A modified OMP method for multi-orbit three dimensional ISAR imaging of the space target

The conventional two dimensional(2D)inverse synthetic aperture radar(ISAR)imaging fails to provide the targets'three dimensional(3D)information.In this paper,a 3D ISAR imaging method for the space target is proposed based on mutliorbit observation data and an improved orthogonal matching pursuit(OMP)algorithm.Firstly,the 3D scattered field data is converted into a set of 2D matrix by stacking slices of the 3D data along the elevation direction dimension.Then,an improved OMP algorithm is applied to recover the space target's amplitude information via the 2D matrix data.Finally,scattering centers can be reconstructed with specific three dimensional locations.Numerical simulations are provided to demonstrate the effectiveness and superiority of the proposed 3D imaging method.

3-Dimensional Irradiance Imaging with a Single Camera System

The focusing tomography is presented to reconstruct 3 dimensional irradiance distribution. A 3 dimensional luminous body could be considered as the combination of many 2 dimensional parallel luminous sections. Focus on these discrete sections respectively by a single camera, a group of images would be captured to form governing equations of irradiance. After inversion procedure, the irradiance distribution of different sections could be decoded. In this experimentation two lightbulbs are used to simulate two luminous sections. Reasonable results demonstrate that this technique could be a useful method in irradiance reconstruction after further development.

Dimensionality Reduction Using Optimized Self-Organized Map Technique for Hyperspectral Image Classification

The high dimensionalhyperspectral image classification is a challenging task due to the spectral feature vectors.The high correlation between these features and the noises greatly affects the classification performances.To overcome this,dimensionality reduction techniques are widely used.Traditional image processing applications recently propose numerous deep learning models.However,in hyperspectral image classification,the features of deep learning models are less explored.Thus,for efficient hyperspectral image classification,a depth-wise convolutional neural network is presented in this research work.To handle the dimensionality issue in the classification process,an optimized self-organized map model is employed using a water strider optimization algorithm.The network parameters of the self-organized map are optimized by the water strider optimization which reduces the dimensionality issues and enhances the classification performances.Standard datasets such as Indian Pines and the University of Pavia(UP)are considered for experimental analysis.Existing dimensionality reduction methods like Enhanced Hybrid-Graph Discriminant Learning(EHGDL),local geometric structure Fisher analysis(LGSFA),Discriminant Hyper-Laplacian projection(DHLP),Group-based tensor model(GBTM),and Lower rank tensor approximation(LRTA)methods are compared with proposed optimized SOM model.Results confirm the superior performance of the proposed model of 98.22%accuracy for the Indian pines dataset and 98.21%accuracy for the University of Pavia dataset over the existing maximum likelihood classifier,and Support vector machine(SVM).

Three-dimensional imaging identified the accessory bile duct in a patient with cholangiocarcinoma

The development of diagnostic imaging technology, such as multidetector computed tomography(MDCT) and magnetic resonance cholangiopancreatography(MRCP), has made it possible to obtain detailed images of the bile duct. Recent reports have indicated that a 3-dimensional(3D) reconstructed imaging system would be useful for understanding the liver anatomy before surgery. We have investigated a novel method that fuses MDCT and MRCP images. This novel system easily made it possible to detect the anatomical relationship between the vessels and bile duct in the portal hepatis. In this report, we describe a very rare case of extrahepatic cholangiocarcinoma associated with an accessory bile duct from the caudate lobe connecting with the intrapancreatic bile duct. We were unable to preoperatively detect this accessory bile duct using MDCT and MRCP. However, prior to the second operation, we were able to clearly visualise the injured accessory bile duct using our novel 3D imaging modality. In thisreport, we suggest that this imaging technique can be considered a novel and useful modality for understanding the anatomy of the portal hepatis, including the hilar bile duct.

Application of Three-Dimensional Magnetic Resonance Imaging in the Diagnosis of Perianal Abscess

Perianal abscess is a common disease in anorectal surgery. If the diagnosis is not clear and the cure is thoroughly cleared, the recurrence and spread of anal fistula will cause life-long pain. Objective: To investigate the application of 3.0T MRI 3D CUBE T2WI lipid suppression sequence in the diagnosis of perianal abscess. Methods: Thirty-six patients with perianal abscess confirmed by operation were examined with 2D T2WI and 3D CUBE T2WI lipid suppression sequences before operation. Two imaging techniques were evaluated to show the types of perianal abscess, the number of abscesses, the number of internal orifices of abscess, and the number of fistula branches with anal fistula in abscess. Results: Among 36 cases of perianal abscess, there were 5 cases of anal subcutaneous abscess, 12 cases of ischiorectal space abscess (8 cases complicated with anal fistula), 6 cases of posterior anal space abscess, 5 cases of anal sphincter abscess (3 cases complicated with anal fistula), 2 cases of high intermuscular abscess, 2 cases of rectal submucosal abscess, 3 cases of complex abscess (3 cases complicated with anal fistula), 1 case of misdiagnosis, 2D T2WI lipid suppression sequence and 3D CUBE T2WI suppression. The accuracy of lipid sequence abscess typing was 80.6% (29/36) and 88.9% (32/36), respectively, with no significant difference (P > 0.05). Thirty-six patients were surgically diagnosed as having 32 internal orifices, 68.8% (22/32) and 93.8% (30/32) of 2D T2WI and 3D CUBE T2WI lipid-suppressing sequences, respectively, with significant difference (P Conclusion: 3D CUBE T2WI lipid suppression sequence is superior to 2D T2WI lipid suppression sequence in the classification of perianal abscess, the number of internal orifices of abscess and the number of fistula branches of abscess complicated with anal fistula. It can also determine the number of internal orifices of abscess complicated with anal fistula, the number of fistula branches, the shape of primary and branch fistula and the relationship among pelvic floor muscle tissues. It can provide more accurate images for preoperative and intraoperative clinical surgery.

Four-dimensional flow magnetic resonance imaging incirrhosis

Since its introduction in the 1970’s,magnetic resonance imaging(MRI)has become a standard imaging modality.With its broad and standardized application,it is firmly established in the clinical routine and an essential element in cardiovascular and abdominal imaging.In addition to sonography and computer tomography,MRI is a valuable tool for diagnosing cardiovascular and abdominal diseases,for determining disease severity,and for assessing therapeutic success.MRI techniques have improved over the last few decades,revealing not just morphologic information,but functional information about perfusion,diffusion and hemodynamics as well.Four-dimensional(4D)flow MRI,a time-resolved phase contrast-MRI with three-dimensional(3D)anatomic coverage and velocity encoding along all three flow directions has been used to comprehensively assess complex cardiovascular hemodynamics in multiple regions of the body.The technique enables visualization of 3D blood flow patterns and retrospective quantification of blood flow parameters in a region of interest.Over the last few years,4D flow MRI has been increasingly performed in the abdominal region.By applying different acceleration techniques,taking 4D flow MRI measurements has dropped to a reasonable scanning time of 8 to 12 min.These new developments have encouraged a growing number of patient studies in the literature validating the technique’s potential for enhanced evaluation of blood flow parameters within the liver’s complex vascular system.The purpose of this review article is to broaden our understanding of 4D flow MRI for the assessment of liver hemodynamics by providing insights into acquisition,data analysis,visualization and quantification.Furthermore,in this article we highlight its development,focussing on the clinical application of the technique.

Continuous imaging space in three-dimensional integral imaging

We report an integral imaging method with continuous imaging space. This method simultaneously reconstructs real and virtual images in the virtual mode, with a minimum gap that separates the entire imaging space into real and virtual space. Experimental results show that the gap is reduced to 45% of that in a conventional integral imaging system with the same parameters.

Prenatal Diagnosis of Sirenomelia by Two-Dimensional and Three-Dimensional Skeletal Imaging Ultrasound

Summary： This study sought to evaluate the contribution of two-dimensional ultrasound （2D-US） and three-dimensional skeletal imaging ultrasound （3D-SUIS） in the prenatal diagnosis of sirenomelia. Be- tween September 2010 and April 2014, a prospective study was conducted in a single referral center using 3D-SU1S performed after 2D-US in 10 cases of sirenomelia. Diagnostic accuracy and detailed findings were compared with postnatal three-dimensional helical computed tomography （3D-HCT）, radiological findings and autopsy. Pregnancy was terminated in all 10 sirenomelia cases, including 9 singletons and I conjoined twin pregnancy, for a total of 5 males and 5 females. These cases of sirenomelia were deter- mined by autopsy and/or chromosomal examination. Initial 2D-US showed that there were 10 cases of oligohydranmios, bilateral renal agenesis, bladder agenesis, single umbilical artery, fusion of the lower limbs and spinal abnormalities; 8 cases of dipus or monopus; 2 cases of apus; and 8 cases of cardiac abnormalities. Subsequent 3D-SUIS showed that there were 9 cases of scoliosis, l0 cases of sacrococ- cygeal vertebra dysplasia, 3 cases of hemivertebra, 1 case of vertebral fusion, 3 cases of spina bifida, and 5 cases of rib abnormalities. 3D-SUIS identified significantly more skeletal abnormalities than did 2D-US, and its accuracy was 79.5% （70/88） compared with 3D-HCT and radiography. 3D-SUIS seems to be a useful complementary method to 2D-US and may improve the accuracy of identifying prenatal skeletal abnormalities related to sirenomelia.

Real-time Three-Dimensional Color Doppler Flow Imaging： An Improved Technique for Quantitative Analysis of Aortic Regurgitation

The recently introduced real-time three-dimensional color Doppler flow imaging （RT-3D CDFI） technique provides a quick and accurate calculation of regurgitant jet volume （RJV） and fraction. In order to evaluate RT-3D CDFI in the noninvasive assessment of aortic RJV and regurgitant jet fraction （RJF） in patients with isolated aortic regurgitation, real-time three-dimensional echocardiographic studies were performed on 23 patients with isolated aortic regurgitation to obtain LV end-diastolic volumes （LVEDV）, end-systolic volumes （LVESV） and RJV, and then RJF could be calculated. The regurgitant volume （RV） and regurgitant fraction （RF） calculated by two-dimensional pulsed Doppler （2D-PD） method served as reference values. The results showed that aortic RJV measured by the RT-3D CDFI method showed a good correlation with the 2D-PD measurements （r= 0.93, Y=0.89X＋ 3.9, SEE= 8.6 mL, P〈0.001 ）; the mean （SD） difference between the two methods was - 1.5 （9.8） mL. % RJF estimated by the RT-3D CDFI method was also correlated well with the values obtained by the 2D-PD method （r=0.88, Y=0.71X＋ 14.8, SEE= 6.4 %, P〈0. 001）; the mean （SD） difference between the two methods was -1.2 （7.9） %. It was suggested that the newly developed RT-3D CDFI technique was feasible in the majority of patients. In patients with eccentric aortic regurgitation, this new modality provides additional information to that obtained from the two-dimensional examination, which overcomes the inherent limitations of two-dimensional echocardiography by depicting the full extent of the jet trajectory. In addition, the RT-3D CDFI method is quick and accurate in calculating RJV and RJF.

Evaluation of Airway Obstruction at Soft Palate Level in Male Patients with Obstructive Sleep Apnea/Hypopnea Syndrome:Dynamic 3-Dimensional CT Imaging of Upper Airway

This study examined the dynamic characteristics of upper airway collapse at soft palate level in patients with obstructive sleep apnea/hypopnea syndrome（OSAHS） by using dynamic 3-Dimensional（3-D） CT imaging.A total of 41 male patients who presented with 2 of the following symptoms,i.e.,daytime sleepiness and fatigue,frequent snoring,and apnea with witness,were diagnosed as having OSAHS.They underwent full-night polysomnography and then dynamic 3-D CT imaging of the upper airway during quiet breathing and in Muller＇s maneuver.The soft palate length（SPL）,the minimal cross-sectional area of the retropalatal region（mXSA-RP）,and the vertical distance from the hard palate to the upper posterior part of the hyoid（hhL） were compared between the two breathing states.These parameters,together with hard palate length（HPL）,were also compared between mild/moderate and severe OSAHS groups.Association of these parameters with the severity of OSAHS [as reflected by apnea hypopnea index（AHI） and the lowest saturation of blood oxygen（LSaO2）] was examined.The results showed that 31 patients had severe OSAHS,and 10 mild/moderate OSAHS.All the patients had airway obstruction at soft palate level.mXSA-RP was significantly decreased and SPL remarkably increased during Muller＇s maneuver as compared with the quiet breathing state.There were no significant differences in these airway parameters（except the position of the hyoid bone） between severe and mild/moderate OSAHS groups.And no significant correlation between these airway parameters and the severity of OSAHS was found.The position of hyoid was lower in the severe OSAHS group than in the mild/moderate OSAHS group.The patients in group with body mass index（BMI）≥26 had higher collapse ratio of mXSA-RP,greater neck circumference and smaller mXSA-RP in the Muller＇s maneuver than those in group with BMI26（P0.05 for all）.It was concluded that dynamic 3-D CT imaging could dynamically show the upper airway changes at soft palate level in OSAHS patients.All the OSAHS patients had airway obstruction of various degrees at soft palate level.But no correlation was observed between the airway change at soft palate level and the severity of OSAHS.The patients in group with BMI≥26 were more likely to develop airway obstruction at soft palate level than those with BMI26.

Magnetic resonance imaging-three-dimensional printing technology fabricates customized scaffolds for brain tissue engineering

Conventional fabrication methods lack the ability to control both macro- and micro-structures of generated scaffolds. Three-dimensional printing is a solid free-form fabrication method that provides novel ways to create customized scaffolds with high precision and accuracy. In this study, an electrically controlled cortical impactor was used to induce randomized brain tissue defects. The overall shape of scaffolds was designed using rat-specific anatomical data obtained from magnetic resonance imaging, and the internal structure was created by computer- aided design. As the result of limitations arising from insufficient resolution of the manufacturing process, we magnified the size of the cavity model prototype five-fold to successfully fabricate customized collagen-chitosan scaffolds using three-dimensional printing. Results demonstrated that scaffolds have three-dimensional porous structures, high porosity, highly specific surface areas, pore connectivity and good internal characteristics. Neural stem cells co-cultured with scaffolds showed good viability, indicating good biocompatibility and biodegradability. This technique may be a promising new strategy for regenerating complex damaged brain tissues, and helps pave the way toward personalized medicine.

Visibility enhancement in two-dimensional lensless ghost imaging with true thermal light

We report an experimental demonstration of two-dimensional（2D） lensless ghost imaging with true thermal light. An electrodeless discharge lamp with a higher light intensity than the hollow cathode lamp used before is employed as a light source. The main problem encountered by the 2D lensless ghost imaging with true thermal light is that its coherence time is much shorter than the resolution time of the detection system. To overcome this difficulty we derive a method based on the relationship between the true and measured values of the second-order optical intensity correlation, by which means the visibility of the ghost image can be dramatically enhanced. This method would also be suitable for ghost imaging with natural sunlight.

A rapid micro-magnetic resonance imaging scanning for three-dimensional reconstruction of peripheral nerve fascicles

The most common methods for three-dimensional reconstruction of peripheral nerve fascicles include histological and radiology techniques. Histological techniques have many drawbacks including an enormous manual workload and poor image registration. Micro-magnetic resonance imaging（Micro-MRI）, an emerging radiology technique, has been used to report results in the brain, liver and tumor tissues. However, micro-MRI usage for obtaining intraneural structures has not been reported. The aim of this study was to present a new imaging method for three-dimensional reconstruction of peripheral nerve fascicles by ~1T micro-MRI. Freshly harvested sciatic nerve samples from an amputated limb were divided into four groups. Two different scanning conditions（Mannerist Solution/GD-DTPA contrast agent, distilled water） were selected, and both T1 and T2 phases programmed for each scanning condition. Three clinical surgeons evaluated the quality of the images via a standardized scale. Moreover, to analyze deformation of the two-dimensional image, the nerve diameter and total area of the micro-MRI images were compared after hematoxylin-eosin staining. The results show that rapid micro-MRI imaging method can be used for three-dimensional reconstruction of the fascicle structure. Nerve sample immersed in contrast agent（Mannerist Solution/GD-DTPA） and scanned in the T1 phase was the best. Moreover, the nerve sample was scanned freshly and can be recycled for other procedures. MRI images show better stability and smaller deformation compared with histological images. In conclusion, micro-MRI provides a feasible and rapid method for three-dimensional reconstruction of peripheral nerve fascicles, which can clearly show the internal structure of the peripheral nerve.

High-Dimensional Spatial Standardization Algorithm for Diffusion Tensor Image Registration

Three high dimensional spatial standardization algorithms are used for diffusion tensor image(DTI)registration,and seven kinds of methods are used to evaluate their performances.Firstly,the template used in this paper was obtained by spatial transformation of 16 subjects by means of tensor-based standardization.Then,high dimensional standardization algorithms for diffusion tensor images,including fractional anisotropy(FA)based diffeomorphic registration algorithm,FA based elastic registration algorithm and tensor-based registration algorithm,were performed.Finally,7 kinds of evaluation methods,including normalized standard deviation,dyadic coherence,diffusion cross-correlation,overlap of eigenvalue-eigenvector pairs,Euclidean distance of diffusion tensor,and Euclidean distance of the deviatoric tensor and deviatoric of tensors,were used to qualitatively compare and summarize the above standardization algorithms.Experimental results revealed that the high-dimensional tensor-based standardization algorithms perform well and can maintain the consistency of anatomical structures.

STUDY OF RECOGNITION TECHNIQUE OF RADAR TARGET'S ONE-DIMENSIONAL IMAGES BASED ON RADIAL BASIS FUNCTION NETWORK

This paper studies the problem applying Radial Basis Function Network(RBFN) which is trained by the Recursive Least Square Algorithm(RLSA) to the recognition of one dimensional images of radar targets. The equivalence between the RBFN and the estimate of Parzen window probabilistic density is proved. It is pointed out that the I/O functions in RBFN hidden units can be generalized to general Parzen window probabilistic kernel function or potential function, too. This paper discusses the effects of the shape parameter a in the RBFN and the forgotten factor A in RLSA on the results of the recognition of three kinds of kernel function such as Gaussian, triangle, double-exponential, at the same time, also discusses the relationship between A and the training time in the RBFN.

Graph-Based Dimensionality Reduction for Hyperspectral Imagery: A Review

Hyperspectral image(HSI)contains a wealth of spectral information,which makes fine classification of ground objects possible.In the meanwhile,overly redundant information in HSI brings many challenges.Specifically,the lack of training samples and the high computational cost are the inevitable obstacles in the design of classifier.In order to solve these problems,dimensionality reduction is usually adopted.Recently,graph-based dimensionality reduction has become a hot topic.In this paper,the graph-based methods for HSI dimensionality reduction are summarized from the following aspects.1)The traditional graph-based methods employ Euclidean distance to explore the local information of samples in spectral feature space.2)The dimensionality-reduction methods based on sparse or collaborative representation regard the sparse or collaborative coefficients as graph weights to effectively reduce reconstruction errors and represent most important information of HSI in the dictionary.3)Improved methods based on sparse or collaborative graph have made great progress by considering global low-rank information,local intra-class information and spatial information.In order to compare typical techniques,three real HSI datasets were used to carry out relevant experiments,and then the experimental results were analysed and discussed.Finally,the future development of this research field is prospected.

Three-dimensional positions of scattering centers reconstruction from multiple SAR images based on radargrammetry

A method and procedure is presented to reconstruct three-dimensional(3D) positions of scattering centers from multiple synthetic aperture radar(SAR) images. Firstly, two-dimensional(2D) attribute scattering centers of targets are extracted from 2D SAR images. Secondly, similarity measure is developed based on 2D attributed scatter centers' location, type, and radargrammetry principle between multiple SAR images. By this similarity, we can associate 2D scatter centers and then obtain candidate 3D scattering centers. Thirdly, these candidate scattering centers are clustered in 3D space to reconstruct final 3D positions. Compared with presented methods, the proposed method has a capability of describing distributed scattering center, reduces false and missing 3D scattering centers, and has fewer restrictionson modeling data. Finally, results of experiments have demonstrated the effectiveness of the proposed method.

A Sequence Image Matching Method Based on Improved High-Dimensional Combined Features

Image matching technology is theoretically significant and practically promising in the field of autonomous navigation.Addressing shortcomings of existing image matching navigation technologies,the concept of high-dimensional combined feature is presented based on sequence image matching navigation.To balance between the distribution of high-dimensional combined features and the shortcomings of the only use of geometric relations,we propose a method based on Delaunay triangulation to improve the feature,and add the regional characteristics of the features together with their geometric characteristics.Finally,k-nearest neighbor(KNN)algorithm is adopted to optimize searching process.Simulation results show that the matching can be realized at the rotation angle of-8°to 8°and the scale factor of 0.9 to 1.1,and when the image size is 160 pixel×160 pixel,the matching time is less than 0.5 s.Therefore,the proposed algorithm can substantially reduce computational complexity,improve the matching speed,and exhibit robustness to the rotation and scale changes.

Analysis of Object Depth Effects on Accuracy of Dimensional Shape in X and Y Directions Using Single Non-metric Image

In general, to reconstruct the accurate shape of buildings, we need at least one stereomodel （two photographs） for each building. In most cases, however, only a single non-metric photograph is available, which is usually obtained either by an amateur, such as a tourist, or from a newspaper or a post card. To evaluate the validity of 3D reconstruction from a single non-metric image, this study analyzes the effects of object depth on the accuracy of dimensional shape in X and Y directions using a single non-metric image by means of simulation technique, as this was considered to be, in most cases, a main source of data acquisition in recording and documenting buildings.

Local Preserving Graphs Using Intra-Class Competitive Representation for Dimensionality Reduction of Hyperspectral Image

As a key technique in hyperspectral image pre-processing,dimensionality reduction has received a lot of attention.However,most of the graph-based dimensionality reduction methods only consider a single structure in the data and ignore the interfusion of multiple structures.In this paper,we propose two methods for combining intra-class competition for locally preserved graphs by constructing a new dictionary containing neighbourhood information.These two methods explore local information into the collaborative graph through competing constraints,thus effectively improving the overcrowded distribution of intra-class coefficients in the collaborative graph and enhancing the discriminative power of the algorithm.By classifying four benchmark hyperspectral data,the proposed methods are proved to be superior to several advanced algorithms,even under small-sample-size conditions.