shown that adding the DRLSE-E term reduces the computation time by about a third, thus demonstrating the effectiveness of our method.     

A strategy for selecting among alternative models for continuous longitudinal data

Linear mixed models (LMMs) can be used to analyze continuous longitudinal response variables of research studies. Specific aims are then addressed through tests of fixed effects comparing means. However, generated fixed effects results can vary according to the choice of the covariance structure, and so strategies for selecting a model should be utilized first to identify an appropriate covariance structure. We describe alternative LMMs for analyzing continuous longitudinal data and discuss a strategy for using model selection criteria to choose among those models. This is accomplished through the analysis of an exemplar data set considering a wide variety of alternative models for the means, variances, and correlations. © 2012 Wiley Periodicals, Inc. Res Nurs Health 35:647–658, 2012     

A disentangled generative model for disease decomposition in chest X-rays via normal image synthesis

The interpretation of medical images is a complex cognition procedure requiring cautious observation, precise understanding/parsing of the normal body anatomies, and combining knowledge of physiology and pathology. Interpreting chest X-ray (CXR) images is challenging since the 2D CXR images show the superimposition on internal organs/tissues with low resolution and poor boundaries. Unlike previous CXR computer-aided diagnosis works that focused on disease diagnosis/classification, we firstly propose a deep disentangled generative model (DGM) simultaneously generating abnormal disease residue maps and “radiorealistic” normal CXR images from an input abnormal CXR image. The intuition of our method is based on the assumption that disease regions usually superimpose upon or replace the pixels of normal tissues in an abnormal CXR. Thus, disease regions can be disentangled or decomposed from the abnormal CXR by comparing it with a generated patient-specific normal CXR. DGM consists of three encoder-decoder architecture branches: one for radiorealistic normal CXR image synthesis using adversarial learning, one for disease separation by generating a residue map to delineate the underlying abnormal region, and the other one for facilitating the training process and enhancing the model’s robustness on noisy data. A self-reconstruction loss is adopted in the first two branches to enforce the generated normal CXR image to preserve similar visual structures as the original CXR. We evaluated our model on a large-scale chest X-ray dataset. The results show that our model can generate disease residue/saliency maps (coherent with radiologist annotations) along with radiorealistic and patient specific normal CXR images. The disease residue/saliency map can be used by radiologists to improve the CXR reading efficiency in clinical practice. The synthesized normal CXR can be used for data augmentation and normal control of personalized longitudinal disease study. Furthermore, DGM quantitatively boosts the diagnosis performance on several important clinical applications, including normal/abnormal CXR classification, and lung opacity classification/detection.     

Statistical shape models for 3D medical image segmentation: A review

Statistical shape models (SSMs) have by now been firmly established as a robust tool for segmentation of medical images. While 2D models have been in use since the early 1990s, wide-spread utilization of three-dimensional models appeared only in recent years, primarily made possible by breakthroughs in automatic detection of shape correspondences. In this article, we review the techniques required to create and employ these 3D SSMs. While we concentrate on landmark-based shape representations and thoroughly examine the most popular variants of Active Shape and Active Appearance models, we also describe several alternative approaches to statistical shape modeling. Structured into the topics of shape representation, model construction, shape correspondence, local appearance models and search algorithms, we present an overview of the current state of the art in the field. We conclude with a survey of applications in the medical field and a discussion of future developments.     

Framework for monitoring the conversion of cultivated land to construction land using SAR image time series

The land cover change from cultivated land to construction land is a world issue since the urbanization process is extensively studied around the world. Chengdu, China, is a representative urbanization area, where cloud cover is very high most of the time, restricting the use of visible and near-infrared satellite data. Here, we present a novel framework for land change monitoring based on synthetic aperture radar (SAR) time series, which comprises three key components: (1) construction of pixel-level SAR image time series; (2) spatio-temporal similarity analysis based on morphological-structural characteristics of time series; and (3) iterative binary partition mean square error model analysis to ascertain change nodes. Experimental results showed that the proposed framework could effectively extract the change nodes and change pixels, with correctness of 85.82% and completeness of 84.78%, outperforming the time-series-only (non-spatial) method, as well as traditional classification methods, and the same framework using shorter Landsat TM image time series.     

Landmark constellation models for medical image content identification and localization

Purpose

Many medical imaging tasks require the detection and localization of anatomical landmarks, for example for the initialization of model-based segmentation or to detect anatomical regions present in an image. A large number of landmark and object localization methods have been described in the literature. The detection of single landmarks may be insufficient to achieve robust localization across a variety of imaging settings and subjects. Furthermore, methods like the generalized Hough transform yield the most likely location of an object, but not an indication whether or not the landmark was actually present in the image.

Methods

For these reasons, we developed a simple and computationally efficient method combining localization results from multiple landmarks to achieve robust localization and to compute a localization confidence measure. For each anatomical region, we train a constellation model indicating the mean relative locations and location variability of a set of landmarks. This model is registered to the landmarks detected in a test image via point-based registration, using closed-form solutions. Three different outlier suppression schemes are compared, two using iterative re-weighting based on the residual landmark registration errors and the third being a variant of RANSAC. The mean weighted residual registration error serves as a confidence measure to distinguish true from false localization results. The method is optimized and evaluated on synthetic data, evaluating both the localization accuracy and the ability to classify good from bad registration results based on the residual registration error.

Results

Two application examples are presented: the identification of the imaged anatomical region in trauma CT scans and the initialization of model-based segmentation for C-arm CT scans with different target regions. The identification of the target region with the presented method was in 96 % of the cases correct.

Conclusion

The presented method is a simple solution for combining multiple landmark localization results. With appropriate parameters, outlier suppression clearly improves the localization performance over model registration without outlier suppression. The optimum choice of method and parameters depends on the expected level of noise and outliers in the application at hand, as well as on the focus on localization, classification, or both. The method allows detecting and localizing anatomical fields of view in medical images and is well suited to support a wide range of applications comprising image content identification, anatomical navigation and visualization, or initializing the pose of organ shape models.

     

A cost-effective alternative to specialty beds for pressure relief

These study findings had an impact upon the costs of pressure relief. In one 28-day period before the inflatable overlays were added to the pressure relief menu, there were 303 patient charges for specialty beds. In contrast, 6 months after the overlays came into use, staff members had been educated and criteria for selection had been established; in a similar 28-day period, there were only 48 charges for specialty beds. Data over time also indicated that those patients who needed specialty beds used them for a shorter period of time and then were transferred onto an inflatable overlay. This decrease in patient charges resulted in an annual savings of more than $200,000. More important than the cost factor, however, is the benefit the inflatable overlay has provided those patients who are at risk for the development or extension of impaired skin by significantly relieving pressure.     

A novel method for reliable and fast extraction of neuronal EEG/MEG oscillations on the basis of spatio-spectral decomposition

Neuronal oscillations have been shown to underlie various cognitive, perceptual and motor functions in the brain. However, studying these oscillations is notoriously difficult with EEG/MEG recordings due to a massive overlap of activity from multiple sources and also due to the strong background noise. Here we present a novel method for the reliable and fast extraction of neuronal oscillations from multi-channel EEG/MEG/LFP recordings. The method is based on a linear decomposition of recordings: it maximizes the signal power at a peak frequency while simultaneously minimizing it at the neighboring, surrounding frequency bins. Such procedure leads to the optimization of signal-to-noise ratio and allows extraction of components with a characteristic "peaky" spectral profile, which is typical for oscillatory processes. We refer to this method as spatio-spectral decomposition (SSD). Our simulations demonstrate that the method allows extraction of oscillatory signals even with a signal-to-noise ratio as low as 1:10. The SSD also outperformed conventional approaches based on independent component analysis. Using real EEG data we also show that SSD allows extraction of neuronal oscillations (e.g., in alpha frequency range) with high signal-to-noise ratio and with the spatial patterns corresponding to central and occipito-parietal sources. Importantly, running time for SSD is only a few milliseconds, which clearly distinguishes it from other extraction techniques usually requiring minutes or even hours of computational time. Due to the high accuracy and speed, we suggest that SSD can be used as a reliable method for the extraction of neuronal oscillations from multi-channel electrophysiological recordings.     

Construction of nano-sized FOX-7/ZIF-8 composites for fast decomposition and reduced sensitivity

Herein, novel nano-sized 1,1-diamino-2,2-dinitroethylene (C₂H₄N₄O₄, FOX-7)/zeolitic imidazolate framework-8 (ZIF-8) composites are constructed by facile liquid-assisted mechanochemical reactions. In contrast to two-step thermal decomposition of raw FOX-7, the prepared FOX-7/ZIF-8 composites demonstrate a single high-intensity exothermal decomposition attributed to the catalysis of ZIF-8. Benefiting from nano-sized energetic materials and the buffering effect of ZIF-8, the mechanical sensitives of FOX-7/ZIF-8 composites are decreased.

Nano-sized FOX-7/ZIF-8 composites are successfully prepared by a liquid-assisted mechanochemical route. They exhibited fast decomposition and reduced mechanical sensitivities.

Energetic materials are a class of material with high amount of stored chemical energy that can be released.^1–3 They represent one of the crucial functional materials which are widely used in military and civil applications. According to their different uses, energetic materials can be classified as propellants, explosives, and pyrotechnics. Exploitation of novel energetic materials is a long-term strategic task, and the common requirements include high energy, low sensitivity, fast decomposition, easy preparation.1,1-Diamino-2,2-dinitroethylene (C₂H₄N₄O₄, FOX-7) has received extensive attention as a high energy material with a density of 1.878 g cm⁻³ and a heat of formation of 133.7 kJ mol⁻¹ since it was synthesized firstly by Latypov et al. in 1998.^4–8 Pioneering researches have been continuously carried out on fabrication of FOX-7 based composites to modify its properties for practical applications. Klapötke et al. reported FOX-7 hosted in MFI-type zeolite for detection purposes.^9,10 Huang et al. studied the FOX-7 embedded in mesoporous carbon FDU-15, showing the extreme insensitivity close to that of FDU-15.¹¹ Fu et al. constructed nano graphene oxide–metal–FOX-7 composites to promote complete thermal decomposition of FOX-7.¹² Li et al. prepared FOX-7/F₂₆₀₂ PBX¹³ and FOX-7/viton microspheres¹⁴ with improved thermal stability. Some formulations containing FOX-7 exhibited good application performance in the field of solid propellant.^12,15,16 However, FOX-7 and most its composites undergo two-steps thermal decomposition at gradually elevated temperature, which is markedly different from other high energy materials, such as 1,3,5-trinitro-1,3,5-triazine (RDX), 1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX), hexanitrohexaazaisowurtzitane (CL-20). Compared with single-step process, two-steps decomposition tends to reduce the energy release efficiency of FOX-7, and increase the energy loss. Hence, design and construction of FOX-7 based composites, that can convert two-steps decomposition into a single-step process, is desired for developing novel solid propellants.Metal–organic frameworks (MOFs), emerging as a representative class of crystalline porous materials with adjustable pore structure, regular channels, abundant interaction sites, diverse composition, attract a surge of attention to be hosting matrixes for host–guest chemistry.^17–19 An attractive aspect of MOF materials lies in the facts that they not only can retain the individual functions, but also often exhibit novel properties derived from blending of the individuals.²⁰ Benefiting from the abundant nano-sized cavities and regular pores, MOFs host can act as confinement to avoid the aggregation of guest molecules. Encapsulation of FOX-7 within the pores of MOFs may provide a promising way to construct nano-sized energetic materials, which showed decreased sensitivities compared with micro-sized ones.^21,22 Additionally, metal species and organic linkers of MOFs host would participate in the thermal decomposition of guest, thus it is expected to regulate decomposition process of FOX-7.In this work, we report a utilization of a liquid-assisted mechanochemical route for the construction of FOX-7/MOF composite materials. Liquid-assisted mechanochemical milling was conducted as an alternative to the conventional solution-based strategy because of its priority in composition control of guest species and size reduction effect.^23–25 A chemically stable zeolitic imidazolate framework-8 (ZIF-8) was used as prototype MOF material due to its easy and efficient preparation process. The resulting FOX-7/ZIF-8 composites were completely characterized by FT-IR, powder X-ray diffraction analysis (XRD), nitrogen adsorption/desorption measurements, and scanning electron microscopy (SEM). Furthermore, the thermal behaviour and mechanical sensitivities of these composites were investigated.The FOX-7/ZIF-8 composites were prepared by easily liquid-assisted mechanochemical reactions (Scheme 1). Commercial Zn(OH)₂ powder was used as the zinc source to react with 2-methylimidazole (HMeIM) in the presence of FOX-7 at room temperature for 4 h. During this process, FOX-7 in situ merged with generated ZIF-8. After washing with ethanol and drying, homogeneous yellow powders were generated as desired composites. To investigate the effect of the proportions of FOX-7 to ZIF-8 on the properties of the obtained FOX-7/ZIF-8 composites, various molar ratios of FOX-7 to Zn(OH)₂, HMeIM were used as starting materials, and the resulting materials were named as FOX-7/ZIF-8 (I) [FOX-7 : Zn(OH)₂ : HMeIM = 1 : 1 : 8], FOX-7/ZIF-8 (II) [FOX-7 : Zn(OH)₂ : HMeIM = 1 : 1.5 : 12], FOX-7/ZIF-8 (III) [FOX-7 : Zn(OH)₂ : HMeIM = 1 : 2 : 16], respectively.Open in a separate windowScheme 1Synthesis route for FOX-7/ZIF-8 composites.The FT-IR spectra of FOX-7/ZIF-8 composites were shown in Fig. 1a. The peaks at ∼3406, ∼3298, ∼1636 cm⁻¹ were ascribed to the –NH₂, and the peaks at ∼1524, ∼1472 cm⁻¹ were related to the –NO₂ of FOX-7.²⁶ The peaks at ∼1308, ∼1145 cm⁻¹ could be attributed to the C–N bands in the imidazole groups,²⁷ and the peaks at ∼760, ∼692 cm⁻¹ demonstrated the presence of the Zn–O and Zn–N bonds.²⁸ The existence of these peaks proved the successful assembly of FOX-7, zinc and HMeIM. XRD was performed to examine the crystallinity of the composites (Fig. 1b). The characteristic peaks at 2θ = 7.3°, 10.4°, 12.7°, 14.8°, 16.4° were corresponding to 110, 200, 211, 220, and 310 planes of ZIF-8, respectively.²⁹ The presence of these strong peaks confirmed a high crystallinity of ZIF-8 in the structure of as-prepared FOX-7/ZIF-8 composites. The peaks observed at 2θ = 20.1°, 26.8°, 28.1° supported the presence of FOX-7 with good crystallinity, which are assigned to its 111, 020, 021 planes, respectively.^14,30 The elemental analysis results showed the content of FOX-7 in composites gradually decreased in FOX-7/ZIF-8 (I) to FOX-7/ZIF-8 (III) (Table S1^†).Open in a separate windowFig. 1(a) IR spectra, (b) XRD patterns, (c) nitrogen adsorption/desorption isotherms of FOX-7/ZIF-8 composites. SEM images of (d) FOX-7/ZIF-8 (I), (e) FOX-7/ZIF-8 (II), (f) FOX-7/ZIF-8 (III).Nitrogen sorption isotherms were collected at 77 K to evaluate the porosity of liquid-assisted mechanochemically prepared ZIF-8 and FOX-7/ZIF-8 composites (Fig. 1c and S1^†). All samples displayed type-IV isotherms. Owing to the space-occupying of FOX-7 in the cages of ZIF-8, the Brunauer–Emmett–Teller (BET) surface areas decreased from 1110 m² g⁻¹ (ZIF-8) to 921 m² g⁻¹ [FOX-7/ZIF-8 (III)], 868 m² g⁻¹ [FOX-7/ZIF-8 (II)], 659 m² g⁻¹ [FOX-7/ZIF-8 (I)], respectively (Table S2^†). SEM image of liquid-assisted mechanochemically prepared ZIF-8 exhibited roughly dodecahedron structure with relatively uniform distribution of crystal particle size (Fig. S2^†). For FOX-7/ZIF-8 composites, the SEM images showed the ordered structure of ZIF-8 was remained mostly (Fig. 1d–f). And some particles were distributed around ZIF-8 due to the presence of FOX-7 in nanoscale size. These results indicated the structural integrity of the ZIF-8 framework with introduction of nano-sized FOX-7. The presence of ZIF-8 was expected to improve the stability of composites due to its buffering effect.The thermal behaviour of FOX-7/ZIF-8 composites were studied by using differential scanning calorimetry (DSC) measurements at a heating rate of 5 °C min⁻¹ (Fig. 2). Particularly, raw FOX-7 was used as a control. As the temperate was increased above 200 °C, all samples underwent decomposition without melting. DSC thermogram of pure FOX-7 exhibited two decomposition steps. The initial decomposition peak was observed at ∼223 °C, which was attributed to the emergence of nitro-to-nitrite rearrangement and the destruction of conjugated system and hydrogen bonds.³¹ And the second exothermal peak at ∼283 °C was ascribed to the fracture of carbon skeleton in FOX-7 molecule. In contrast, the DSC thermogram of FOX-7/ZIF-8 (I) indicated a single high-intensity exothermal peak at ∼206 °C. The peak intensity was much greater than each exothermal peak of FOX-7. It demonstrated the catalytic effect of ZIF-8 on the exothermic decomposition of FOX-7. Converting two-steps decomposition into single-step is conducive to improving the energy release efficiency and reducing the energy loss in the exothermic process of energetic materials. Analogously, the DSC thermogram of FOX-7/ZIF-8 (II) and FOX-7/ZIF-8 (III) also showed one-step decomposition peak at ∼205 and ∼202 °C, respectively. The gradual decrease in peak intensities were due to the reduction of FOX-7 content. Furthermore, equivalent physical mixture of FOX-7 and Zn(OH)₂ [denoted as FOX-7 + Zn(OH)₂] afforded two exothermic peaks similar to FOX-7 (Fig. S3^†), and equivalent physical mixture of FOX-7 and ZIF-8 (denoted as FOX-7 + ZIF-8) afforded a single exothermic peak similar to FOX-7/ZIF-8 composites (Fig. S4^†). It showed the unique catalytic effect of ZIF-8 beyond inorganic zinc salt.Open in a separate windowFig. 2DSC curves of raw FOX-7 and FOX-7/ZIF-8 composites at a heating rate of 5 °C min⁻¹.To explore the possible microstructure of FOX-7/ZIF-8 composites and the reason for the difference of exothermic behaviour between raw FOX-7 and FOX-7/ZIF-8 composites, studies on structural modeling and ab initio molecular dynamics simulation (AIMD) were conducted. FOX-7 molecules were inserted into the cages of ZIF-8 according to appropriate density, affording proposed FOX-7/ZIF-8 Periodic cell structure with 3–4 FOX-7 molecules in each cage (Fig. 3a). The energy of the proposed FOX-7/ZIF-8 structure converged successfully through first-principles optimization, and the structural configuration was maintained through relaxation for 5 ps at 300 K. It demonstrated the thermodynamics and kinetics of the proposed FOX-7/ZIF-8 structure are stable. Notably, the FOX-7 molecules in the cages were no longer planar accumulation due to the van der Waals interactions with surrounding molecules in cages.Open in a separate windowFig. 3(a) Schematic diagram of theoretical model structure of FOX-7/ZIF-8 composite, (b) Root Mean Square Deviation (RMSD) of atomic position shift in FOX-7/ZIF-8 model when temperature rises to 1000 K.300–1000 K temperature programmed AIMD simulation of NVT ensemble for 40 ps were carried out for the proposed FOX-7/ZIF-8 composite structure and α-FOX-7. The reversible hydrogen transfer was observed in the heating process of FOX-7/ZIF-8 and α-FOX-7. It was generally believed that reversible hydrogen transfers consumed energy.³² Thus, the higher frequency of reversible hydrogen transfers generally led to the higher the initial decomposition temperature. The frequency of reversible hydrogen transfers of α-FOX-7 was higher than that of FOX-7/ZIF-8. It preliminarily explains that raw FOX-7 had a higher thermal decomposition temperature than the FOX-7/ZIF-8 composites. Furthermore, the Root Mean Square Deviation (RMSD) diagram of FOX-7/ZIF-8 model showed oxygen atom had significantly larger position shift compared with hydrogen atom and nitrogen atom (Fig. 3b). It indicated the rotation of –NO₂. In contrast, the position shift of oxygen atom in α-FOX-7 was slightly smaller than that of hydrogen atom, and slightly greater than that of nitrogen atom, which was caused by the vibration before denitrification (Fig. S5^†). And the track file of FOX-7/ZIF-8 model during the heating process exhibited oxygen atom on the –NO₂ was attracted by Zn atom on the MOF structure, leading to deflection and separation of oxygen atom from the molecular plane. Based on these results, it was speculated that the initial thermal decomposition path of FOX-7 in cage of ZIF-8 was abscission of oxygen radicals from FOX-7 molecule and reaction with the transferred hydrogen in the system to form H₂O. It was different from the traditional thermal decomposition path of pure α-FOX-7 that denitrogenates led to rapid and centralized disassembly of the molecule structure.³³The mechanical sensitivities of FOX-7, FOX-7 + ZIF-8 and these FOX-7/ZIF-8 composites were further investigated, as shown in 13 FOX-7/viton granules,¹⁴ FOX-7/viton microspheres.¹⁴ The reduced mechanical sensitivities were assumed to be due to nano-sized energetic materials and the buffering effect of ZIF-8. Moreover, the large specific surface area of FOX-7/ZIF-8 composites could accelerate the heat transfer process, and prevented the accumulation of heat and the formation of “hot spots”.¹³H₅₀ of FOX-7/ZIF-8 (II) and FOX-7/ZIF-8 (III) were >112.2 cm, and their P were 0%. These results indicated that assembly of FOX-7 and ZIF-8 provided a beneficial effect for improving the safety property of energetic materials.Mechanical sensitivities of FOX-7/ZIF-8 composites

Fast and adaptive region merging based on perceptual hashing via multi-thresholding for SAR image segmentation

Due to the serious speckle noise in synthetic aperture radar (SAR) image, segmentation of SAR images is still a challenging problem. In this paper, a novel region merging method based on perceptual hashing is proposed for SAR image segmentation. In the proposed method, perceptual hash algorithm (PHA) is utilized to calculate the degree of similarity between different regions during region merging in SAR image segmentation. After reducing the speckle noise by Lee filter which maintains the sharpness of SAR image, a set of different homogeneous regions is constructed based on multi-thresholding and treated as the input data of region merging. The new contribution of this paper is the combination of multi-thresholding for initial segmentation and perceptual hash method for the adaptive process of region merging, which preserves the texture feature of input images and reduces the time complexity of the proposed method. The experimental results on synthetic and real SAR images show that the proposed algorithm is faster and attains higher-quality segmentation results than the three recent state-of-the-art image segmentation methods.     

From clinical imaging and computational models to personalised medicine and image guided interventions

This short paper describes the development of the UCL Centre for Medical Image Computing (CMIC) from 2006 to 2016, together with reference to historical developments of the Computational Imaging sciences Group (CISG) at Guy’s Hospital. Key early work in automated image registration led to developments in image guided surgery and improved cancer diagnosis and therapy. The work is illustrated with examples from neurosurgery, laparoscopic liver and gastric surgery, diagnosis and treatment of prostate cancer and breast cancer, and image guided radiotherapy for lung cancer.     

Fast spin-echo imaging of the abdomen during breath-holding: An alternative to RASE and other fast imaging techniques

We have developed a rapidly acquired T1-weighted spin-echo pulse sequence that uses gradient echo-like parameters of TR 70 ms, TE 10 ms, NEX-1 (SE 70/10/1) with large pulse angles, and presaturation. This sequence yields two images of the abdomen during a comfortable breath-hold of 9 s. Preliminary phantom studies with this sequence demonstrated that peak signal-to-noise ratios occurred at pulse angles of 120° and 135°. Compared to this rapidly acquired sequence, a conventional T1-weighted spin-echo sequence of TR 140 ms, TE 10 ms, NEX-4 demonstrated 2.8 times the signal-to-noise ratio, 2.6 times the liver-spleen contrast-to-noise ratio but only 1.6 times the contrast-to-artifact ratio. When normalized for the imaging time, however, there was little difference in the signal-to-noise and contrast-to-noise ratios, although the SE 70/10/ 1 demonstrated 2.0 times the contrast-to-artifact ratio. We conclude that for abdominal imaging the SE 70/10/1 is an excellent alternative to RASE and other fast imaging techniques, and, although there are inherently low signal-to-noise ratios, it may be particularly useful when coupled with a paramagnetic contrast agent.