NEW SAR IMAGE INTERPRETATION METHOD OF AIRCRAFT BASED ON JOINT TIME-FREQUENCY ANALYSIS

With the continuous improvement of Synthetic Aperture Radar(SAR) resolution, interpreting the small targets like aircraft in SAR images becomes possible and turn out to be a hot spot in SAR application research. However, due to the complexity of SAR imaging mechanism, interpreting targets in SAR images is a tough problem. This paper presents a new aircraft interpretation method based on the joint time-frequency analysis and multi-dimensional contrasting of basic structures. Moreover, SAR data acquisition experiment is designed for interpreting the aircraft. Analyzing the experiment data with our method, the result shows that the proposed method largely makes use of the SAR data information. The reasonable results can provide some auxiliary support for the SAR images manual interpretation.

Classification and detection of dental images using meta-learning

Meta-learning of dental X-rays is a machine learning technique that can be used to train models to perform new tasks quickly and with minimal input.Instead of just memorizing a task,this is accomplished through teaching a model how to learn.Algorithms for meta-learning are typically trained on a collection of training problems,each of which has a limited number of labelled instances.Multiple Xray classification tasks,including the detection of pneumonia,coronavirus disease 2019,and other disorders,have demonstrated the effectiveness of meta-learning.Meta-learning has the benefit of allowing models to be trained on dental X-ray datasets that are too few for more conventional machine learning methods.Due to the high cost and lengthy collection process associated with dental imaging datasets,this is significant for dental X-ray classification jobs.The ability to train models that are more resistant to fresh input is another benefit of meta-learning.

Image interpretation of weak-coupling N-mer adsorbate's STM system

Up to now, there have been many indistinctive points in the image interpretation of scanning tunnelhng microscopy (STM) system, and the problems have attracted almost all STM scientists’ attention. In 1992, Kenkre proposed the new programme which describes the behaviour of the electrons moving in the STM tunnelling by the method of exciton dynamics, and the programme not only breaks through the restrictions of Tersoff-Hamann theory, but also can be applied conveniently to discussing the effects of the tip structure, adsorbate structure, substrate structure, temperature, tunneling voltage, and the degree of coherence of elec-

Image interpretation: mining the visible and syntactic correlation of annotated words

Automatic web image annotation is a practical and effective way for both web image retrieval and image understanding. However, current annotation techniques make no further investigation of the statement-level syntactic correlation among the annotated words, therefore making it very difficult to render natural language interpretation for images such as "pandas eat bamboo". In this paper, we propose an approach to interpret image semantics through mining the visible and textual information hidden in images. This approach mainly consists of two parts: first the annotated words of target images are ranked according to two factors, namely the visual correlation and the pairwise co-occurrence; then the statement-level syntactic correlation among annotated words is explored and natural language interpretation for the target image is obtained. Experiments conducted on real-world web images show the effectiveness of the proposed approach.

MARKER-BASED MAPPING BETWEEN MEDICAL IMAGE AND ROBOT SPACE IN ROBOT-ASSISTED SURGERY

This paper focuses on the problems of matching a virtual and a real environments by means of hardware and software tools. The real space is represented by a patient’s bone where a set of cuts by means of robot system is to be made. The virtual space is a 3D model of the bone reconstructed from a set of CT slices. Robot system is then not only to machine bones but also to perform the fundamental step of registration between the two spaces. An external force sensor is used to adjust robot stiffness in order to perform the tactile searching necessary for the registration. A simple but reliable software algorithm is used to control the robot for matching between medical image and robot space in robot-assisted surgery. The results show the system proposed is precise enough for application, and tests been made also clarify the way to improve it.

Study of the Retinal Imaging and Output in Premature Baby under a Computer-assisted Binocular Indirect Ophthalmoscope

Purpose:To explore a clear retinal imaging and output and enhance the development of retinopathy of prematurity (ROP) screening,which is safe and effective for ROP screening in premature infants. Methods:A computer-assisted binocular indirect ophthalmoscope imaging and output system was equipped with camera and image processing hardware and connected to computers. The process of fundus examination was videotaped (photograph) and output. Simulated eyes were utilized to debug video head and acquire stable and clear fundus images by binocular indirect ophthalmoscope for premature infants. Results:Fundus imaging output technique was sucessfully established. The common reasons of unclear imaging and corresponding solutions were summarized. This technique can capture and output stable and clear fundus images of premature infants. Conclusion: Assisted by hardware and software processing, a compute assisted binocular indirect ophthalmoscope imaging and output system was established,which can be used for screening, research, treatment and follow-up of ROP in premature babies to resolve the difficulty in obtaining clear fundus photograph.

Optimized Non-hyperbolic Stack Imaging Based on Interpretation Model

In complex media, especially for seismic prospecting in deep layers in East China and in the mountainous area in West China, due to the complex geological condition, the common-mid-point （CMP） gather of deep reflection event is neither hyperbolic, nor any simple function. If traditional normal move-out （NMO） and stack imaging technology are still used, it is difficult to get a clear stack image. Based on previous techniques on non-hyperbolic stack, it is thought in this paper that no matter how complex the geological condition is, in order to get an optimized stack image, the stack should be non time move-out stack, and any stacking method limited to some kind of curve will be restricted to application conditions. In order to overcome the above-mentioned limit, a new method called optimized non-hyperbolic stack imaging based on interpretation model is presented in this paper. Based on CMP/CRP （Common-Reflection-Point） gather after NMO or pre-stack migration, this method uses the interpretation model of reflectors as constraint, and takes comparability as a distinguishing criterion, and finally forms a residual move-out correction for the gather of constrained model. Numerical simulation indicates that this method could overcome the non hyperbolic problem and get fine stack image.

A Study on Diagnostic Assist Systems of Chronic Obstructive Pulmonary Disease from Medical Images by Deep Learning

In this paper, we propose new diagnostic assist systems of medical images using deep learning algorithms. Specifically, we aim to develop a diagnostic support system for the very early stage of chronic obstructive pulmonary disease (COPD) based on the CT images. It is said that COPD is a disease that develops due to long-term smoking, and it is said that there are a large number of latent onset reserve forces. By discovering this COPD in the very early period 0 and improving the living conditions, subsequent severity can be avoided in many cases, so a system that will help diagnosis by professional radiologists is needed. We show the some experimental results examined by the constructed system.

The Only Possible Mirror Image of Interpreting by Means of Understanding in Modem Westem Philosophy

Interpreting is one of the studies that is in the phase of its theoretical bottleneck. The difficulty comes from the lack of a possible holistic understanding of the phenomenon of interpreting, not to mention the mirror image of interpreting. Different linguistic studies could do nothing since nowadays their respective studies are mostly suffering their own research bottlenecks. Furthermore, it is impossible for individual linguistic studies to elaborate on the complicated interpreting practice. The only possible mirror is Modem Western Philosophy, which can present the image of interpreting. Such a mirror image is by no means possible without the full-fledged development of language study, and in particular, the uncovering of human understanding, in Modem Western Philosophy.

3-D Seismic Imaging and Morpho-tectonical Interpretation of Saucerlike Dykes of the Tarim Flood Basalt Province, NW China

The detailed structures of the plumbing system of the early Permian Tarim flood basalt were investigated by 3-D seismic imaging.The images show that the Tarim flood basalt mainly erupted from central volcanoes distributed

Up-to-date intraoperative computer assisted solutions for liver surgery

Computer assisted surgical planning allowed for a better selection of patients,evaluation of operative strategy, appropriate volumetric measurements,identification of anatomical risks, definition of tumour resection margins and choice of surgical approach in liver oncologic resections and living donor liver transplantations. Although preoperative computer surgical analysis has been widely used in daily clinical practice, intraoperative computer assisted solutions for risk analysis and navigation in liver surgery are not widely available or still under clinical evaluation. Computer science technology can efficiently assist modern surgeons during complex liver operations, mainly by providing image guidance with individualized 2 D images and 3 D models of the various anatomical and pathological structures of interest. Intraoperative computer assisted liver surgery is particularly useful in complex parenchyma-sparing hepatectomies, for intraoperative risk analysis and for the effective treatment of colorectal metastases after neoadjuvant therapy or when they are multiple. In laparoscopic liver surgery, intraoperative computer aid is definitively more important as, apart from a restricted field of view, there is also loss of the fine haptic feedback. Intraoperative computer assisted developments face challenges that prevent their application in daily clinical practice. There is a vast variety of studies regarding intraoperative computer assisted liver surgery but there are no clear objective measurements in order to compare them and select the most effective solutions. An overview of up-to-date intraoperative computer assisted solutions for liver surgery will be discussed.

An optical tweezer-based microdroplet imaging technology

Microspheres can break the diffraction limit and magnify nano-structure imaging,and with its advantages of low cost and label-free operation,microsphere-assisted imaging has become an irreplaceable tool in the life sciences and for precision measurements.However,the tiny size and limited imaging field of traditional solid microspheres cause difficulties when imaging large sample areas.Alternatively,droplets have similar properties to those of microspheres,with large surface curvature and refractive-index difference from the surrounding environment,and they can also serve as lenses to focus light for observation and imaging.Previous work has shown that droplets with controllable size can be generated using an optical tweezer system and can be driven by optical traps to move precisely like solid microspheres.Here,a novel microdroplet-assisted imaging technology based on optical tweezers is proposed that better integrates the generation,manipulation,and utilization of droplets.

Search Space Pruning Based on Image Tools for Preliminary Interplanetary Trajectory Design

A novel gravity assist space pruning(GASP)algorithm based on image tools is proposed for solving interplanetary trajectory optimization problem.Compared with traditional GASP algorithm,the concept of image is introduced to avoid missing interesting solutions with appropriate number of function evaluations.Image tools allow us to evaluate the objective function in regions in place of points and provide an effective way to evaluate the forward and backward constraints for the multi-gravity assist trajectory optimization problem.Since the interesting solutions of the interplanetary trajectory optimization problem are often clustered in a small portion of the search space rather than being overall evenly distributed,the regionwise evaluations with image tools make the little large interval with the proper Lipschitzian tolerances sampling effective.The detailed steps of the proposed method are presented and two examples including Earth Venus Mars(EVM)transfer and Earth Venus Venus Earth Jupiter Saturn(EVVEJS)transfer are given.Finally,a comparison with solutions given by the literature demonstrates the effectiveness of the proposed method.

An Interpretable CNN for the Segmentation of the Left Ventricle in Cardiac MRI by Real-Time Visualization

The interpretability of deep learning models has emerged as a compelling area in artificial intelligence research.The safety criteria for medical imaging are highly stringent,and models are required for an explanation.However,existing convolutional neural network solutions for left ventricular segmentation are viewed in terms of inputs and outputs.Thus,the interpretability of CNNs has come into the spotlight.Since medical imaging data are limited,many methods to fine-tune medical imaging models that are popular in transfer models have been built using massive public Image Net datasets by the transfer learning method.Unfortunately,this generates many unreliable parameters and makes it difficult to generate plausible explanations from these models.In this study,we trained from scratch rather than relying on transfer learning,creating a novel interpretable approach for autonomously segmenting the left ventricle with a cardiac MRI.Our enhanced GPU training system implemented interpretable global average pooling for graphics using deep learning.The deep learning tasks were simplified.Simplification included data management,neural network architecture,and training.Our system monitored and analyzed the gradient changes of different layers with dynamic visualizations in real-time and selected the optimal deployment model.Our results demonstrated that the proposed method was feasible and efficient:the Dice coefficient reached 94.48%,and the accuracy reached 99.7%.It was found that no current transfer learning models could perform comparably to the ImageNet transfer learning architectures.This model is lightweight and more convenient to deploy on mobile devices than transfer learning models.

A REVIEW ON ARTERY WALL SEGMENTATION TECHNIQUES AND INTIMA-MEDIA THICKNESS MEASUREMENT FOR CAROTID ULTRASOUND IMAGES

Stroke and heart attack,which could be led by a kind of cerebrovascular and cardiovascular disease named as atherosclerosis,would seriously cause human morbidity and mortality.It is important for the early stage diagnosis and monitoring medical intervention of the atherosclerosis.Carotid stenosis is a classical atherosclerotic lesion with vessel wall narrowing down and accumulating plaques burden.The carotid artery of intima-media thickness(IMT)is a key indicator to the disease.With the development of computer assisted diagnosis technology,the imaging techniques,segmentation algorithms,measurement methods,and evaluation tools have made considerable progress.Ultrasound imaging,being real-time,economic,reliable,and safe,now seems to become a standard in vascular assessment methodology especially for the measurement of IMT.This review firstly attempts to discuss the clinical relevance of measurements in clinical practice at first,and then followed by the challenges that one has to face when approaching the segmentation of ultrasound images.Secondly,the commonly used methods for the IMT segmentation and measurement are presented.Thirdly,discussion and evaluation of different segmentation techniques are performed.An overview of summary and future perspectives is given finally.

Photographic Image: Thematization of Its Discourses

This paper deals with thematization as a fundamental step towards the determination of photography image discourses in order to index them. It deals with questions related to photographic reality, polysemy, denotation and connotation, whose comprehension is fundamentally important for the interpretation of photography discourses. It also approaches aspects that have influenced photography analysis towards its thematization, such as the characterization of an image bank, the functions performed by photos, as well as technical and visual quality.

Anisotropy interpretation and the coherence research between resistivity and acoustic anisotropy in tight sands

Aiming at the problem of anisotropy inversion of tight sands, a new method for extracting resistivity anisotropy from array laterolog and micro-resistivity scanning imaging logging is proposed, and also the consistency of electric and acoustic anisotropy is discussed. Array laterolog includes resistivity anisotropy information, but numerical simulation shows that drilling fluid invasion has the greatest influence on the response, followed by the relative dip angle θ and electrical anisotropy coefficient λ. A new inversion method to determine ri, Rxo, Rt and λ is developed with the given θ and initial values of invasion radius ri, flushed zone resistivity Rxo, in-situ formation resistivity Rt. Micro-resistivity image can also be used for describing the resistivity distribution information in different directions, and the electrical characteristics from micro-resistivity log in different azimuths, lateral and vertical, can be compared to extract electric anisotropy information. Directional arrangement of mineral particles in tight sands and fracture development are the intrinsic causes of anisotropy, which in turn brings about anisotropy in resistivity and acoustic velocity, so the resistivity anisotropy and acoustic velocity anisotropy are consistent in trends. Analysis of log data of several wells show that the electrical anisotropy and acoustic anisotropy extracted from array laterolog, micro-resistivity imaging and cross-dipole acoustic logs respectively are consistent in trend and magnitude, proving the inversion method is accurate and the anisotropies of different formation physical parameters caused by the intrinsic structure of tight sand reservoir are consistent. This research provides a new idea for evaluating anisotropy of tight sands.

The Differences between Chinese and Western Cultures based on the Animal Images in Idioms

Chinese idioms,like English proverbs,are a language form,with a certain philosophical motive and ideological basis,given meaning through people's lifelong experiences.Throughout the ages,a wide range of beliefs,customs and natural scenery have been condensed into text forms in both Chinese idioms and English proverbs that display certain aspects of the essence of the two cultures.This paper focuses on the study of animal images in idioms,and elaborates on the different interpretations of specific images caused by the differences in history,regions,customs,and values of the two cultures.The purpose of this research is to provide a breakthrough more relevant to students who devote themselves to the study and research of Chinese and English languages and culture from the perspective of cultural contrast and analysis,so as to make a more thorough understanding of differences between Chinese and Western customs,culture and ideology.Therefore,language translations and cultural communications can be improved through a more accurate understanding of the Chinese and Western cultures.

Classification and structural characteristics of amorphous materials based on interpretable deep learning

Defining the structure characteristics of amorphous materials is one of the fundamental problems that need to be solved urgently in complex materials because of their complex structure and long-range disorder.In this study,we develop an interpretable deep learning model capable of accurately classifying amorphous configurations and characterizing their structural properties.The results demonstrate that the multi-dimensional hybrid convolutional neural network can classify the two-dimensional(2D)liquids and amorphous solids of molecular dynamics simulation.The classification process does not make a priori assumptions on the amorphous particle environment,and the accuracy is 92.75%,which is better than other convolutional neural networks.Moreover,our model utilizes the gradient-weighted activation-like mapping method,which generates activation-like heat maps that can precisely identify important structures in the amorphous configuration maps.We obtain an order parameter from the heatmap and conduct finite scale analysis of this parameter.Our findings demonstrate that the order parameter effectively captures the amorphous phase transition process across various systems.These results hold significant scientific implications for the study of amorphous structural characteristics via deep learning.

A novel technique for sacropelvic fixation using image-guided sacroiliac screws:a case series and biomechanical study

In this study, we sought to assess the safety and accuracy of sacropelvic fixation performed with image-guided sacroiliac screw placement using postoperative computed tomography and X-rays. The sacroiliac screws were placed with navigation in five patients. Intact specimens were mounted onto a six-degrees-of-freedom spine motion simulator. Long lumbosacral constructs using bilateral sacroiliac screws and bilateral S1 pedicle and iliac screws were tested in seven cadaveric spines. Nine sacroiliac screws were well-placed under an image guidance system(IGS);one was placed poorly without IGS with no symptoms. Both fixation techniques significantly reduced range of motion(P<0.05) at L5-S1. The research concluded that rigid lumbosacral fixation can be achieved with sacroiliac screws,and image guidance improves its safety and accuracy. This new technique of image-guided sacroiliac screw insertion should prove useful in many types of fusion to the sacrum, particularly for patients with poor bone quality,complicated anatomy, infection, previous failed fusion and iliac harvesting.