focus image fusion: Topics by Science.gov

Sample records for focus image fusion

Multi-focus image fusion using a guided-filter-based difference image.

PubMed

Yan, Xiang; Qin, Hanlin; Li, Jia; Zhou, Huixin; Yang, Tingwu

2016-03-20

The aim of multi-focus image fusion technology is to integrate different partially focused images into one all-focused image. To realize this goal, a new multi-focus image fusion method based on a guided filter is proposed and an efficient salient feature extraction method is presented in this paper. Furthermore, feature extraction is primarily the main objective of the present work. Based on salient feature extraction, the guided filter is first used to acquire the smoothing image containing the most sharpness regions. To obtain the initial fusion map, we compose a mixed focus measure by combining the variance of image intensities and the energy of the image gradient together. Then, the initial fusion map is further processed by a morphological filter to obtain a good reprocessed fusion map. Lastly, the final fusion map is determined via the reprocessed fusion map and is optimized by a guided filter. Experimental results demonstrate that the proposed method does markedly improve the fusion performance compared to previous fusion methods and can be competitive with or even outperform state-of-the-art fusion methods in terms of both subjective visual effects and objective quality metrics.
Extended depth of field integral imaging using multi-focus fusion

NASA Astrophysics Data System (ADS)

Piao, Yongri; Zhang, Miao; Wang, Xiaohui; Li, Peihua

2018-03-01

In this paper, we propose a new method for depth of field extension in integral imaging by realizing the image fusion method on the multi-focus elemental images. In the proposed method, a camera is translated on a 2D grid to take multi-focus elemental images by sweeping the focus plane across the scene. Simply applying an image fusion method on the elemental images holding rich parallax information does not work effectively because registration accuracy of images is the prerequisite for image fusion. To solve this problem an elemental image generalization method is proposed. The aim of this generalization process is to geometrically align the objects in all elemental images so that the correct regions of multi-focus elemental images can be exacted. The all-in focus elemental images are then generated by fusing the generalized elemental images using the block based fusion method. The experimental results demonstrate that the depth of field of synthetic aperture integral imaging system has been extended by realizing the generation method combined with the image fusion on multi-focus elemental images in synthetic aperture integral imaging system.
Multi-focus image fusion based on window empirical mode decomposition

NASA Astrophysics Data System (ADS)

Qin, Xinqiang; Zheng, Jiaoyue; Hu, Gang; Wang, Jiao

2017-09-01

In order to improve multi-focus image fusion quality, a novel fusion algorithm based on window empirical mode decomposition (WEMD) is proposed. This WEMD is an improved form of bidimensional empirical mode decomposition (BEMD), due to its decomposition process using the adding window principle, effectively resolving the signal concealment problem. We used WEMD for multi-focus image fusion, and formulated different fusion rules for bidimensional intrinsic mode function (BIMF) components and the residue component. For fusion of the BIMF components, the concept of the Sum-modified-Laplacian was used and a scheme based on the visual feature contrast adopted; when choosing the residue coefficients, a pixel value based on the local visibility was selected. We carried out four groups of multi-focus image fusion experiments and compared objective evaluation criteria with other three fusion methods. The experimental results show that the proposed fusion approach is effective and performs better at fusing multi-focus images than some traditional methods.
Dual-Tree Complex Wavelet Transform and Image Block Residual-Based Multi-Focus Image Fusion in Visual Sensor Networks

PubMed Central

Yang, Yong; Tong, Song; Huang, Shuying; Lin, Pan

2014-01-01

This paper presents a novel framework for the fusion of multi-focus images explicitly designed for visual sensor network (VSN) environments. Multi-scale based fusion methods can often obtain fused images with good visual effect. However, because of the defects of the fusion rules, it is almost impossible to completely avoid the loss of useful information in the thus obtained fused images. The proposed fusion scheme can be divided into two processes: initial fusion and final fusion. The initial fusion is based on a dual-tree complex wavelet transform (DTCWT). The Sum-Modified-Laplacian (SML)-based visual contrast and SML are employed to fuse the low- and high-frequency coefficients, respectively, and an initial composited image is obtained. In the final fusion process, the image block residuals technique and consistency verification are used to detect the focusing areas and then a decision map is obtained. The map is used to guide how to achieve the final fused image. The performance of the proposed method was extensively tested on a number of multi-focus images, including no-referenced images, referenced images, and images with different noise levels. The experimental results clearly indicate that the proposed method outperformed various state-of-the-art fusion methods, in terms of both subjective and objective evaluations, and is more suitable for VSNs. PMID:25587878
Dual-tree complex wavelet transform and image block residual-based multi-focus image fusion in visual sensor networks.

PubMed

Yang, Yong; Tong, Song; Huang, Shuying; Lin, Pan

2014-11-26

This paper presents a novel framework for the fusion of multi-focus images explicitly designed for visual sensor network (VSN) environments. Multi-scale based fusion methods can often obtain fused images with good visual effect. However, because of the defects of the fusion rules, it is almost impossible to completely avoid the loss of useful information in the thus obtained fused images. The proposed fusion scheme can be divided into two processes: initial fusion and final fusion. The initial fusion is based on a dual-tree complex wavelet transform (DTCWT). The Sum-Modified-Laplacian (SML)-based visual contrast and SML are employed to fuse the low- and high-frequency coefficients, respectively, and an initial composited image is obtained. In the final fusion process, the image block residuals technique and consistency verification are used to detect the focusing areas and then a decision map is obtained. The map is used to guide how to achieve the final fused image. The performance of the proposed method was extensively tested on a number of multi-focus images, including no-referenced images, referenced images, and images with different noise levels. The experimental results clearly indicate that the proposed method outperformed various state-of-the-art fusion methods, in terms of both subjective and objective evaluations, and is more suitable for VSNs.
An adaptive block-based fusion method with LUE-SSIM for multi-focus images

NASA Astrophysics Data System (ADS)

Zheng, Jianing; Guo, Yongcai; Huang, Yukun

2016-09-01

Because of the lenses' limited depth of field, digital cameras are incapable of acquiring an all-in-focus image of objects at varying distances in a scene. Multi-focus image fusion technique can effectively solve this problem. Aiming at the block-based multi-focus image fusion methods, the problem that blocking-artifacts often occurs. An Adaptive block-based fusion method based on lifting undistorted-edge structural similarity (LUE-SSIM) is put forward. In this method, image quality metrics LUE-SSIM is firstly proposed, which utilizes the characteristics of human visual system (HVS) and structural similarity (SSIM) to make the metrics consistent with the human visual perception. Particle swarm optimization(PSO) algorithm which selects LUE-SSIM as the object function is used for optimizing the block size to construct the fused image. Experimental results on LIVE image database shows that LUE-SSIM outperform SSIM on Gaussian defocus blur images quality assessment. Besides, multi-focus image fusion experiment is carried out to verify our proposed image fusion method in terms of visual and quantitative evaluation. The results show that the proposed method performs better than some other block-based methods, especially in reducing the blocking-artifact of the fused image. And our method can effectively preserve the undistorted-edge details in focus region of the source images.
Fully Convolutional Network-Based Multifocus Image Fusion.

PubMed

Guo, Xiaopeng; Nie, Rencan; Cao, Jinde; Zhou, Dongming; Qian, Wenhua

2018-07-01

As the optical lenses for cameras always have limited depth of field, the captured images with the same scene are not all in focus. Multifocus image fusion is an efficient technology that can synthesize an all-in-focus image using several partially focused images. Previous methods have accomplished the fusion task in spatial or transform domains. However, fusion rules are always a problem in most methods. In this letter, from the aspect of focus region detection, we propose a novel multifocus image fusion method based on a fully convolutional network (FCN) learned from synthesized multifocus images. The primary novelty of this method is that the pixel-wise focus regions are detected through a learning FCN, and the entire image, not just the image patches, are exploited to train the FCN. First, we synthesize 4500 pairs of multifocus images by repeatedly using a gaussian filter for each image from PASCAL VOC 2012, to train the FCN. After that, a pair of source images is fed into the trained FCN, and two score maps indicating the focus property are generated. Next, an inversed score map is averaged with another score map to produce an aggregative score map, which take full advantage of focus probabilities in two score maps. We implement the fully connected conditional random field (CRF) on the aggregative score map to accomplish and refine a binary decision map for the fusion task. Finally, we exploit the weighted strategy based on the refined decision map to produce the fused image. To demonstrate the performance of the proposed method, we compare its fused results with several start-of-the-art methods not only on a gray data set but also on a color data set. Experimental results show that the proposed method can achieve superior fusion performance in both human visual quality and objective assessment.
Autofocus and fusion using nonlinear correlation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cabazos-Marín, Alma Rocío; Álvarez-Borrego, Josué, E-mail: josue@cicese.mx; Coronel-Beltrán, Ángel

2014-10-06

In this work a new algorithm is proposed for auto focusing and images fusion captured by microscope's CCD. The proposed algorithm for auto focusing implements the spiral scanning of each image in the stack f(x, y){sub w} to define the V{sub w} vector. The spectrum of the vector FV{sub w} is calculated by fast Fourier transform. The best in-focus image is determined by a focus measure that is obtained by the FV{sub 1} nonlinear correlation vector, of the reference image, with each other FV{sub W} images in the stack. In addition, fusion is performed with a subset of selected imagesmore » f(x, y){sub SBF} like the images with best focus measurement. Fusion creates a new improved image f(x, y){sub F} with the selection of pixels of higher intensity.« less
Effective Multifocus Image Fusion Based on HVS and BP Neural Network

PubMed Central

Yang, Yong

2014-01-01

The aim of multifocus image fusion is to fuse the images taken from the same scene with different focuses to obtain a resultant image with all objects in focus. In this paper, a novel multifocus image fusion method based on human visual system (HVS) and back propagation (BP) neural network is presented. Three features which reflect the clarity of a pixel are firstly extracted and used to train a BP neural network to determine which pixel is clearer. The clearer pixels are then used to construct the initial fused image. Thirdly, the focused regions are detected by measuring the similarity between the source images and the initial fused image followed by morphological opening and closing operations. Finally, the final fused image is obtained by a fusion rule for those focused regions. Experimental results show that the proposed method can provide better performance and outperform several existing popular fusion methods in terms of both objective and subjective evaluations. PMID:24683327
An efficient method for the fusion of light field refocused images

NASA Astrophysics Data System (ADS)

Wang, Yingqian; Yang, Jungang; Xiao, Chao; An, Wei

2018-04-01

Light field cameras have drawn much attention due to the advantage of post-capture adjustments such as refocusing after exposure. The depth of field in refocused images is always shallow because of the large equivalent aperture. As a result, a large number of multi-focus images are obtained and an all-in-focus image is demanded. Consider that most multi-focus image fusion algorithms do not particularly aim at large numbers of source images and traditional DWT-based fusion approach has serious problems in dealing with lots of multi-focus images, causing color distortion and ringing effect. To solve this problem, this paper proposes an efficient multi-focus image fusion method based on stationary wavelet transform (SWT), which can deal with a large quantity of multi-focus images with shallow depth of fields. We compare SWT-based approach with DWT-based approach on various occasions. And the results demonstrate that the proposed method performs much better both visually and quantitatively.
Multifocus image fusion using phase congruency

NASA Astrophysics Data System (ADS)

Zhan, Kun; Li, Qiaoqiao; Teng, Jicai; Wang, Mingying; Shi, Jinhui

2015-05-01

We address the problem of fusing multifocus images based on the phase congruency (PC). PC provides a sharpness feature of a natural image. The focus measure (FM) is identified as strong PC near a distinctive image feature evaluated by the complex Gabor wavelet. The PC is more robust against noise than other FMs. The fusion image is obtained by a new fusion rule (FR), and the focused region is selected by the FR from one of the input images. Experimental results show that the proposed fusion scheme achieves the fusion performance of the state-of-the-art methods in terms of visual quality and quantitative evaluations.
Adaptive multifocus image fusion using block compressed sensing with smoothed projected Landweber integration in the wavelet domain.

PubMed

V S, Unni; Mishra, Deepak; Subrahmanyam, G R K S

2016-12-01

The need for image fusion in current image processing systems is increasing mainly due to the increased number and variety of image acquisition techniques. Image fusion is the process of combining substantial information from several sensors using mathematical techniques in order to create a single composite image that will be more comprehensive and thus more useful for a human operator or other computer vision tasks. This paper presents a new approach to multifocus image fusion based on sparse signal representation. Block-based compressive sensing integrated with a projection-driven compressive sensing (CS) recovery that encourages sparsity in the wavelet domain is used as a method to get the focused image from a set of out-of-focus images. Compression is achieved during the image acquisition process using a block compressive sensing method. An adaptive thresholding technique within the smoothed projected Landweber recovery process reconstructs high-resolution focused images from low-dimensional CS measurements of out-of-focus images. Discrete wavelet transform and dual-tree complex wavelet transform are used as the sparsifying basis for the proposed fusion. The main finding lies in the fact that sparsification enables a better selection of the fusion coefficients and hence better fusion. A Laplacian mixture model fit is done in the wavelet domain and estimation of the probability density function (pdf) parameters by expectation maximization leads us to the proper selection of the coefficients of the fused image. Using the proposed method compared with the fusion scheme without employing the projected Landweber (PL) scheme and the other existing CS-based fusion approaches, it is observed that with fewer samples itself, the proposed method outperforms other approaches.
A comparative study of multi-focus image fusion validation metrics

NASA Astrophysics Data System (ADS)

Giansiracusa, Michael; Lutz, Adam; Messer, Neal; Ezekiel, Soundararajan; Alford, Mark; Blasch, Erik; Bubalo, Adnan; Manno, Michael

2016-05-01

Fusion of visual information from multiple sources is relevant for applications security, transportation, and safety applications. One way that image fusion can be particularly useful is when fusing imagery data from multiple levels of focus. Different focus levels can create different visual qualities for different regions in the imagery, which can provide much more visual information to analysts when fused. Multi-focus image fusion would benefit a user through automation, which requires the evaluation of the fused images to determine whether they have properly fused the focused regions of each image. Many no-reference metrics, such as information theory based, image feature based and structural similarity-based have been developed to accomplish comparisons. However, it is hard to scale an accurate assessment of visual quality which requires the validation of these metrics for different types of applications. In order to do this, human perception based validation methods have been developed, particularly dealing with the use of receiver operating characteristics (ROC) curves and the area under them (AUC). Our study uses these to analyze the effectiveness of no-reference image fusion metrics applied to multi-resolution fusion methods in order to determine which should be used when dealing with multi-focus data. Preliminary results show that the Tsallis, SF, and spatial frequency metrics are consistent with the image quality and peak signal to noise ratio (PSNR).
Multi-focus image fusion with the all convolutional neural network

NASA Astrophysics Data System (ADS)

Du, Chao-ben; Gao, She-sheng

2018-01-01

A decision map contains complete and clear information about the image to be fused, which is crucial to various image fusion issues, especially multi-focus image fusion. However, in order to get a satisfactory image fusion effect, getting a decision map is very necessary and usually difficult to finish. In this letter, we address this problem with convolutional neural network (CNN), aiming to get a state-of-the-art decision map. The main idea is that the max-pooling of CNN is replaced by a convolution layer, the residuals are propagated backwards by gradient descent, and the training parameters of the individual layers of the CNN are updated layer by layer. Based on this, we propose a new all CNN (ACNN)-based multi-focus image fusion method in spatial domain. We demonstrate that the decision map obtained from the ACNN is reliable and can lead to high-quality fusion results. Experimental results clearly validate that the proposed algorithm can obtain state-of-the-art fusion performance in terms of both qualitative and quantitative evaluations.
Multi-focus image fusion and robust encryption algorithm based on compressive sensing

NASA Astrophysics Data System (ADS)

Xiao, Di; Wang, Lan; Xiang, Tao; Wang, Yong

2017-06-01

Multi-focus image fusion schemes have been studied in recent years. However, little work has been done in multi-focus image transmission security. This paper proposes a scheme that can reduce data transmission volume and resist various attacks. First, multi-focus image fusion based on wavelet decomposition can generate complete scene images and optimize the perception of the human eye. The fused images are sparsely represented with DCT and sampled with structurally random matrix (SRM), which reduces the data volume and realizes the initial encryption. Then the obtained measurements are further encrypted to resist noise and crop attack through combining permutation and diffusion stages. At the receiver, the cipher images can be jointly decrypted and reconstructed. Simulation results demonstrate the security and robustness of the proposed scheme.
Multi-focus image fusion based on area-based standard deviation in dual tree contourlet transform domain

NASA Astrophysics Data System (ADS)

Dong, Min; Dong, Chenghui; Guo, Miao; Wang, Zhe; Mu, Xiaomin

2018-04-01

Multiresolution-based methods, such as wavelet and Contourlet are usually used to image fusion. This work presents a new image fusion frame-work by utilizing area-based standard deviation in dual tree Contourlet trans-form domain. Firstly, the pre-registered source images are decomposed with dual tree Contourlet transform; low-pass and high-pass coefficients are obtained. Then, the low-pass bands are fused with weighted average based on area standard deviation rather than the simple "averaging" rule. While the high-pass bands are merged with the "max-absolute' fusion rule. Finally, the modified low-pass and high-pass coefficients are used to reconstruct the final fused image. The major advantage of the proposed fusion method over conventional fusion is the approximately shift invariance and multidirectional selectivity of dual tree Contourlet transform. The proposed method is compared with wavelet- , Contourletbased methods and other the state-of-the art methods on common used multi focus images. Experiments demonstrate that the proposed fusion framework is feasible and effective, and it performs better in both subjective and objective evaluation.
Design of a new type synchronous focusing mechanism

NASA Astrophysics Data System (ADS)

Zhang, Jintao; Tan, Ruijun; Chen, Zhou; Zhang, Yongqi; Fu, Panlong; Qu, Yachen

2018-05-01

Aiming at the dual channel telescopic imaging system composed of infrared imaging system, low-light-level imaging system and image fusion module, In the fusion of low-light-level images and infrared images, it is obvious that using clear source images is easier to obtain high definition fused images. When the target is imaged at 15m to infinity, focusing is needed to ensure the imaging quality of the dual channel imaging system; therefore, a new type of synchronous focusing mechanism is designed. The synchronous focusing mechanism realizes the focusing function through the synchronous translational imaging devices, mainly including the structure of the screw rod nut, the shaft hole coordination structure and the spring steel ball eliminating clearance structure, etc. Starting from the synchronous focusing function of two imaging devices, the structure characteristics of the synchronous focusing mechanism are introduced in detail, and the focusing range is analyzed. The experimental results show that the synchronous focusing mechanism has the advantages of ingenious design, high focusing accuracy and stable and reliable operation.
Region-based multifocus image fusion for the precise acquisition of Pap smear images.

PubMed

Tello-Mijares, Santiago; Bescós, Jesús

2018-05-01

A multifocus image fusion method to obtain a single focused image from a sequence of microscopic high-magnification Papanicolau source (Pap smear) images is presented. These images, captured each in a different position of the microscope lens, frequently show partially focused cells or parts of cells, which makes them unpractical for the direct application of image analysis techniques. The proposed method obtains a focused image with a high preservation of original pixels information while achieving a negligible visibility of the fusion artifacts. The method starts by identifying the best-focused image of the sequence; then, it performs a mean-shift segmentation over this image; the focus level of the segmented regions is evaluated in all the images of the sequence, and best-focused regions are merged in a single combined image; finally, this image is processed with an adaptive artifact removal process. The combination of a region-oriented approach, instead of block-based approaches, and a minimum modification of the value of focused pixels in the original images achieve a highly contrasted image with no visible artifacts, which makes this method especially convenient for the medical imaging domain. The proposed method is compared with several state-of-the-art alternatives over a representative dataset. The experimental results show that our proposal obtains the best and more stable quality indicators. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).
Applicability of common measures in multifocus image fusion comparison

NASA Astrophysics Data System (ADS)

Vajgl, Marek

2017-11-01

Image fusion is an image processing area aimed at fusion of multiple input images to achieve an output image somehow better then each of the input ones. In the case of "multifocus fusion", input images are capturing the same scene differing ina focus distance. The aim is to obtain an image, which is sharp in all its areas. The are several different approaches and methods used to solve this problem. However, it is common question which one is the best. This work describes a research covering the field of common measures with a question, if some of them can be used as a quality measure of the fusion result evaluation.
Focus measure method based on the modulus of the gradient of the color planes for digital microscopy

NASA Astrophysics Data System (ADS)

Hurtado-Pérez, Román; Toxqui-Quitl, Carina; Padilla-Vivanco, Alfonso; Aguilar-Valdez, J. Félix; Ortega-Mendoza, Gabriel

2018-02-01

The modulus of the gradient of the color planes (MGC) is implemented to transform multichannel information to a grayscale image. This digital technique is used in two applications: (a) focus measurements during autofocusing (AF) process and (b) extending the depth of field (EDoF) by means of multifocus image fusion. In the first case, the MGC procedure is based on an edge detection technique and is implemented in over 15 focus metrics that are typically handled in digital microscopy. The MGC approach is tested on color images of histological sections for the selection of in-focus images. An appealing attribute of all the AF metrics working in the MGC space is their monotonic behavior even up to a magnification of 100×. An advantage of the MGC method is its computational simplicity and inherent parallelism. In the second application, a multifocus image fusion algorithm based on the MGC approach has been implemented on graphics processing units (GPUs). The resulting fused images are evaluated using a nonreference image quality metric. The proposed fusion method reveals a high-quality image independently of faulty illumination during the image acquisition. Finally, the three-dimensional visualization of the in-focus image is shown.

Image fusion based on Bandelet and sparse representation

NASA Astrophysics Data System (ADS)

Zhang, Jiuxing; Zhang, Wei; Li, Xuzhi

2018-04-01

Bandelet transform could acquire geometric regular direction and geometric flow, sparse representation could represent signals with as little as possible atoms on over-complete dictionary, both of which could be used to image fusion. Therefore, a new fusion method is proposed based on Bandelet and Sparse Representation, to fuse Bandelet coefficients of multi-source images and obtain high quality fusion effects. The test are performed on remote sensing images and simulated multi-focus images, experimental results show that the performance of new method is better than tested methods according to objective evaluation indexes and subjective visual effects.
Collection Fusion Using Bayesian Estimation of a Linear Regression Model in Image Databases on the Web.

ERIC Educational Resources Information Center

Kim, Deok-Hwan; Chung, Chin-Wan

2003-01-01

Discusses the collection fusion problem of image databases, concerned with retrieving relevant images by content based retrieval from image databases distributed on the Web. Focuses on a metaserver which selects image databases supporting similarity measures and proposes a new algorithm which exploits a probabilistic technique using Bayesian…
Fusion Imaging for Procedural Guidance.

PubMed

Wiley, Brandon M; Eleid, Mackram F; Thaden, Jeremy J

2018-05-01

The field of percutaneous structural heart interventions has grown tremendously in recent years. This growth has fueled the development of new imaging protocols and technologies in parallel to help facilitate these minimally-invasive procedures. Fusion imaging is an exciting new technology that combines the strength of 2 imaging modalities and has the potential to improve procedural planning and the safety of many commonly performed transcatheter procedures. In this review we discuss the basic concepts of fusion imaging along with the relative strengths and weaknesses of static vs dynamic fusion imaging modalities. This review will focus primarily on echocardiographic-fluoroscopic fusion imaging and its application in commonly performed transcatheter structural heart procedures. Copyright © 2017 Sociedad Española de Cardiología. Published by Elsevier España, S.L.U. All rights reserved.
Pixel-level multisensor image fusion based on matrix completion and robust principal component analysis

NASA Astrophysics Data System (ADS)

Wang, Zhuozheng; Deller, J. R.; Fleet, Blair D.

2016-01-01

Acquired digital images are often corrupted by a lack of camera focus, faulty illumination, or missing data. An algorithm is presented for fusion of multiple corrupted images of a scene using the lifting wavelet transform. The method employs adaptive fusion arithmetic based on matrix completion and self-adaptive regional variance estimation. Characteristics of the wavelet coefficients are used to adaptively select fusion rules. Robust principal component analysis is applied to low-frequency image components, and regional variance estimation is applied to high-frequency components. Experiments reveal that the method is effective for multifocus, visible-light, and infrared image fusion. Compared with traditional algorithms, the new algorithm not only increases the amount of preserved information and clarity but also improves robustness.
Application of Multimodality Imaging Fusion Technology in Diagnosis and Treatment of Malignant Tumors under the Precision Medicine Plan.

PubMed

Wang, Shun-Yi; Chen, Xian-Xia; Li, Yi; Zhang, Yu-Ying

2016-12-20

The arrival of precision medicine plan brings new opportunities and challenges for patients undergoing precision diagnosis and treatment of malignant tumors. With the development of medical imaging, information on different modality imaging can be integrated and comprehensively analyzed by imaging fusion system. This review aimed to update the application of multimodality imaging fusion technology in the precise diagnosis and treatment of malignant tumors under the precision medicine plan. We introduced several multimodality imaging fusion technologies and their application to the diagnosis and treatment of malignant tumors in clinical practice. The data cited in this review were obtained mainly from the PubMed database from 1996 to 2016, using the keywords of "precision medicine", "fusion imaging", "multimodality", and "tumor diagnosis and treatment". Original articles, clinical practice, reviews, and other relevant literatures published in English were reviewed. Papers focusing on precision medicine, fusion imaging, multimodality, and tumor diagnosis and treatment were selected. Duplicated papers were excluded. Multimodality imaging fusion technology plays an important role in tumor diagnosis and treatment under the precision medicine plan, such as accurate location, qualitative diagnosis, tumor staging, treatment plan design, and real-time intraoperative monitoring. Multimodality imaging fusion systems could provide more imaging information of tumors from different dimensions and angles, thereby offing strong technical support for the implementation of precision oncology. Under the precision medicine plan, personalized treatment of tumors is a distinct possibility. We believe that multimodality imaging fusion technology will find an increasingly wide application in clinical practice.
Framework for 2D-3D image fusion of infrared thermography with preoperative MRI.

PubMed

Hoffmann, Nico; Weidner, Florian; Urban, Peter; Meyer, Tobias; Schnabel, Christian; Radev, Yordan; Schackert, Gabriele; Petersohn, Uwe; Koch, Edmund; Gumhold, Stefan; Steiner, Gerald; Kirsch, Matthias

2017-11-27

Multimodal medical image fusion combines information of one or more images in order to improve the diagnostic value. While previous applications mainly focus on merging images from computed tomography, magnetic resonance imaging (MRI), ultrasonic and single-photon emission computed tomography, we propose a novel approach for the registration and fusion of preoperative 3D MRI with intraoperative 2D infrared thermography. Image-guided neurosurgeries are based on neuronavigation systems, which further allow us track the position and orientation of arbitrary cameras. Hereby, we are able to relate the 2D coordinate system of the infrared camera with the 3D MRI coordinate system. The registered image data are now combined by calibration-based image fusion in order to map our intraoperative 2D thermographic images onto the respective brain surface recovered from preoperative MRI. In extensive accuracy measurements, we found that the proposed framework achieves a mean accuracy of 2.46 mm.
SCAR/WAVE and Arp2/3 are critical for cytoskeletal remodeling at the site of myoblast fusion

PubMed Central

Richardson, Brian E.; Beckett, Karen; Nowak, Scott J.; Baylies, Mary K.

2010-01-01

Summary Myoblast fusion is critical for formation and repair of skeletal muscle. Here we show that active remodeling of the actin cytoskeleton is essential for fusion in Drosophila. Using live imaging, we have identified a dynamic F-actin accumulation (actin focus) at the site of fusion. Dissolution of the actin focus directly precedes a fusion event. Whereas several known fusion components regulate these actin foci, others target additional behaviors required for fusion. Mutations in kette/Nap1, an actin polymerization regulator, lead to enlarged foci that do not dissolve, consistent with the observed block in fusion. Kette is required to positively regulate SCAR/WAVE, which in turn activates the Arp2/3 complex. Mutants in SCAR and Arp2/3 have a fusion block and foci phenotype, suggesting that Kette-SCAR-Arp2/3 participate in an actin polymerization event required for focus dissolution. Our data identify a new paradigm for understanding the mechanisms underlying fusion in myoblasts and other tissues. PMID:18003739
Multi-scale pixel-based image fusion using multivariate empirical mode decomposition.

PubMed

Rehman, Naveed ur; Ehsan, Shoaib; Abdullah, Syed Muhammad Umer; Akhtar, Muhammad Jehanzaib; Mandic, Danilo P; McDonald-Maier, Klaus D

2015-05-08

A novel scheme to perform the fusion of multiple images using the multivariate empirical mode decomposition (MEMD) algorithm is proposed. Standard multi-scale fusion techniques make a priori assumptions regarding input data, whereas standard univariate empirical mode decomposition (EMD)-based fusion techniques suffer from inherent mode mixing and mode misalignment issues, characterized respectively by either a single intrinsic mode function (IMF) containing multiple scales or the same indexed IMFs corresponding to multiple input images carrying different frequency information. We show that MEMD overcomes these problems by being fully data adaptive and by aligning common frequency scales from multiple channels, thus enabling their comparison at a pixel level and subsequent fusion at multiple data scales. We then demonstrate the potential of the proposed scheme on a large dataset of real-world multi-exposure and multi-focus images and compare the results against those obtained from standard fusion algorithms, including the principal component analysis (PCA), discrete wavelet transform (DWT) and non-subsampled contourlet transform (NCT). A variety of image fusion quality measures are employed for the objective evaluation of the proposed method. We also report the results of a hypothesis testing approach on our large image dataset to identify statistically-significant performance differences.
Multi-Scale Pixel-Based Image Fusion Using Multivariate Empirical Mode Decomposition

PubMed Central

Rehman, Naveed ur; Ehsan, Shoaib; Abdullah, Syed Muhammad Umer; Akhtar, Muhammad Jehanzaib; Mandic, Danilo P.; McDonald-Maier, Klaus D.

2015-01-01

A novel scheme to perform the fusion of multiple images using the multivariate empirical mode decomposition (MEMD) algorithm is proposed. Standard multi-scale fusion techniques make a priori assumptions regarding input data, whereas standard univariate empirical mode decomposition (EMD)-based fusion techniques suffer from inherent mode mixing and mode misalignment issues, characterized respectively by either a single intrinsic mode function (IMF) containing multiple scales or the same indexed IMFs corresponding to multiple input images carrying different frequency information. We show that MEMD overcomes these problems by being fully data adaptive and by aligning common frequency scales from multiple channels, thus enabling their comparison at a pixel level and subsequent fusion at multiple data scales. We then demonstrate the potential of the proposed scheme on a large dataset of real-world multi-exposure and multi-focus images and compare the results against those obtained from standard fusion algorithms, including the principal component analysis (PCA), discrete wavelet transform (DWT) and non-subsampled contourlet transform (NCT). A variety of image fusion quality measures are employed for the objective evaluation of the proposed method. We also report the results of a hypothesis testing approach on our large image dataset to identify statistically-significant performance differences. PMID:26007714
Multifocus image fusion scheme based on the multiscale curvature in nonsubsampled contourlet transform domain

NASA Astrophysics Data System (ADS)

Li, Xiaosong; Li, Huafeng; Yu, Zhengtao; Kong, Yingchun

2015-07-01

An efficient multifocus image fusion scheme in nonsubsampled contourlet transform (NSCT) domain is proposed. Based on the property of optical imaging and the theory of defocused image, we present a selection principle for lowpass frequency coefficients and also investigate the connection between a low-frequency image and the defocused image. Generally, the NSCT algorithm decomposes detail image information indwells in different scales and different directions in the bandpass subband coefficient. In order to correctly pick out the prefused bandpass directional coefficients, we introduce multiscale curvature, which not only inherits the advantages of windows with different sizes, but also correctly recognizes the focused pixels from source images, and then develop a new fusion scheme of the bandpass subband coefficients. The fused image can be obtained by inverse NSCT with the different fused coefficients. Several multifocus image fusion methods are compared with the proposed scheme. The experimental results clearly indicate the validity and superiority of the proposed scheme in terms of both the visual qualities and the quantitative evaluation.
Salient region detection by fusing bottom-up and top-down features extracted from a single image.

PubMed

Tian, Huawei; Fang, Yuming; Zhao, Yao; Lin, Weisi; Ni, Rongrong; Zhu, Zhenfeng

2014-10-01

Recently, some global contrast-based salient region detection models have been proposed based on only the low-level feature of color. It is necessary to consider both color and orientation features to overcome their limitations, and thus improve the performance of salient region detection for images with low-contrast in color and high-contrast in orientation. In addition, the existing fusion methods for different feature maps, like the simple averaging method and the selective method, are not effective sufficiently. To overcome these limitations of existing salient region detection models, we propose a novel salient region model based on the bottom-up and top-down mechanisms: the color contrast and orientation contrast are adopted to calculate the bottom-up feature maps, while the top-down cue of depth-from-focus from the same single image is used to guide the generation of final salient regions, since depth-from-focus reflects the photographer's preference and knowledge of the task. A more general and effective fusion method is designed to combine the bottom-up feature maps. According to the degree-of-scattering and eccentricities of feature maps, the proposed fusion method can assign adaptive weights to different feature maps to reflect the confidence level of each feature map. The depth-from-focus of the image as a significant top-down feature for visual attention in the image is used to guide the salient regions during the fusion process; with its aid, the proposed fusion method can filter out the background and highlight salient regions for the image. Experimental results show that the proposed model outperforms the state-of-the-art models on three public available data sets.
Comparison Between CT and MR Images as More Favorable Reference Data Sets for Fusion Imaging-Guided Radiofrequency Ablation or Biopsy of Hepatic Lesions: A Prospective Study with Focus on Patient's Respiration.

PubMed

Cha, Dong Ik; Lee, Min Woo; Kang, Tae Wook; Oh, Young-Taek; Jeong, Ja-Yeon; Chang, Jung-Woo; Ryu, Jiwon; Lee, Kyong Joon; Kim, Jaeil; Bang, Won-Chul; Shin, Dong Kuk; Choi, Sung Jin; Koh, Dalkwon; Kim, Kyunga

2017-10-01

To identify the more accurate reference data sets for fusion imaging-guided radiofrequency ablation or biopsy of hepatic lesions between computed tomography (CT) and magnetic resonance (MR) images. This study was approved by the institutional review board, and written informed consent was received from all patients. Twelve consecutive patients who were referred to assess the feasibility of radiofrequency ablation or biopsy were enrolled. Automatic registration using CT and MR images was performed in each patient. Registration errors during optimal and opposite respiratory phases, time required for image fusion and number of point locks used were compared using the Wilcoxon signed-rank test. The registration errors during optimal respiratory phase were not significantly different between image fusion using CT and MR images as reference data sets (p = 0.969). During opposite respiratory phase, the registration error was smaller with MR images than CT (p = 0.028). The time and the number of points locks needed for complete image fusion were not significantly different between CT and MR images (p = 0.328 and p = 0.317, respectively). MR images would be more suitable as the reference data set for fusion imaging-guided procedures of focal hepatic lesions than CT images.
Direct fusion of geostationary meteorological satellite visible and infrared images based on thermal physical properties.

PubMed

Han, Lei; Wulie, Buzha; Yang, Yiling; Wang, Hongqing

2015-01-05

This study investigated a novel method of fusing visible (VIS) and infrared (IR) images with the major objective of obtaining higher-resolution IR images. Most existing image fusion methods focus only on visual performance and many fail to consider the thermal physical properties of the IR images, leading to spectral distortion in the fused image. In this study, we use the IR thermal physical property to correct the VIS image directly. Specifically, the Stefan-Boltzmann Law is used as a strong constraint to modulate the VIS image, such that the fused result shows a similar level of regional thermal energy as the original IR image, while preserving the high-resolution structural features from the VIS image. This method is an improvement over our previous study, which required VIS-IR multi-wavelet fusion before the same correction method was applied. The results of experiments show that applying this correction to the VIS image directly without multi-resolution analysis (MRA) processing achieves similar results, but is considerably more computationally efficient, thereby providing a new perspective on VIS and IR image fusion.
Direct Fusion of Geostationary Meteorological Satellite Visible and Infrared Images Based on Thermal Physical Properties

PubMed Central

Han, Lei; Wulie, Buzha; Yang, Yiling; Wang, Hongqing

2015-01-01

This study investigated a novel method of fusing visible (VIS) and infrared (IR) images with the major objective of obtaining higher-resolution IR images. Most existing image fusion methods focus only on visual performance and many fail to consider the thermal physical properties of the IR images, leading to spectral distortion in the fused image. In this study, we use the IR thermal physical property to correct the VIS image directly. Specifically, the Stefan-Boltzmann Law is used as a strong constraint to modulate the VIS image, such that the fused result shows a similar level of regional thermal energy as the original IR image, while preserving the high-resolution structural features from the VIS image. This method is an improvement over our previous study, which required VIS-IR multi-wavelet fusion before the same correction method was applied. The results of experiments show that applying this correction to the VIS image directly without multi-resolution analysis (MRA) processing achieves similar results, but is considerably more computationally efficient, thereby providing a new perspective on VIS and IR image fusion. PMID:25569749
Detection of buried objects by fusing dual-band infrared images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Clark, G.A.; Sengupta, S.K.; Sherwood, R.J.

1993-11-01

We have conducted experiments to demonstrate the enhanced detectability of buried land mines using sensor fusion techniques. Multiple sensors, including visible imagery, infrared imagery, and ground penetrating radar (GPR), have been used to acquire data on a number of buried mines and mine surrogates. Because the visible wavelength and GPR data are currently incomplete. This paper focuses on the fusion of two-band infrared images. We use feature-level fusion and supervised learning with the probabilistic neural network (PNN) to evaluate detection performance. The novelty of the work lies in the application of advanced target recognition algorithms, the fusion of dual-band infraredmore » images and evaluation of the techniques using two real data sets.« less
Proceedings of the Augmented VIsual Display (AVID) Research Workshop

NASA Technical Reports Server (NTRS)

Kaiser, Mary K. (Editor); Sweet, Barbara T. (Editor)

1993-01-01

The papers, abstracts, and presentations were presented at a three day workshop focused on sensor modeling and simulation, and image enhancement, processing, and fusion. The technical sessions emphasized how sensor technology can be used to create visual imagery adequate for aircraft control and operations. Participants from industry, government, and academic laboratories contributed to panels on Sensor Systems, Sensor Modeling, Sensor Fusion, Image Processing (Computer and Human Vision), and Image Evaluation and Metrics.
Comparison and evaluation on image fusion methods for GaoFen-1 imagery

NASA Astrophysics Data System (ADS)

Zhang, Ningyu; Zhao, Junqing; Zhang, Ling

2016-10-01

Currently, there are many research works focusing on the best fusion method suitable for satellite images of SPOT, QuickBird, Landsat and so on, but only a few of them discuss the application of GaoFen-1 satellite images. This paper proposes a novel idea by using four fusion methods, such as principal component analysis transform, Brovey transform, hue-saturation-value transform, and Gram-Schmidt transform, from the perspective of keeping the original image spectral information. The experimental results showed that the transformed images by the four fusion methods not only retain high spatial resolution on panchromatic band but also have the abundant spectral information. Through comparison and evaluation, the integration of Brovey transform is better, but the color fidelity is not the premium. The brightness and color distortion in hue saturation-value transformed image is the largest. Principal component analysis transform did a good job in color fidelity, but its clarity still need improvement. Gram-Schmidt transform works best in color fidelity, and the edge of the vegetation is the most obvious, the fused image sharpness is higher than that of principal component analysis. Brovey transform, is suitable for distinguishing the Gram-Schmidt transform, and the most appropriate for GaoFen-1 satellite image in vegetation and non-vegetation area. In brief, different fusion methods have different advantages in image quality and class extraction, and should be used according to the actual application information and image fusion algorithm.
Multi-Focus Image Fusion Based on NSCT and NSST

NASA Astrophysics Data System (ADS)

Moonon, Altan-Ulzii; Hu, Jianwen

2015-12-01

In this paper, a multi-focus image fusion algorithm based on the nonsubsampled contourlet transform (NSCT) and the nonsubsampled shearlet transform (NSST) is proposed. The source images are first decomposed by the NSCT and NSST into low frequency coefficients and high frequency coefficients. Then, the average method is used to fuse low frequency coefficient of the NSCT. To obtain more accurate salience measurement, the high frequency coefficients of the NSST and NSCT are combined to measure salience. The high frequency coefficients of the NSCT with larger salience are selected as fused high frequency coefficients. Finally, the fused image is reconstructed by the inverse NSCT. We adopt three metrics (Q AB/F , Q e and Q w ) to evaluate the quality of fused images. The experimental results demonstrate that the proposed method outperforms other methods. It retains highly detailed edges and contours.
Comparing fusion techniques for the ImageCLEF 2013 medical case retrieval task.

PubMed

G Seco de Herrera, Alba; Schaer, Roger; Markonis, Dimitrios; Müller, Henning

2015-01-01

Retrieval systems can supply similar cases with a proven diagnosis to a new example case under observation to help clinicians during their work. The ImageCLEFmed evaluation campaign proposes a framework where research groups can compare case-based retrieval approaches. This paper focuses on the case-based task and adds results of the compound figure separation and modality classification tasks. Several fusion approaches are compared to identify the approaches best adapted to the heterogeneous data of the task. Fusion of visual and textual features is analyzed, demonstrating that the selection of the fusion strategy can improve the best performance on the case-based retrieval task. Copyright © 2014 Elsevier Ltd. All rights reserved.
[Magnetic resonance imaging in facial injuries and digital fusion CT/MRI].

PubMed

Kozakiewicz, Marcin; Olszycki, Marek; Arkuszewski, Piotr; Stefańczyk, Ludomir

2006-01-01

Magnetic resonance images [MRI] and their digital fusion with computed tomography [CT] data, observed in patients affected with facial injuries, are presented in this study. The MR imaging of 12 posttraumatic patients was performed in the same plains as their previous CT scans. Evaluation focused on quality of the facial soft tissues depicting, which was unsatisfactory in CT. Using the own "Dental Studio" programme the digital fusion of the both modalities was performed. Pathologic dislocations and injures of facial soft tissues are visualized better in MRI than in CT examination. Especially MRI properly reveals disturbances in intraorbital soft structures. MRI-based assessment is valuable in patients affected with facial soft tissues injuries, especially in case of orbita/sinuses hernia. Fusion CT/MRI scans allows to evaluate simultaneously bone structure and soft tissues of the same region.

Multi-focus image fusion algorithm using NSCT and MPCNN

NASA Astrophysics Data System (ADS)

Liu, Kang; Wang, Lianli

2018-04-01

Based on nonsubsampled contourlet transform (NSCT) and modified pulse coupled neural network (MPCNN), the paper proposes an effective method of image fusion. Firstly, the paper decomposes the source image into the low-frequency components and high-frequency components using NSCT, and then processes the low-frequency components by regional statistical fusion rules. For high-frequency components, the paper calculates the spatial frequency (SF), which is input into MPCNN model to get relevant coefficients according to the fire-mapping image of MPCNN. At last, the paper restructures the final image by inverse transformation of low-frequency and high-frequency components. Compared with the wavelet transformation (WT) and the traditional NSCT algorithm, experimental results indicate that the method proposed in this paper achieves an improvement both in human visual perception and objective evaluation. It indicates that the method is effective, practical and good performance.
[Fusion of MRI, fMRI and intraoperative MRI data. Methods and clinical significance exemplified by neurosurgical interventions].

PubMed

Moche, M; Busse, H; Dannenberg, C; Schulz, T; Schmitgen, A; Trantakis, C; Winkler, D; Schmidt, F; Kahn, T

2001-11-01

The aim of this work was to realize and clinically evaluate an image fusion platform for the integration of preoperative MRI and fMRI data into the intraoperative images of an interventional MRI system with a focus on neurosurgical procedures. A vertically open 0.5 T MRI scanner was equipped with a dedicated navigation system enabling the registration of additional imaging modalities (MRI, fMRI, CT) with the intraoperatively acquired data sets. These merged image data served as the basis for interventional planning and multimodal navigation. So far, the system has been used in 70 neurosurgical interventions (13 of which involved image data fusion--requiring 15 minutes extra time). The augmented navigation system is characterized by a higher frame rate and a higher image quality as compared to the system-integrated navigation based on continuously acquired (near) real time images. Patient movement and tissue shifts can be immediately detected by monitoring the morphological differences between both navigation scenes. The multimodal image fusion allowed a refined navigation planning especially for the resection of deeply seated brain lesions or pathologies close to eloquent areas. Augmented intraoperative orientation and instrument guidance improve the safety and accuracy of neurosurgical interventions.
Novel Three-Dimensional Image Fusion Software to Facilitate Guidance of Complex Cardiac Catheterization : 3D image fusion for interventions in CHD.

PubMed

Goreczny, Sebastian; Dryzek, Pawel; Morgan, Gareth J; Lukaszewski, Maciej; Moll, Jadwiga A; Moszura, Tomasz

2017-08-01

We report initial experience with novel three-dimensional (3D) image fusion software for guidance of transcatheter interventions in congenital heart disease. Developments in fusion imaging have facilitated the integration of 3D roadmaps from computed tomography or magnetic resonance imaging datasets. The latest software allows live fusion of two-dimensional (2D) fluoroscopy with pre-registered 3D roadmaps. We reviewed all cardiac catheterizations guided with this software (Philips VesselNavigator). Pre-catheterization imaging and catheterization data were collected focusing on fusion of 3D roadmap, intervention guidance, contrast and radiation exposure. From 09/2015 until 06/2016, VesselNavigator was applied in 34 patients for guidance (n = 28) or planning (n = 6) of cardiac catheterization. In all 28 patients successful 2D-3D registration was performed. Bony structures combined with the cardiovascular silhouette were used for fusion in 26 patients (93%), calcifications in 9 (32%), previously implanted devices in 8 (29%) and low-volume contrast injection in 7 patients (25%). Accurate initial 3D roadmap alignment was achieved in 25 patients (89%). Six patients (22%) required realignment during the procedure due to distortion of the anatomy after introduction of stiff equipment. Overall, VesselNavigator was applied successfully in 27 patients (96%) without any complications related to 3D image overlay. VesselNavigator was useful in guidance of nearly all of cardiac catheterizations. The combination of anatomical markers and low-volume contrast injections allowed reliable 2D-3D registration in the vast majority of patients.
MO-FG-210-02: Implementation of Image-Guided Prostate HDR Brachytherapy Using MR-Ultrasound Fusion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Libby, B.

Ultrasound (US) is one of the most widely used imaging modalities in medical practice. Since US imaging offers real-time imaging capability, it has becomes an excellent option to provide image guidance for brachytherapy (IGBT). (1) The physics and the fundamental principles of US imaging are presented, and the typical steps required to commission an US system for IGBT is provided for illustration. (2) Application of US for prostate HDR brachytherapy, including partial prostate treatments using MR-ultrasound co-registration to enable a focused treatment on the disease within the prostate is also presented. Prostate HDR with US image guidance planning can benefitmore » from real time visualization of the needles, and fusion of the ultrasound images with T2 weighted MR allows the focusing of the treatment to the specific areas of disease within the prostate, so that the entire gland need not be treated. Finally, (3) ultrasound guidance for an eye plaque program is presented. US can be a key component of placement and QA for episcleral plaque brachytherapy for ocular cancer, and the UCLA eye plaque program with US for image guidance is presented to demonstrate the utility of US verification of plaque placement in improving the methods and QA in episcleral plaque brachytherapy. Learning Objectives: To understand the physics of an US system and the necessary aspects of commissioning US for image guided brachytherapy (IGBT). To understand real time planning of prostate HDR using ultrasound, and its application in partial prostate treatments using MR-ultrasound fusion to focus treatment on disease within the prostate. To understand the methods and QA in applying US for localizing the target and the implant during a episcleral plaque brachytherapy procedures.« less
Maximizing Science Return from Future Mars Missions with Onboard Image Analyses

NASA Technical Reports Server (NTRS)

Gulick, V. C.; Morris, R. L.; Bandari, E. B.; Roush, T. L.

2000-01-01

We have developed two new techniques to enhance science return and to decrease returned data volume for near-term Mars missions: 1) multi-spectral image compression and 2) autonomous identification and fusion of in-focus regions in an image series.
Research on polarization imaging information parsing method

NASA Astrophysics Data System (ADS)

Yuan, Hongwu; Zhou, Pucheng; Wang, Xiaolong

2016-11-01

Polarization information parsing plays an important role in polarization imaging detection. This paper focus on the polarization information parsing method: Firstly, the general process of polarization information parsing is given, mainly including polarization image preprocessing, multiple polarization parameters calculation, polarization image fusion and polarization image tracking, etc.; And then the research achievements of the polarization information parsing method are presented, in terms of polarization image preprocessing, the polarization image registration method based on the maximum mutual information is designed. The experiment shows that this method can improve the precision of registration and be satisfied the need of polarization information parsing; In terms of multiple polarization parameters calculation, based on the omnidirectional polarization inversion model is built, a variety of polarization parameter images are obtained and the precision of inversion is to be improve obviously; In terms of polarization image fusion , using fuzzy integral and sparse representation, the multiple polarization parameters adaptive optimal fusion method is given, and the targets detection in complex scene is completed by using the clustering image segmentation algorithm based on fractal characters; In polarization image tracking, the average displacement polarization image characteristics of auxiliary particle filtering fusion tracking algorithm is put forward to achieve the smooth tracking of moving targets. Finally, the polarization information parsing method is applied to the polarization imaging detection of typical targets such as the camouflage target, the fog and latent fingerprints.
A multi-focus image fusion method via region mosaicking on Laplacian pyramids

PubMed Central

Kou, Liang; Zhang, Liguo; Sun, Jianguo; Han, Qilong; Jin, Zilong

2018-01-01

In this paper, a method named Region Mosaicking on Laplacian Pyramids (RMLP) is proposed to fuse multi-focus images that is captured by microscope. First, the Sum-Modified-Laplacian is applied to measure the focus of multi-focus images. Then the density-based region growing algorithm is utilized to segment the focused region mask of each image. Finally, the mask is decomposed into a mask pyramid to supervise region mosaicking on a Laplacian pyramid. The region level pyramid keeps more original information than the pixel level. The experiment results show that RMLP has best performance in quantitative comparison with other methods. In addition, RMLP is insensitive to noise and can reduces the color distortion of the fused images on two datasets. PMID:29771912
An Ultrasound Image-Based Dynamic Fusion Modeling Method for Predicting the Quantitative Impact of In Vivo Liver Motion on Intraoperative HIFU Therapies: Investigations in a Porcine Model

PubMed Central

N'Djin, W. Apoutou; Chapelon, Jean-Yves; Melodelima, David

2015-01-01

Organ motion is a key component in the treatment of abdominal tumors by High Intensity Focused Ultrasound (HIFU), since it may influence the safety, efficacy and treatment time. Here we report the development in a porcine model of an Ultrasound (US) image-based dynamic fusion modeling method for predicting the effect of in vivo motion on intraoperative HIFU treatments performed in the liver in conjunction with surgery. A speckle tracking method was used on US images to quantify in vivo liver motions occurring intraoperatively during breathing and apnea. A fusion modeling of HIFU treatments was implemented by merging dynamic in vivo motion data in a numerical modeling of HIFU treatments. Two HIFU strategies were studied: a spherical focusing delivering 49 juxtapositions of 5-second HIFU exposures and a toroidal focusing using 1 single 40-second HIFU exposure. Liver motions during breathing were spatially homogenous and could be approximated to a rigid motion mainly encountered in the cranial-caudal direction (f = 0.20Hz, magnitude >13mm). Elastic liver motions due to cardiovascular activity, although negligible, were detectable near millimeter-wide sus-hepatic veins (f = 0.96Hz, magnitude <1mm). The fusion modeling quantified the deleterious effects of respiratory motions on the size and homogeneity of a standard “cigar-shaped” millimetric lesion usually predicted after a 5-second single spherical HIFU exposure in stationary tissues (Dice Similarity Coefficient: DSC<45%). This method assessed the ability to enlarge HIFU ablations during respiration, either by juxtaposing “cigar-shaped” lesions with spherical HIFU exposures, or by generating one large single lesion with toroidal HIFU exposures (DSC>75%). Fusion modeling predictions were preliminarily validated in vivo and showed the potential of using a long-duration toroidal HIFU exposure to accelerate the ablation process during breathing (from 0.5 to 6 cm3·min-1). To improve HIFU treatment control, dynamic fusion modeling may be interesting for assessing numerically focusing strategies and motion compensation techniques in more realistic conditions. PMID:26398366
Brain Atlas Fusion from High-Thickness Diagnostic Magnetic Resonance Images by Learning-Based Super-Resolution

PubMed Central

Zhang, Jinpeng; Zhang, Lichi; Xiang, Lei; Shao, Yeqin; Wu, Guorong; Zhou, Xiaodong; Shen, Dinggang; Wang, Qian

2017-01-01

It is fundamentally important to fuse the brain atlas from magnetic resonance (MR) images for many imaging-based studies. Most existing works focus on fusing the atlases from high-quality MR images. However, for low-quality diagnostic images (i.e., with high inter-slice thickness), the problem of atlas fusion has not been addressed yet. In this paper, we intend to fuse the brain atlas from the high-thickness diagnostic MR images that are prevalent for clinical routines. The main idea of our works is to extend the conventional groupwise registration by incorporating a novel super-resolution strategy. The contribution of the proposed super-resolution framework is two-fold. First, each high-thickness subject image is reconstructed to be isotropic by the patch-based sparsity learning. Then, the reconstructed isotropic image is enhanced for better quality through the random-forest-based regression model. In this way, the images obtained by the super-resolution strategy can be fused together by applying the groupwise registration method to construct the required atlas. Our experiments have shown that the proposed framework can effectively solve the problem of atlas fusion from the low-quality brain MR images. PMID:29062159
Brain Atlas Fusion from High-Thickness Diagnostic Magnetic Resonance Images by Learning-Based Super-Resolution.

PubMed

Zhang, Jinpeng; Zhang, Lichi; Xiang, Lei; Shao, Yeqin; Wu, Guorong; Zhou, Xiaodong; Shen, Dinggang; Wang, Qian

2017-03-01

It is fundamentally important to fuse the brain atlas from magnetic resonance (MR) images for many imaging-based studies. Most existing works focus on fusing the atlases from high-quality MR images. However, for low-quality diagnostic images (i.e., with high inter-slice thickness), the problem of atlas fusion has not been addressed yet. In this paper, we intend to fuse the brain atlas from the high-thickness diagnostic MR images that are prevalent for clinical routines. The main idea of our works is to extend the conventional groupwise registration by incorporating a novel super-resolution strategy. The contribution of the proposed super-resolution framework is two-fold. First, each high-thickness subject image is reconstructed to be isotropic by the patch-based sparsity learning. Then, the reconstructed isotropic image is enhanced for better quality through the random-forest-based regression model. In this way, the images obtained by the super-resolution strategy can be fused together by applying the groupwise registration method to construct the required atlas. Our experiments have shown that the proposed framework can effectively solve the problem of atlas fusion from the low-quality brain MR images.
Information fusion for diabetic retinopathy CAD in digital color fundus photographs.

PubMed

Niemeijer, Meindert; Abramoff, Michael D; van Ginneken, Bram

2009-05-01

The purpose of computer-aided detection or diagnosis (CAD) technology has so far been to serve as a second reader. If, however, all relevant lesions in an image can be detected by CAD algorithms, use of CAD for automatic reading or prescreening may become feasible. This work addresses the question how to fuse information from multiple CAD algorithms, operating on multiple images that comprise an exam, to determine a likelihood that the exam is normal and would not require further inspection by human operators. We focus on retinal image screening for diabetic retinopathy, a common complication of diabetes. Current CAD systems are not designed to automatically evaluate complete exams consisting of multiple images for which several detection algorithm output sets are available. Information fusion will potentially play a crucial role in enabling the application of CAD technology to the automatic screening problem. Several different fusion methods are proposed and their effect on the performance of a complete comprehensive automatic diabetic retinopathy screening system is evaluated. Experiments show that the choice of fusion method can have a large impact on system performance. The complete system was evaluated on a set of 15,000 exams (60,000 images). The best performing fusion method obtained an area under the receiver operator characteristic curve of 0.881. This indicates that automated prescreening could be applied in diabetic retinopathy screening programs.
Fusion of infrared and visible images based on saliency scale-space in frequency domain

NASA Astrophysics Data System (ADS)

Chen, Yanfei; Sang, Nong; Dan, Zhiping

2015-12-01

A fusion algorithm of infrared and visible images based on saliency scale-space in the frequency domain was proposed. Focus of human attention is directed towards the salient targets which interpret the most important information in the image. For the given registered infrared and visible images, firstly, visual features are extracted to obtain the input hypercomplex matrix. Secondly, the Hypercomplex Fourier Transform (HFT) is used to obtain the salient regions of the infrared and visible images respectively, the convolution of the input hypercomplex matrix amplitude spectrum with a low-pass Gaussian kernel of an appropriate scale which is equivalent to an image saliency detector are done. The saliency maps are obtained by reconstructing the 2D signal using the original phase and the amplitude spectrum, filtered at a scale selected by minimizing saliency map entropy. Thirdly, the salient regions are fused with the adoptive weighting fusion rules, and the nonsalient regions are fused with the rule based on region energy (RE) and region sharpness (RS), then the fused image is obtained. Experimental results show that the presented algorithm can hold high spectrum information of the visual image, and effectively get the thermal targets information at different scales of the infrared image.
Plasma focus neutron anisotropy measurements and influence of a deuteron beam obstacle

NASA Astrophysics Data System (ADS)

Talebitaher, A.; Springham, S. V.; Rawat, R. S.; Lee, P.

2017-03-01

The deuterium-deuterium (DD) fusion neutron yield and anisotropy were measured on a shot-to-shot basis for the NX2 plasma focus (PF) device using two beryllium fast-neutron activation detectors at 0° and 90° to the PF axis. Measurements were performed for deuterium gas pressures in the range 6-16 mbar, and positive correlations between neutron yield and anisotropy were observed at all pressures. Subsequently, at one deuterium gas pressure (13 mbar), the contribution to the fusion yield produced by the forwardly-directed D+ ion beam, emitted from the plasma pinch, was investigated by using a circular Pyrex plate to obstruct the beam and suppress its fusion contribution. Neutron measurements were performed with the obstacle positioned at two distances from the anode tip, and also without the obstacle. It was found that 80% of the neutron yield originates in the plasma pinch column and just above that. In addition, proton pinhole imaging was performed from the 0° and 90° directions to the pinch. The obtained proton images are consistent with the conclusion that DD fusion is concentrated ( 80%) in the pinch column region.
Fusion and quality analysis for remote sensing images using contourlet transform

NASA Astrophysics Data System (ADS)

Choi, Yoonsuk; Sharifahmadian, Ershad; Latifi, Shahram

2013-05-01

Recent developments in remote sensing technologies have provided various images with high spatial and spectral resolutions. However, multispectral images have low spatial resolution and panchromatic images have low spectral resolution. Therefore, image fusion techniques are necessary to improve the spatial resolution of spectral images by injecting spatial details of high-resolution panchromatic images. The objective of image fusion is to provide useful information by improving the spatial resolution and the spectral information of the original images. The fusion results can be utilized in various applications, such as military, medical imaging, and remote sensing. This paper addresses two issues in image fusion: i) image fusion method and ii) quality analysis of fusion results. First, a new contourlet-based image fusion method is presented, which is an improvement over the wavelet-based fusion. This fusion method is then applied to a case study to demonstrate its fusion performance. Fusion framework and scheme used in the study are discussed in detail. Second, quality analysis for the fusion results is discussed. We employed various quality metrics in order to analyze the fusion results both spatially and spectrally. Our results indicate that the proposed contourlet-based fusion method performs better than the conventional wavelet-based fusion methods.
Multimodal fusion of brain imaging data: A key to finding the missing link(s) in complex mental illness

PubMed Central

Calhoun, Vince D; Sui, Jing

2016-01-01

It is becoming increasingly clear that combining multi-modal brain imaging data is able to provide more information for individual subjects by exploiting the rich multimodal information that exists. However, the number of studies that do true multimodal fusion (i.e. capitalizing on joint information among modalities) is still remarkably small given the known benefits. In part, this is because multi-modal studies require broader expertise in collecting, analyzing, and interpreting the results than do unimodal studies. In this paper, we start by introducing the basic reasons why multimodal data fusion is important and what it can do, and importantly how it can help us avoid wrong conclusions and help compensate for imperfect brain imaging studies. We also discuss the challenges that need to be confronted for such approaches to be more widely applied by the community. We then provide a review of the diverse studies that have used multimodal data fusion (primarily focused on psychosis) as well as provide an introduction to some of the existing analytic approaches. Finally, we discuss some up-and-coming approaches to multi-modal fusion including deep learning and multimodal classification which show considerable promise. Our conclusion is that multimodal data fusion is rapidly growing, but it is still underutilized. The complexity of the human brain coupled with the incomplete measurement provided by existing imaging technology makes multimodal fusion essential in order to mitigate against misdirection and hopefully provide a key to finding the missing link(s) in complex mental illness. PMID:27347565
Multimodal fusion of brain imaging data: A key to finding the missing link(s) in complex mental illness.

PubMed

Calhoun, Vince D; Sui, Jing

2016-05-01

It is becoming increasingly clear that combining multi-modal brain imaging data is able to provide more information for individual subjects by exploiting the rich multimodal information that exists. However, the number of studies that do true multimodal fusion (i.e. capitalizing on joint information among modalities) is still remarkably small given the known benefits. In part, this is because multi-modal studies require broader expertise in collecting, analyzing, and interpreting the results than do unimodal studies. In this paper, we start by introducing the basic reasons why multimodal data fusion is important and what it can do, and importantly how it can help us avoid wrong conclusions and help compensate for imperfect brain imaging studies. We also discuss the challenges that need to be confronted for such approaches to be more widely applied by the community. We then provide a review of the diverse studies that have used multimodal data fusion (primarily focused on psychosis) as well as provide an introduction to some of the existing analytic approaches. Finally, we discuss some up-and-coming approaches to multi-modal fusion including deep learning and multimodal classification which show considerable promise. Our conclusion is that multimodal data fusion is rapidly growing, but it is still underutilized. The complexity of the human brain coupled with the incomplete measurement provided by existing imaging technology makes multimodal fusion essential in order to mitigate against misdirection and hopefully provide a key to finding the missing link(s) in complex mental illness.
Nighttime images fusion based on Laplacian pyramid

NASA Astrophysics Data System (ADS)

Wu, Cong; Zhan, Jinhao; Jin, Jicheng

2018-02-01

This paper expounds method of the average weighted fusion, image pyramid fusion, the wavelet transform and apply these methods on the fusion of multiple exposures nighttime images. Through calculating information entropy and cross entropy of fusion images, we can evaluate the effect of different fusion. Experiments showed that Laplacian pyramid image fusion algorithm is suitable for processing nighttime images fusion, it can reduce the halo while preserving image details.
Multi-PSF fusion in image restoration of range-gated systems

NASA Astrophysics Data System (ADS)

Wang, Canjin; Sun, Tao; Wang, Tingfeng; Miao, Xikui; Wang, Rui

2018-07-01

For the task of image restoration, an accurate estimation of degrading PSF/kernel is the premise of recovering a visually superior image. The imaging process of range-gated imaging system in atmosphere associates with lots of factors, such as back scattering, background radiation, diffraction limit and the vibration of the platform. On one hand, due to the difficulty of constructing models for all factors, the kernels from physical-model based methods are not strictly accurate and practical. On the other hand, there are few strong edges in images, which brings significant errors to most of image-feature-based methods. Since different methods focus on different formation factors of the kernel, their results often complement each other. Therefore, we propose an approach which combines physical model with image features. With an fusion strategy using GCRF (Gaussian Conditional Random Fields) framework, we get a final kernel which is closer to the actual one. Aiming at the problem that ground-truth image is difficult to obtain, we then propose a semi data-driven fusion method in which different data sets are used to train fusion parameters. Finally, a semi blind restoration strategy based on EM (Expectation Maximization) and RL (Richardson-Lucy) algorithm is proposed. Our methods not only models how the lasers transfer in the atmosphere and imaging in the ICCD (Intensified CCD) plane, but also quantifies other unknown degraded factors using image-based methods, revealing how multiple kernel elements interact with each other. The experimental results demonstrate that our method achieves better performance than state-of-the-art restoration approaches.
A novel imaging method for photonic crystal fiber fusion splicer

NASA Astrophysics Data System (ADS)

Bi, Weihong; Fu, Guangwei; Guo, Xuan

2007-01-01

Because the structure of Photonic Crystal Fiber (PCF) is very complex, and it is very difficult that traditional fiber fusion splice obtains optical axial information of PCF. Therefore, we must search for a bran-new optical imaging method to get section information of Photonic Crystal Fiber. Based on complex trait of PCF, a novel high-precision optics imaging system is presented in this article. The system uses a thinned electron-bombarded CCD (EBCCD) which is a kind of image sensor as imaging element, the thinned electron-bombarded CCD can offer low light level performance superior to conventional image intensifier coupled CCD approaches, this high-performance device can provide high contrast high resolution in low light level surveillance imaging; in order to realize precision focusing of image, we use a ultra-highprecision pace motor to adjust position of imaging lens. In this way, we can obtain legible section information of PCF. We may realize further concrete analysis for section information of PCF by digital image processing technology. Using this section information may distinguish different sorts of PCF, compute some parameters such as the size of PCF ventage, cladding structure of PCF and so on, and provide necessary analysis data for PCF fixation, adjustment, regulation, fusion and cutting system.
Registration and Fusion of Multiple Source Remotely Sensed Image Data

NASA Technical Reports Server (NTRS)

LeMoigne, Jacqueline

2004-01-01

Earth and Space Science often involve the comparison, fusion, and integration of multiple types of remotely sensed data at various temporal, radiometric, and spatial resolutions. Results of this integration may be utilized for global change analysis, global coverage of an area at multiple resolutions, map updating or validation of new instruments, as well as integration of data provided by multiple instruments carried on multiple platforms, e.g. in spacecraft constellations or fleets of planetary rovers. Our focus is on developing methods to perform fast, accurate and automatic image registration and fusion. General methods for automatic image registration are being reviewed and evaluated. Various choices for feature extraction, feature matching and similarity measurements are being compared, including wavelet-based algorithms, mutual information and statistically robust techniques. Our work also involves studies related to image fusion and investigates dimension reduction and co-kriging for application-dependent fusion. All methods are being tested using several multi-sensor datasets, acquired at EOS Core Sites, and including multiple sensors such as IKONOS, Landsat-7/ETM+, EO1/ALI and Hyperion, MODIS, and SeaWIFS instruments. Issues related to the coregistration of data from the same platform (i.e., AIRS and MODIS from Aqua) or from several platforms of the A-train (i.e., MLS, HIRDLS, OMI from Aura with AIRS and MODIS from Terra and Aqua) will also be considered.

Thermal Physical Property-Based Fusion of Geostationary Meteorological Satellite Visible and Infrared Channel Images

PubMed Central

Han, Lei; Shi, Lu; Yang, Yiling; Song, Dalei

2014-01-01

Geostationary meteorological satellite infrared (IR) channel data contain important spectral information for meteorological research and applications, but their spatial resolution is relatively low. The objective of this study is to obtain higher-resolution IR images. One common method of increasing resolution fuses the IR data with high-resolution visible (VIS) channel data. However, most existing image fusion methods focus only on visual performance, and often fail to take into account the thermal physical properties of the IR images. As a result, spectral distortion occurs frequently. To tackle this problem, we propose a thermal physical properties-based correction method for fusing geostationary meteorological satellite IR and VIS images. In our two-step process, the high-resolution structural features of the VIS image are first extracted and incorporated into the IR image using regular multi-resolution fusion approach, such as the multiwavelet analysis. This step significantly increases the visual details in the IR image, but fake thermal information may be included. Next, the Stefan-Boltzmann Law is applied to correct the distortion, to retain or recover the thermal infrared nature of the fused image. The results of both the qualitative and quantitative evaluation demonstrate that the proposed physical correction method both improves the spatial resolution and preserves the infrared thermal properties. PMID:24919017
Thermal physical property-based fusion of geostationary meteorological satellite visible and infrared channel images.

PubMed

Han, Lei; Shi, Lu; Yang, Yiling; Song, Dalei

2014-06-10

Geostationary meteorological satellite infrared (IR) channel data contain important spectral information for meteorological research and applications, but their spatial resolution is relatively low. The objective of this study is to obtain higher-resolution IR images. One common method of increasing resolution fuses the IR data with high-resolution visible (VIS) channel data. However, most existing image fusion methods focus only on visual performance, and often fail to take into account the thermal physical properties of the IR images. As a result, spectral distortion occurs frequently. To tackle this problem, we propose a thermal physical properties-based correction method for fusing geostationary meteorological satellite IR and VIS images. In our two-step process, the high-resolution structural features of the VIS image are first extracted and incorporated into the IR image using regular multi-resolution fusion approach, such as the multiwavelet analysis. This step significantly increases the visual details in the IR image, but fake thermal information may be included. Next, the Stefan-Boltzmann Law is applied to correct the distortion, to retain or recover the thermal infrared nature of the fused image. The results of both the qualitative and quantitative evaluation demonstrate that the proposed physical correction method both improves the spatial resolution and preserves the infrared thermal properties.
Autofocus algorithm using one-dimensional Fourier transform and Pearson correlation

NASA Astrophysics Data System (ADS)

Bueno Mario, A.; Alvarez-Borrego, Josue; Acho, L.

2004-10-01

A new autofocus algorithm based on one-dimensional Fourier transform and Pearson correlation for Z automatized microscope is proposed. Our goal is to determine in fast response time and accuracy, the best focused plane through an algorithm. We capture in bright and dark field several images set at different Z distances from biological organism sample. The algorithm uses the one-dimensional Fourier transform to obtain the image frequency content of a vectors pattern previously defined comparing the Pearson correlation of these frequency vectors versus the reference image frequency vector, the most out of focus image, we find the best focusing. Experimental results showed the algorithm has fast response time and accuracy in getting the best focus plane from captured images. In conclusions, the algorithm can be implemented in real time systems due fast response time, accuracy and robustness. The algorithm can be used to get focused images in bright and dark field and it can be extended to include fusion techniques to construct multifocus final images beyond of this paper.
Enhanced Deforestation Mapping in North Korea using Spatial-temporal Image Fusion Method and Phenology-based Index

NASA Astrophysics Data System (ADS)

Jin, Y.; Lee, D.

2017-12-01

North Korea (the Democratic People's Republic of Korea, DPRK) is known to have some of the most degraded forest in the world. The characteristics of forest landscape in North Korea is complex and heterogeneous, the major vegetation cover types in the forest are hillside farm, unstocked forest, natural forest, and plateau vegetation. Better classification of types in high spatial resolution of deforested areas could provide essential information for decisions about forest management priorities and restoration of deforested areas. For mapping heterogeneous vegetation covers, the phenology-based indices are helpful to overcome the reflectance value confusion that occurs when using one season images. Coarse spatial resolution images may be acquired with a high repetition rate and it is useful for analyzing phenology characteristics, but may not capture the spatial detail of the land cover mosaic of the region of interest. Previous spatial-temporal fusion methods were only capture the temporal change, or focused on both temporal change and spatial change but with low accuracy in heterogeneous landscapes and small patches. In this study, a new concept for spatial-temporal image fusion method focus on heterogeneous landscape was proposed to produce fine resolution images at both fine spatial and temporal resolution. We classified the three types of pixels between the base image and target image, the first type is only reflectance changed caused by phenology, this type of pixels supply the reflectance, shape and texture information; the second type is both reflectance and spectrum changed in some bands caused by phenology like rice paddy or farmland, this type of pixels only supply shape and texture information; the third type is reflectance and spectrum changed caused by land cover type change, this type of pixels don't provide any information because we can't know how land cover changed in target image; and each type of pixels were applied different prediction methods. Results show that both STARFM and FSDAF predicted in low accuracy in second type pixels and small patches. Classification results used spatial-temporal image fusion method proposed in this study showed overall classification accuracy of 89.38%, with corresponding kappa coefficients of 0.87.
Spectral edge: gradient-preserving spectral mapping for image fusion.

PubMed

Connah, David; Drew, Mark S; Finlayson, Graham D

2015-12-01

This paper describes a novel approach to image fusion for color display. Our goal is to generate an output image whose gradient matches that of the input as closely as possible. We achieve this using a constrained contrast mapping paradigm in the gradient domain, where the structure tensor of a high-dimensional gradient representation is mapped exactly to that of a low-dimensional gradient field which is then reintegrated to form an output. Constraints on output colors are provided by an initial RGB rendering. Initially, we motivate our solution with a simple "ansatz" (educated guess) for projecting higher-D contrast onto color gradients, which we expand to a more rigorous theorem to incorporate color constraints. The solution to these constrained optimizations is closed-form, allowing for simple and hence fast and efficient algorithms. The approach can map any N-D image data to any M-D output and can be used in a variety of applications using the same basic algorithm. In this paper, we focus on the problem of mapping N-D inputs to 3D color outputs. We present results in five applications: hyperspectral remote sensing, fusion of color and near-infrared or clear-filter images, multilighting imaging, dark flash, and color visualization of magnetic resonance imaging diffusion-tensor imaging.
Novel cooperative neural fusion algorithms for image restoration and image fusion.

PubMed

Xia, Youshen; Kamel, Mohamed S

2007-02-01

To deal with the problem of restoring degraded images with non-Gaussian noise, this paper proposes a novel cooperative neural fusion regularization (CNFR) algorithm for image restoration. Compared with conventional regularization algorithms for image restoration, the proposed CNFR algorithm can relax need of the optimal regularization parameter to be estimated. Furthermore, to enhance the quality of restored images, this paper presents a cooperative neural fusion (CNF) algorithm for image fusion. Compared with existing signal-level image fusion algorithms, the proposed CNF algorithm can greatly reduce the loss of contrast information under blind Gaussian noise environments. The performance analysis shows that the proposed two neural fusion algorithms can converge globally to the robust and optimal image estimate. Simulation results confirm that in different noise environments, the proposed two neural fusion algorithms can obtain a better image estimate than several well known image restoration and image fusion methods.
Face-iris multimodal biometric scheme based on feature level fusion

NASA Astrophysics Data System (ADS)

Huo, Guang; Liu, Yuanning; Zhu, Xiaodong; Dong, Hongxing; He, Fei

2015-11-01

Unlike score level fusion, feature level fusion demands all the features extracted from unimodal traits with high distinguishability, as well as homogeneity and compatibility, which is difficult to achieve. Therefore, most multimodal biometric research focuses on score level fusion, whereas few investigate feature level fusion. We propose a face-iris recognition method based on feature level fusion. We build a special two-dimensional-Gabor filter bank to extract local texture features from face and iris images, and then transform them by histogram statistics into an energy-orientation variance histogram feature with lower dimensions and higher distinguishability. Finally, through a fusion-recognition strategy based on principal components analysis and support vector machine (FRSPS), feature level fusion and one-to-n identification are accomplished. The experimental results demonstrate that this method can not only effectively extract face and iris features but also provide higher recognition accuracy. Compared with some state-of-the-art fusion methods, the proposed method has a significant performance advantage.
Live-Cell Imaging of Early Steps of Single HIV-1 Infection.

PubMed

Francis, Ashwanth C; Melikyan, Gregory B

2018-05-19

Live-cell imaging of single HIV-1 entry offers a unique opportunity to delineate the spatio-temporal regulation of infection. Novel virus labeling and imaging approaches enable the visualization of key steps of HIV-1 entry leading to nuclear import, integration into the host genome, and viral protein expression. Here, we discuss single virus imaging strategies, focusing on live-cell imaging of single virus fusion and productive uncoating that culminates in HIV-1 infection.
U.S. Army Medical Department

MedlinePlus

... Games, they came ready to play. Read more Image-2 Excerpt-2 Training, technological synergy key to future battlefield care scenarios To obtain a more complete, more mature fusion of technology and Soldier, Army Medicine focuses on ...
Characterization of pulsed (plasma focus) neutron source with image plate and application to neutron radiography

NASA Astrophysics Data System (ADS)

Andola, Sanjay; Niranjan, Ram; Shaikh, A. M.; Rout, R. K.; Kaushik, T. C.; Gupta, S. C.

2013-02-01

Plasma focus device of Mather type developed in house has been used first time for neutron radiography of different objects. The device gives (1.2±0.3) ×109 neutrons per pulse produced by D-D fusion reaction with a pulse width of 50±5 ns. The method involves exposing sample to be radiographed to thermalized D-D neutrons and recording the image on Fuji-film BAS-ND image plates. The thermal neutron component of the moderated beam was estimated using two image plates: a conventional IP for X-rays and gamma rays, and an IP doped with Gd for detecting neutrons.
Invited Review Article: Gas puff imaging diagnostics of edge plasma turbulence in magnetic fusion devices

DOE PAGES

Zweben, S. J.; Terry, J. L.; Stotler, D. P.; ...

2017-04-27

Gas puff imaging (GPI) is a diagnostic of plasma turbulence which uses a puff of neutral gas at the plasma edge to increase the local visible light emission for improved space-time resolution of plasma fluctuations. This paper reviews gas puff imaging diagnostics of edge plasma turbulence in magnetic fusion research, with a focus on the instrumentation, diagnostic cross-checks, and interpretation issues. The gas puff imaging hardware, optics, and detectors are described for about 10 GPI systems implemented over the past similar to 15 years. Comparison of GPI results with other edge turbulence diagnostic results is described, and many common featuresmore » are observed. Here, several issues in the interpretation of GPI measurements are discussed, and potential improvements in hardware and modeling are suggested.« less
Invited Review Article: Gas puff imaging diagnostics of edge plasma turbulence in magnetic fusion devices

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zweben, S. J.; Terry, J. L.; Stotler, D. P.

Gas puff imaging (GPI) is a diagnostic of plasma turbulence which uses a puff of neutral gas at the plasma edge to increase the local visible light emission for improved space-time resolution of plasma fluctuations. This paper reviews gas puff imaging diagnostics of edge plasma turbulence in magnetic fusion research, with a focus on the instrumentation, diagnostic cross-checks, and interpretation issues. The gas puff imaging hardware, optics, and detectors are described for about 10 GPI systems implemented over the past similar to 15 years. Comparison of GPI results with other edge turbulence diagnostic results is described, and many common featuresmore » are observed. Here, several issues in the interpretation of GPI measurements are discussed, and potential improvements in hardware and modeling are suggested.« less
[Research Progress of Multi-Model Medical Image Fusion at Feature Level].

PubMed

Zhang, Junjie; Zhou, Tao; Lu, Huiling; Wang, Huiqun

2016-04-01

Medical image fusion realizes advantage integration of functional images and anatomical images.This article discusses the research progress of multi-model medical image fusion at feature level.We firstly describe the principle of medical image fusion at feature level.Then we analyze and summarize fuzzy sets,rough sets,D-S evidence theory,artificial neural network,principal component analysis and other fusion methods’ applications in medical image fusion and get summery.Lastly,we in this article indicate present problems and the research direction of multi-model medical images in the future.
Enhanced image capture through fusion

NASA Technical Reports Server (NTRS)

Burt, Peter J.; Hanna, Keith; Kolczynski, Raymond J.

1993-01-01

Image fusion may be used to combine images from different sensors, such as IR and visible cameras, to obtain a single composite with extended information content. Fusion may also be used to combine multiple images from a given sensor to form a composite image in which information of interest is enhanced. We present a general method for performing image fusion and show that this method is effective for diverse fusion applications. We suggest that fusion may provide a powerful tool for enhanced image capture with broad utility in image processing and computer vision.
Hybrid Image Fusion for Sharpness Enhancement of Multi-Spectral Lunar Images

NASA Astrophysics Data System (ADS)

Awumah, Anna; Mahanti, Prasun; Robinson, Mark

2016-10-01

Image fusion enhances the sharpness of a multi-spectral (MS) image by incorporating spatial details from a higher-resolution panchromatic (Pan) image [1,2]. Known applications of image fusion for planetary images are rare, although image fusion is well-known for its applications to Earth-based remote sensing. In a recent work [3], six different image fusion algorithms were implemented and their performances were verified with images from the Lunar Reconnaissance Orbiter (LRO) Camera. The image fusion procedure obtained a high-resolution multi-spectral (HRMS) product from the LRO Narrow Angle Camera (used as Pan) and LRO Wide Angle Camera (used as MS) images. The results showed that the Intensity-Hue-Saturation (IHS) algorithm results in a high-spatial quality product while the Wavelet-based image fusion algorithm best preserves spectral quality among all the algorithms. In this work we show the results of a hybrid IHS-Wavelet image fusion algorithm when applied to LROC MS images. The hybrid method provides the best HRMS product - both in terms of spatial resolution and preservation of spectral details. Results from hybrid image fusion can enable new science and increase the science return from existing LROC images.[1] Pohl, Cle, and John L. Van Genderen. "Review article multisensor image fusion in remote sensing: concepts, methods and applications." International journal of remote sensing 19.5 (1998): 823-854.[2] Zhang, Yun. "Understanding image fusion." Photogramm. Eng. Remote Sens 70.6 (2004): 657-661.[3] Mahanti, Prasun et al. "Enhancement of spatial resolution of the LROC Wide Angle Camera images." Archives, XXIII ISPRS Congress Archives (2016).
Infrared and Visual Image Fusion through Fuzzy Measure and Alternating Operators

PubMed Central

Bai, Xiangzhi

2015-01-01

The crucial problem of infrared and visual image fusion is how to effectively extract the image features, including the image regions and details and combine these features into the final fusion result to produce a clear fused image. To obtain an effective fusion result with clear image details, an algorithm for infrared and visual image fusion through the fuzzy measure and alternating operators is proposed in this paper. Firstly, the alternating operators constructed using the opening and closing based toggle operator are analyzed. Secondly, two types of the constructed alternating operators are used to extract the multi-scale features of the original infrared and visual images for fusion. Thirdly, the extracted multi-scale features are combined through the fuzzy measure-based weight strategy to form the final fusion features. Finally, the final fusion features are incorporated with the original infrared and visual images using the contrast enlargement strategy. All the experimental results indicate that the proposed algorithm is effective for infrared and visual image fusion. PMID:26184229
Infrared and Visual Image Fusion through Fuzzy Measure and Alternating Operators.

PubMed

Bai, Xiangzhi

2015-07-15

The crucial problem of infrared and visual image fusion is how to effectively extract the image features, including the image regions and details and combine these features into the final fusion result to produce a clear fused image. To obtain an effective fusion result with clear image details, an algorithm for infrared and visual image fusion through the fuzzy measure and alternating operators is proposed in this paper. Firstly, the alternating operators constructed using the opening and closing based toggle operator are analyzed. Secondly, two types of the constructed alternating operators are used to extract the multi-scale features of the original infrared and visual images for fusion. Thirdly, the extracted multi-scale features are combined through the fuzzy measure-based weight strategy to form the final fusion features. Finally, the final fusion features are incorporated with the original infrared and visual images using the contrast enlargement strategy. All the experimental results indicate that the proposed algorithm is effective for infrared and visual image fusion.
Visualization and Sequencing of Membrane Remodeling Leading to Influenza Virus Fusion

PubMed Central

Gui, Long; Ebner, Jamie L.; Mileant, Alexander; Williams, James A.

2016-01-01

ABSTRACT Protein-mediated membrane fusion is an essential step in many fundamental biological events, including enveloped virus infection. The nature of protein and membrane intermediates and the sequence of membrane remodeling during these essential processes remain poorly understood. Here we used cryo-electron tomography (cryo-ET) to image the interplay between influenza virus and vesicles with a range of lipid compositions. By following the population kinetics of membrane fusion intermediates imaged by cryo-ET, we found that membrane remodeling commenced with the hemagglutinin fusion protein spikes grappling onto the target membrane, followed by localized target membrane dimpling as local clusters of hemagglutinin started to undergo conformational refolding. The local dimples then transitioned to extended, tightly apposed contact zones where the two proximal membrane leaflets were in most cases indistinguishable from each other, suggesting significant dehydration and possible intermingling of the lipid head groups. Increasing the content of fusion-enhancing cholesterol or bis-monoacylglycerophosphate in the target membrane led to an increase in extended contact zone formation. Interestingly, hemifused intermediates were found to be extremely rare in the influenza virus fusion system studied here, most likely reflecting the instability of this state and its rapid conversion to postfusion complexes, which increased in population over time. By tracking the populations of fusion complexes over time, the architecture and sequence of membrane reorganization leading to efficient enveloped virus fusion were thus resolved. IMPORTANCE Enveloped viruses employ specialized surface proteins to mediate fusion of cellular and viral membranes that results in the formation of pores through which the viral genetic material is delivered to the cell. For influenza virus, the trimeric hemagglutinin (HA) glycoprotein spike mediates host cell attachment and membrane fusion. While structures of a subset of conformations and parts of the fusion machinery have been characterized, the nature and sequence of membrane deformations during fusion have largely eluded characterization. Building upon studies that focused on early stages of HA-mediated membrane remodeling, here cryo-electron tomography (cryo-ET) was used to image the three-dimensional organization of intact influenza virions at different stages of fusion with liposomes, leading all the way to completion of the fusion reaction. By monitoring the evolution of fusion intermediate populations over the course of acid-induced fusion, we identified the progression of membrane reorganization that leads to efficient fusion by an enveloped virus. PMID:27226364
Contrast enhanced ultrasound (CEUS) with MRI image fusion for monitoring focal therapy of prostate cancer with high intensity focused ultrasound (HIFU)1.

PubMed

Apfelbeck, M; Clevert, D-A; Ricke, J; Stief, C; Schlenker, B

2018-01-01

Reduced acceptance of radical prostatectomy in patients with low risk or intermediate risk prostate cancer has significantly changed treatment strategies in prostate cancer (PCa) during the last years. Focal therapy of the prostate with high intensity focused ultrasound (HIFU) is an organ-preserving treatment for prostate cancer with less impairment of health-related quality of life. Follow-up after HIFU therapy by imaging modalities remains a major problem as eg. MRI performs poorly. Contrast enhanced ultrasound (CEUS) allows to monitor the vascular architecture of organs non-invasively. However, only limited data are available using CEUS to define successful and complete HIFU treatment of the prostate. In this study, we aimed to evaluate short-term image findings using CEUS and image fusion before and after HIFU treatment. Prospective single arm study in patients with uni- or bilateral, low or intermediate risk prostate cancer or recurrent cancer after radiotherapy treated with HIFU at our institution between October 2016 and November 2017. HIFU hemiablation or whole gland treatment was performed using the Focal One® device. PCa was diagnosed either by multiparametric magnetic resonance imaging (mpMRI) followed by MRI fusion based targeted biopsy combined with 12 core transrectal ultrasound (TRUS) guided biopsy or 12 core random biopsy only. Monitoring of the target region before, immediately and 24 hours after the ablation was done by CEUS in combination with image fusion using an axial T2-weighted MRI sequence. 6 consecutive patients with Gleason score (GS) 6, 5 patients with GS 7a prostate cancer and one patient with biochemical recurrence after radiotherapy were included in the study. Three patients underwent whole gland treatment due to histological proven bilateral PCa or recurrent PCa after radiotherapy. Hemiablation was performed in 9 patients with unilateral tumor and no PIRADS 4 or 5 lesion in the contralateral lobe. Median patient age was 69.8 years and median PSA (prostate-specific antigen) level was 8.4 ng/ml. CEUS showed markedly reduced microbubbles in the ablated area, the prostate capsule still showed signs of perfusion. The study is limited by the short follow up and small number of patients. CEUS examination showed a reduction of microcirculation in the treated area immediately after the treatment and 24 hours later. The combination of CEUS and image fusion seems to be helpful for detecting the PCa target lesion and monitor the success of HIFU ablation treatment. Evidence for image findings after HIFU-therapy are rare. Further studies on this topic are needed.
MO-FG-210-00: US Guided Systems for Brachytherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

Ultrasound (US) is one of the most widely used imaging modalities in medical practice. Since US imaging offers real-time imaging capability, it has becomes an excellent option to provide image guidance for brachytherapy (IGBT). (1) The physics and the fundamental principles of US imaging are presented, and the typical steps required to commission an US system for IGBT is provided for illustration. (2) Application of US for prostate HDR brachytherapy, including partial prostate treatments using MR-ultrasound co-registration to enable a focused treatment on the disease within the prostate is also presented. Prostate HDR with US image guidance planning can benefitmore » from real time visualization of the needles, and fusion of the ultrasound images with T2 weighted MR allows the focusing of the treatment to the specific areas of disease within the prostate, so that the entire gland need not be treated. Finally, (3) ultrasound guidance for an eye plaque program is presented. US can be a key component of placement and QA for episcleral plaque brachytherapy for ocular cancer, and the UCLA eye plaque program with US for image guidance is presented to demonstrate the utility of US verification of plaque placement in improving the methods and QA in episcleral plaque brachytherapy. Learning Objectives: To understand the physics of an US system and the necessary aspects of commissioning US for image guided brachytherapy (IGBT). To understand real time planning of prostate HDR using ultrasound, and its application in partial prostate treatments using MR-ultrasound fusion to focus treatment on disease within the prostate. To understand the methods and QA in applying US for localizing the target and the implant during a episcleral plaque brachytherapy procedures.« less

MO-FG-210-01: Commissioning An US System for Brachytherapy: An Overview of Physics, Instrumentation, and Techniques

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chang, Z.

Ultrasound (US) is one of the most widely used imaging modalities in medical practice. Since US imaging offers real-time imaging capability, it has becomes an excellent option to provide image guidance for brachytherapy (IGBT). (1) The physics and the fundamental principles of US imaging are presented, and the typical steps required to commission an US system for IGBT is provided for illustration. (2) Application of US for prostate HDR brachytherapy, including partial prostate treatments using MR-ultrasound co-registration to enable a focused treatment on the disease within the prostate is also presented. Prostate HDR with US image guidance planning can benefitmore » from real time visualization of the needles, and fusion of the ultrasound images with T2 weighted MR allows the focusing of the treatment to the specific areas of disease within the prostate, so that the entire gland need not be treated. Finally, (3) ultrasound guidance for an eye plaque program is presented. US can be a key component of placement and QA for episcleral plaque brachytherapy for ocular cancer, and the UCLA eye plaque program with US for image guidance is presented to demonstrate the utility of US verification of plaque placement in improving the methods and QA in episcleral plaque brachytherapy. Learning Objectives: To understand the physics of an US system and the necessary aspects of commissioning US for image guided brachytherapy (IGBT). To understand real time planning of prostate HDR using ultrasound, and its application in partial prostate treatments using MR-ultrasound fusion to focus treatment on disease within the prostate. To understand the methods and QA in applying US for localizing the target and the implant during a episcleral plaque brachytherapy procedures.« less
MO-FG-210-03: Intraoperative Ultrasonography-Guided Positioning of Plaque Brachytherapy in the Treatment of Choroidal Melanoma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lamb, J.

2015-06-15

Ultrasound (US) is one of the most widely used imaging modalities in medical practice. Since US imaging offers real-time imaging capability, it has becomes an excellent option to provide image guidance for brachytherapy (IGBT). (1) The physics and the fundamental principles of US imaging are presented, and the typical steps required to commission an US system for IGBT is provided for illustration. (2) Application of US for prostate HDR brachytherapy, including partial prostate treatments using MR-ultrasound co-registration to enable a focused treatment on the disease within the prostate is also presented. Prostate HDR with US image guidance planning can benefitmore » from real time visualization of the needles, and fusion of the ultrasound images with T2 weighted MR allows the focusing of the treatment to the specific areas of disease within the prostate, so that the entire gland need not be treated. Finally, (3) ultrasound guidance for an eye plaque program is presented. US can be a key component of placement and QA for episcleral plaque brachytherapy for ocular cancer, and the UCLA eye plaque program with US for image guidance is presented to demonstrate the utility of US verification of plaque placement in improving the methods and QA in episcleral plaque brachytherapy. Learning Objectives: To understand the physics of an US system and the necessary aspects of commissioning US for image guided brachytherapy (IGBT). To understand real time planning of prostate HDR using ultrasound, and its application in partial prostate treatments using MR-ultrasound fusion to focus treatment on disease within the prostate. To understand the methods and QA in applying US for localizing the target and the implant during a episcleral plaque brachytherapy procedures.« less
Characterization of pulsed (plasma focus) neutron source with image plate and application to neutron radiography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Andola, Sanjay; Niranjan, Ram; Rout, R. K.

Plasma focus device of Mather type developed in house has been used first time for neutron radiography of different objects. The device gives (1.2{+-}0.3) Multiplication-Sign 10{sup 9} neutrons per pulse produced by D-D fusion reaction with a pulse width of 50{+-}5 ns. The method involves exposing sample to be radiographed to thermalized D-D neutrons and recording the image on Fuji-film BAS-ND image plates. The thermal neutron component of the moderated beam was estimated using two image plates: a conventional IP for X-rays and gamma rays, and an IP doped with Gd for detecting neutrons.
A dual-channel fusion system of visual and infrared images based on color transfer

NASA Astrophysics Data System (ADS)

Pei, Chuang; Jiang, Xiao-yu; Zhang, Peng-wei; Liang, Hao-cong

2013-09-01

A dual-channel fusion system of visual and infrared images based on color transfer The increasing availability and deployment of imaging sensors operating in multiple spectrums has led to a large research effort in image fusion, resulting in a plethora of pixel-level image fusion algorithms. However, most of these algorithms have gray or false color fusion results which are not adapt to human vision. Transfer color from a day-time reference image to get natural color fusion result is an effective way to solve this problem, but the computation cost of color transfer is expensive and can't meet the request of real-time image processing. We developed a dual-channel infrared and visual images fusion system based on TMS320DM642 digital signal processing chip. The system is divided into image acquisition and registration unit, image fusion processing unit, system control unit and image fusion result out-put unit. The image registration of dual-channel images is realized by combining hardware and software methods in the system. False color image fusion algorithm in RGB color space is used to get R-G fused image, then the system chooses a reference image to transfer color to the fusion result. A color lookup table based on statistical properties of images is proposed to solve the complexity computation problem in color transfer. The mapping calculation between the standard lookup table and the improved color lookup table is simple and only once for a fixed scene. The real-time fusion and natural colorization of infrared and visual images are realized by this system. The experimental result shows that the color-transferred images have a natural color perception to human eyes, and can highlight the targets effectively with clear background details. Human observers with this system will be able to interpret the image better and faster, thereby improving situational awareness and reducing target detection time.
Underwater video enhancement using multi-camera super-resolution

NASA Astrophysics Data System (ADS)

Quevedo, E.; Delory, E.; Callicó, G. M.; Tobajas, F.; Sarmiento, R.

2017-12-01

Image spatial resolution is critical in several fields such as medicine, communications or satellite, and underwater applications. While a large variety of techniques for image restoration and enhancement has been proposed in the literature, this paper focuses on a novel Super-Resolution fusion algorithm based on a Multi-Camera environment that permits to enhance the quality of underwater video sequences without significantly increasing computation. In order to compare the quality enhancement, two objective quality metrics have been used: PSNR (Peak Signal-to-Noise Ratio) and the SSIM (Structural SIMilarity) index. Results have shown that the proposed method enhances the objective quality of several underwater sequences, avoiding the appearance of undesirable artifacts, with respect to basic fusion Super-Resolution algorithms.
A color fusion method of infrared and low-light-level images based on visual perception

NASA Astrophysics Data System (ADS)

Han, Jing; Yan, Minmin; Zhang, Yi; Bai, Lianfa

2014-11-01

The color fusion images can be obtained through the fusion of infrared and low-light-level images, which will contain both the information of the two. The fusion images can help observers to understand the multichannel images comprehensively. However, simple fusion may lose the target information due to inconspicuous targets in long-distance infrared and low-light-level images; and if targets extraction is adopted blindly, the perception of the scene information will be affected seriously. To solve this problem, a new fusion method based on visual perception is proposed in this paper. The extraction of the visual targets ("what" information) and parallel processing mechanism are applied in traditional color fusion methods. The infrared and low-light-level color fusion images are achieved based on efficient typical targets learning. Experimental results show the effectiveness of the proposed method. The fusion images achieved by our algorithm can not only improve the detection rate of targets, but also get rich natural information of the scenes.
Feature-Motivated Simplified Adaptive PCNN-Based Medical Image Fusion Algorithm in NSST Domain.

PubMed

Ganasala, Padma; Kumar, Vinod

2016-02-01

Multimodality medical image fusion plays a vital role in diagnosis, treatment planning, and follow-up studies of various diseases. It provides a composite image containing critical information of source images required for better localization and definition of different organs and lesions. In the state-of-the-art image fusion methods based on nonsubsampled shearlet transform (NSST) and pulse-coupled neural network (PCNN), authors have used normalized coefficient value to motivate the PCNN-processing both low-frequency (LF) and high-frequency (HF) sub-bands. This makes the fused image blurred and decreases its contrast. The main objective of this work is to design an image fusion method that gives the fused image with better contrast, more detail information, and suitable for clinical use. We propose a novel image fusion method utilizing feature-motivated adaptive PCNN in NSST domain for fusion of anatomical images. The basic PCNN model is simplified, and adaptive-linking strength is used. Different features are used to motivate the PCNN-processing LF and HF sub-bands. The proposed method is extended for fusion of functional image with an anatomical image in improved nonlinear intensity hue and saturation (INIHS) color model. Extensive fusion experiments have been performed on CT-MRI and SPECT-MRI datasets. Visual and quantitative analysis of experimental results proved that the proposed method provides satisfactory fusion outcome compared to other image fusion methods.
Fusion of digital breast tomosynthesis images via wavelet synthesis for improved lesion conspicuity

NASA Astrophysics Data System (ADS)

Hariharan, Harishwaran; Pomponiu, Victor; Zheng, Bin; Whiting, Bruce; Gur, David

2014-03-01

Full-field digital mammography (FFDM) is the most common screening procedure for detecting early breast cancer. However, due to complications such as overlapping breast tissue in projection images, the efficacy of FFDM reading is reduced. Recent studies have shown that digital breast tomosynthesis (DBT), in combination with FFDM, increases detection sensitivity considerably while decreasing false-positive, recall rates. There is a huge interest in creating diagnostically accurate 2-D interpretations from the DBT slices. Most of the 2-D syntheses rely on visualizing the maximum intensities (brightness) from each slice through different methods. We propose a wavelet based fusion method, where we focus on preserving holistic information from larger structures such as masses while adding high frequency information that is relevant and helpful for diagnosis. This method enables the spatial generation of a 2D image from a series of DBT images, each of which contains both smooth and coarse structures distributed in the wavelet domain. We believe that the wavelet-synthesized images, generated from their DBT image datasets, provide radiologists with improved lesion and micro-calcification conspicuity as compared with FFDM images. The potential impact of this fusion method is (1) Conception of a device-independent, data-driven modality that increases the conspicuity of lesions, thereby facilitating early detection and potentially reducing recall rates; (2) Reduction of the accompanying radiation dose to the patient.
Multiscale Medical Image Fusion in Wavelet Domain

PubMed Central

Khare, Ashish

2013-01-01

Wavelet transforms have emerged as a powerful tool in image fusion. However, the study and analysis of medical image fusion is still a challenging area of research. Therefore, in this paper, we propose a multiscale fusion of multimodal medical images in wavelet domain. Fusion of medical images has been performed at multiple scales varying from minimum to maximum level using maximum selection rule which provides more flexibility and choice to select the relevant fused images. The experimental analysis of the proposed method has been performed with several sets of medical images. Fusion results have been evaluated subjectively and objectively with existing state-of-the-art fusion methods which include several pyramid- and wavelet-transform-based fusion methods and principal component analysis (PCA) fusion method. The comparative analysis of the fusion results has been performed with edge strength (Q), mutual information (MI), entropy (E), standard deviation (SD), blind structural similarity index metric (BSSIM), spatial frequency (SF), and average gradient (AG) metrics. The combined subjective and objective evaluations of the proposed fusion method at multiple scales showed the effectiveness and goodness of the proposed approach. PMID:24453868
Adaptive fusion of infrared and visible images in dynamic scene

NASA Astrophysics Data System (ADS)

Yang, Guang; Yin, Yafeng; Man, Hong; Desai, Sachi

2011-11-01

Multiple modalities sensor fusion has been widely employed in various surveillance and military applications. A variety of image fusion techniques including PCA, wavelet, curvelet and HSV has been proposed in recent years to improve human visual perception for object detection. One of the main challenges for visible and infrared image fusion is to automatically determine an optimal fusion strategy for different input scenes along with an acceptable computational cost. This paper, we propose a fast and adaptive feature selection based image fusion method to obtain high a contrast image from visible and infrared sensors for targets detection. At first, fuzzy c-means clustering is applied on the infrared image to highlight possible hotspot regions, which will be considered as potential targets' locations. After that, the region surrounding the target area is segmented as the background regions. Then image fusion is locally applied on the selected target and background regions by computing different linear combination of color components from registered visible and infrared images. After obtaining different fused images, histogram distributions are computed on these local fusion images as the fusion feature set. The variance ratio which is based on Linear Discriminative Analysis (LDA) measure is employed to sort the feature set and the most discriminative one is selected for the whole image fusion. As the feature selection is performed over time, the process will dynamically determine the most suitable feature for the image fusion in different scenes. Experiment is conducted on the OSU Color-Thermal database, and TNO Human Factor dataset. The fusion results indicate that our proposed method achieved a competitive performance compared with other fusion algorithms at a relatively low computational cost.
Present status and trends of image fusion

NASA Astrophysics Data System (ADS)

Xiang, Dachao; Fu, Sheng; Cai, Yiheng

2009-10-01

Image fusion information extracted from multiple images which is more accurate and reliable than that from just a single image. Since various images contain different information aspects of the measured parts, and comprehensive information can be obtained by integrating them together. Image fusion is a main branch of the application of data fusion technology. At present, it was widely used in computer vision technology, remote sensing, robot vision, medical image processing and military field. This paper mainly presents image fusion's contents, research methods, and the status quo at home and abroad, and analyzes the development trend.
Radiotherapy treatment planning: benefits of CT-MR image registration and fusion in tumor volume delineation.

PubMed

Djan, Igor; Petrović, Borislava; Erak, Marko; Nikolić, Ivan; Lucić, Silvija

2013-08-01

Development of imaging techniques, computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET), made great impact on radiotherapy treatment planning by improving the localization of target volumes. Improved localization allows better local control of tumor volumes, but also minimizes geographical misses. Mutual information is obtained by registration and fusion of images achieved manually or automatically. The aim of this study was to validate the CT-MRI image fusion method and compare delineation obtained by CT versus CT-MRI image fusion. The image fusion software (XIO CMS 4.50.0) was applied to delineate 16 patients. The patients were scanned on CT and MRI in the treatment position within an immobilization device before the initial treatment. The gross tumor volume (GTV) and clinical target volume (CTV) were delineated on CT alone and on CT+MRI images consecutively and image fusion was obtained. Image fusion showed that CTV delineated on a CT image study set is mainly inadequate for treatment planning, in comparison with CTV delineated on CT-MRI fused image study set. Fusion of different modalities enables the most accurate target volume delineation. This study shows that registration and image fusion allows precise target localization in terms of GTV and CTV and local disease control.
[Possibilities of sonographic image fusion: Current developments].

PubMed

Jung, E M; Clevert, D-A

2015-11-01

For diagnostic and interventional procedures ultrasound (US) image fusion can be used as a complementary imaging technique. Image fusion has the advantage of real time imaging and can be combined with other cross-sectional imaging techniques. With the introduction of US contrast agents sonography and image fusion have gained more importance in the detection and characterization of liver lesions. Fusion of US images with computed tomography (CT) or magnetic resonance imaging (MRI) facilitates the diagnostics and postinterventional therapy control. In addition to the primary application of image fusion in the diagnosis and treatment of liver lesions, there are more useful indications for contrast-enhanced US (CEUS) in routine clinical diagnostic procedures, such as intraoperative US (IOUS), vascular imaging and diagnostics of other organs, such as the kidneys and prostate gland.
Airborne Infrared and Visible Image Fusion Combined with Region Segmentation

PubMed Central

Zuo, Yujia; Liu, Jinghong; Bai, Guanbing; Wang, Xuan; Sun, Mingchao

2017-01-01

This paper proposes an infrared (IR) and visible image fusion method introducing region segmentation into the dual-tree complex wavelet transform (DTCWT) region. This method should effectively improve both the target indication and scene spectrum features of fusion images, and the target identification and tracking reliability of fusion system, on an airborne photoelectric platform. The method involves segmenting the region in an IR image by significance, and identifying the target region and the background region; then, fusing the low-frequency components in the DTCWT region according to the region segmentation result. For high-frequency components, the region weights need to be assigned by the information richness of region details to conduct fusion based on both weights and adaptive phases, and then introducing a shrinkage function to suppress noise; Finally, the fused low-frequency and high-frequency components are reconstructed to obtain the fusion image. The experimental results show that the proposed method can fully extract complementary information from the source images to obtain a fusion image with good target indication and rich information on scene details. They also give a fusion result superior to existing popular fusion methods, based on eithers subjective or objective evaluation. With good stability and high fusion accuracy, this method can meet the fusion requirements of IR-visible image fusion systems. PMID:28505137
Airborne Infrared and Visible Image Fusion Combined with Region Segmentation.

PubMed

Zuo, Yujia; Liu, Jinghong; Bai, Guanbing; Wang, Xuan; Sun, Mingchao

2017-05-15

This paper proposes an infrared (IR) and visible image fusion method introducing region segmentation into the dual-tree complex wavelet transform (DTCWT) region. This method should effectively improve both the target indication and scene spectrum features of fusion images, and the target identification and tracking reliability of fusion system, on an airborne photoelectric platform. The method involves segmenting the region in an IR image by significance, and identifying the target region and the background region; then, fusing the low-frequency components in the DTCWT region according to the region segmentation result. For high-frequency components, the region weights need to be assigned by the information richness of region details to conduct fusion based on both weights and adaptive phases, and then introducing a shrinkage function to suppress noise; Finally, the fused low-frequency and high-frequency components are reconstructed to obtain the fusion image. The experimental results show that the proposed method can fully extract complementary information from the source images to obtain a fusion image with good target indication and rich information on scene details. They also give a fusion result superior to existing popular fusion methods, based on eithers subjective or objective evaluation. With good stability and high fusion accuracy, this method can meet the fusion requirements of IR-visible image fusion systems.
Ultrahigh field magnetic resonance and colour Doppler real-time fusion imaging of the orbit--a hybrid tool for assessment of choroidal melanoma.

PubMed

Walter, Uwe; Niendorf, Thoralf; Graessl, Andreas; Rieger, Jan; Krüger, Paul-Christian; Langner, Sönke; Guthoff, Rudolf F; Stachs, Oliver

2014-05-01

A combination of magnetic resonance images with real-time high-resolution ultrasound known as fusion imaging may improve ophthalmologic examination. This study was undertaken to evaluate the feasibility of orbital high-field magnetic resonance and real-time colour Doppler ultrasound image fusion and navigation. This case study, performed between April and June 2013, included one healthy man (age, 47 years) and two patients (one woman, 57 years; one man, 67 years) with choroidal melanomas. All cases underwent 7.0-T magnetic resonance imaging using a custom-made ocular imaging surface coil. The Digital Imaging and Communications in Medicine volume data set was then loaded into the ultrasound system for manual registration of the live ultrasound image and fusion imaging examination. Data registration, matching and then volume navigation were feasible in all cases. Fusion imaging provided real-time imaging capabilities and high tissue contrast of choroidal tumour and optic nerve. It also allowed adding a real-time colour Doppler signal on magnetic resonance images for assessment of vasculature of tumour and retrobulbar structures. The combination of orbital high-field magnetic resonance and colour Doppler ultrasound image fusion and navigation is feasible. Multimodal fusion imaging promises to foster assessment and monitoring of choroidal melanoma and optic nerve disorders. • Orbital magnetic resonance and colour Doppler ultrasound real-time fusion imaging is feasible • Fusion imaging combines the spatial and temporal resolution advantages of each modality • Magnetic resonance and ultrasound fusion imaging improves assessment of choroidal melanoma vascularisation.
[An improved medical image fusion algorithm and quality evaluation].

PubMed

Chen, Meiling; Tao, Ling; Qian, Zhiyu

2009-08-01

Medical image fusion is of very important value for application in medical image analysis and diagnosis. In this paper, the conventional method of wavelet fusion is improved,so a new algorithm of medical image fusion is presented and the high frequency and low frequency coefficients are studied respectively. When high frequency coefficients are chosen, the regional edge intensities of each sub-image are calculated to realize adaptive fusion. The choice of low frequency coefficient is based on the edges of images, so that the fused image preserves all useful information and appears more distinctly. We apply the conventional and the improved fusion algorithms based on wavelet transform to fuse two images of human body and also evaluate the fusion results through a quality evaluation method. Experimental results show that this algorithm can effectively retain the details of information on original images and enhance their edge and texture features. This new algorithm is better than the conventional fusion algorithm based on wavelet transform.
A survey of infrared and visual image fusion methods

NASA Astrophysics Data System (ADS)

Jin, Xin; Jiang, Qian; Yao, Shaowen; Zhou, Dongming; Nie, Rencan; Hai, Jinjin; He, Kangjian

2017-09-01

Infrared (IR) and visual (VI) image fusion is designed to fuse multiple source images into a comprehensive image to boost imaging quality and reduce redundancy information, which is widely used in various imaging equipment to improve the visual ability of human and robot. The accurate, reliable and complementary descriptions of the scene in fused images make these techniques be widely used in various fields. In recent years, a large number of fusion methods for IR and VI images have been proposed due to the ever-growing demands and the progress of image representation methods; however, there has not been published an integrated survey paper about this field in last several years. Therefore, we make a survey to report the algorithmic developments of IR and VI image fusion. In this paper, we first characterize the IR and VI image fusion based applications to represent an overview of the research status. Then we present a synthesize survey of the state of the art. Thirdly, the frequently-used image fusion quality measures are introduced. Fourthly, we perform some experiments of typical methods and make corresponding analysis. At last, we summarize the corresponding tendencies and challenges in IR and VI image fusion. This survey concludes that although various IR and VI image fusion methods have been proposed, there still exist further improvements or potential research directions in different applications of IR and VI image fusion.
Objective quality assessment for multiexposure multifocus image fusion.

PubMed

Hassen, Rania; Wang, Zhou; Salama, Magdy M A

2015-09-01

There has been a growing interest in image fusion technologies, but how to objectively evaluate the quality of fused images has not been fully understood. Here, we propose a method for objective quality assessment of multiexposure multifocus image fusion based on the evaluation of three key factors of fused image quality: 1) contrast preservation; 2) sharpness; and 3) structure preservation. Subjective experiments are conducted to create an image fusion database, based on which, performance evaluation shows that the proposed fusion quality index correlates well with subjective scores, and gives a significant improvement over the existing fusion quality measures.
An extended model of vesicle fusion at the plasma membrane to estimate protein lateral diffusion from TIRF microscopy images.

PubMed

Basset, Antoine; Bouthemy, Patrick; Boulanger, Jérôme; Waharte, François; Salamero, Jean; Kervrann, Charles

2017-07-24

Characterizing membrane dynamics is a key issue to understand cell exchanges with the extra-cellular medium. Total internal reflection fluorescence microscopy (TIRFM) is well suited to focus on the late steps of exocytosis at the plasma membrane. However, it is still a challenging task to quantify (lateral) diffusion and estimate local dynamics of proteins. A new model was introduced to represent the behavior of cargo transmembrane proteins during the vesicle fusion to the plasma membrane at the end of the exocytosis process. Two biophysical parameters, the diffusion coefficient and the release rate parameter, are automatically estimated from TIRFM image sequences, to account for both the lateral diffusion of molecules at the membrane and the continuous release of the proteins from the vesicle to the plasma membrane. Quantitative evaluation on 300 realistic computer-generated image sequences demonstrated the efficiency and accuracy of the method. The application of our method on 16 real TIRFM image sequences additionally revealed differences in the dynamic behavior of Transferrin Receptor (TfR) and Langerin proteins. An automated method has been designed to simultaneously estimate the diffusion coefficient and the release rate for each individual vesicle fusion event at the plasma membrane in TIRFM image sequences. It can be exploited for further deciphering cell membrane dynamics.

Characterization of the axial plasma shock in a table top plasma focus after the pinch and its possible application to testing materials for fusion reactors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Soto, Leopoldo, E-mail: lsoto@cchen.cl; Pavez, Cristian; Moreno, José

2014-12-15

The characterization of plasma bursts produced after the pinch phase in a plasma focus of hundreds of joules, using pulsed optical refractive techniques, is presented. A pulsed Nd-YAG laser at 532 nm and 8 ns FWHM pulse duration was used to obtain Schlieren images at different times of the plasma dynamics. The energy, interaction time with a target, and power flux of the plasma burst were assessed, providing useful information for the application of plasma focus devices for studying the effects of fusion-relevant pulses on material targets. In particular, it was found that damage factors on targets of the order of 10{supmore » 4} (W/cm{sup 2})s{sup 1/2} can be obtained with a small plasma focus operating at hundred joules.« less
A New Approach to Image Fusion Based on Cokriging

NASA Technical Reports Server (NTRS)

Memarsadeghi, Nargess; LeMoigne, Jacqueline; Mount, David M.; Morisette, Jeffrey T.

2005-01-01

We consider the image fusion problem involving remotely sensed data. We introduce cokriging as a method to perform fusion. We investigate the advantages of fusing Hyperion with ALI. The evaluation is performed by comparing the classification of the fused data with that of input images and by calculating well-chosen quantitative fusion quality metrics. We consider the Invasive Species Forecasting System (ISFS) project as our fusion application. The fusion of ALI with Hyperion data is studies using PCA and wavelet-based fusion. We then propose utilizing a geostatistical based interpolation method called cokriging as a new approach for image fusion.
Magnetic resonance imaging-transectal ultrasound image-fusion biopsies accurately characterize the index tumor: correlation with step-sectioned radical prostatectomy specimens in 135 patients.

PubMed

Baco, Eduard; Ukimura, Osamu; Rud, Erik; Vlatkovic, Ljiljana; Svindland, Aud; Aron, Manju; Palmer, Suzanne; Matsugasumi, Toru; Marien, Arnaud; Bernhard, Jean-Christophe; Rewcastle, John C; Eggesbø, Heidi B; Gill, Inderbir S

2015-04-01

Prostate biopsies targeted by elastic fusion of magnetic resonance (MR) and three-dimensional (3D) transrectal ultrasound (TRUS) images may allow accurate identification of the index tumor (IT), defined as the lesion with the highest Gleason score or the largest volume or extraprostatic extension. To determine the accuracy of MR-TRUS image-fusion biopsy in characterizing ITs, as confirmed by correlation with step-sectioned radical prostatectomy (RP) specimens. Retrospective analysis of 135 consecutive patients who sequentially underwent pre-biopsy MR, MR-TRUS image-fusion biopsy, and robotic RP at two centers between January 2010 and September 2013. Image-guided biopsies of MR-suspected IT lesions were performed with tracking via real-time 3D TRUS. The largest geographically distinct cancer focus (IT lesion) was independently registered on step-sectioned RP specimens. A validated schema comprising 27 regions of interest was used to identify the IT center location on MR images and in RP specimens, as well as the location of the midpoint of the biopsy trajectory, and variables were correlated. The concordance between IT location on biopsy and RP specimens was 95% (128/135). The coefficient for correlation between IT volume on MRI and histology was r=0.663 (p<0.001). The maximum cancer core length on biopsy was weakly correlated with RP tumor volume (r=0.466, p<0.001). The concordance of primary Gleason pattern between targeted biopsy and RP specimens was 90% (115/128; κ=0.76). The study limitations include retrospective evaluation of a selected patient population, which limits the generalizability of the results. Use of MR-TRUS image fusion to guide prostate biopsies reliably identified the location and primary Gleason pattern of the IT lesion in >90% of patients, but showed limited ability to predict cancer volume, as confirmed by step-sectioned RP specimens. Biopsies targeted using magnetic resonance images combined with real-time three-dimensional transrectal ultrasound allowed us to reliably identify the spatial location of the most important tumor in prostate cancer and characterize its aggressiveness. Copyright © 2014 European Association of Urology. Published by Elsevier B.V. All rights reserved.
Gradient-based multiresolution image fusion.

PubMed

Petrović, Valdimir S; Xydeas, Costas S

2004-02-01

A novel approach to multiresolution signal-level image fusion is presented for accurately transferring visual information from any number of input image signals, into a single fused image without loss of information or the introduction of distortion. The proposed system uses a "fuse-then-decompose" technique realized through a novel, fusion/decomposition system architecture. In particular, information fusion is performed on a multiresolution gradient map representation domain of image signal information. At each resolution, input images are represented as gradient maps and combined to produce new, fused gradient maps. Fused gradient map signals are processed, using gradient filters derived from high-pass quadrature mirror filters to yield a fused multiresolution pyramid representation. The fused output image is obtained by applying, on the fused pyramid, a reconstruction process that is analogous to that of conventional discrete wavelet transform. This new gradient fusion significantly reduces the amount of distortion artefacts and the loss of contrast information usually observed in fused images obtained from conventional multiresolution fusion schemes. This is because fusion in the gradient map domain significantly improves the reliability of the feature selection and information fusion processes. Fusion performance is evaluated through informal visual inspection and subjective psychometric preference tests, as well as objective fusion performance measurements. Results clearly demonstrate the superiority of this new approach when compared to conventional fusion systems.
Study on polarization image methods in turbid medium

NASA Astrophysics Data System (ADS)

Fu, Qiang; Mo, Chunhe; Liu, Boyu; Duan, Jin; Zhang, Su; Zhu, Yong

2014-11-01

Polarization imaging detection technology in addition to the traditional imaging information, also can get polarization multi-dimensional information, thus improve the probability of target detection and recognition.Image fusion in turbid medium target polarization image research, is helpful to obtain high quality images. Based on visible light wavelength of light wavelength of laser polarization imaging, through the rotation Angle of polaroid get corresponding linear polarized light intensity, respectively to obtain the concentration range from 5% to 10% of turbid medium target stocks of polarization parameters, introduces the processing of image fusion technology, main research on access to the polarization of the image by using different polarization image fusion methods for image processing, discusses several kinds of turbid medium has superior performance of polarization image fusion method, and gives the treatment effect and analysis of data tables. Then use pixel level, feature level and decision level fusion algorithm on three levels of information fusion, DOLP polarization image fusion, the results show that: with the increase of the polarization Angle, polarization image will be more and more fuzzy, quality worse and worse. Than a single fused image contrast of the image be improved obviously, the finally analysis on reasons of the increase the image contrast and polarized light.
Fusion of multi-spectral and panchromatic images based on 2D-PWVD and SSIM

NASA Astrophysics Data System (ADS)

Tan, Dongjie; Liu, Yi; Hou, Ruonan; Xue, Bindang

2016-03-01

A combined method using 2D pseudo Wigner-Ville distribution (2D-PWVD) and structural similarity(SSIM) index is proposed for fusion of low resolution multi-spectral (MS) image and high resolution panchromatic (PAN) image. First, the intensity component of multi-spectral image is extracted with generalized IHS transform. Then, the spectrum diagrams of the intensity components of multi-spectral image and panchromatic image are obtained with 2D-PWVD. Different fusion rules are designed for different frequency information of the spectrum diagrams. SSIM index is used to evaluate the high frequency information of the spectrum diagrams for assigning the weights in the fusion processing adaptively. After the new spectrum diagram is achieved according to the fusion rule, the final fusion image can be obtained by inverse 2D-PWVD and inverse GIHS transform. Experimental results show that, the proposed method can obtain high quality fusion images.
Correlative Microscopy Combining Secondary Ion Mass Spectrometry and Electron Microscopy: Comparison of Intensity-Hue-Saturation and Laplacian Pyramid Methods for Image Fusion.

PubMed

Vollnhals, Florian; Audinot, Jean-Nicolas; Wirtz, Tom; Mercier-Bonin, Muriel; Fourquaux, Isabelle; Schroeppel, Birgit; Kraushaar, Udo; Lev-Ram, Varda; Ellisman, Mark H; Eswara, Santhana

2017-10-17

Correlative microscopy combining various imaging modalities offers powerful insights into obtaining a comprehensive understanding of physical, chemical, and biological phenomena. In this article, we investigate two approaches for image fusion in the context of combining the inherently lower-resolution chemical images obtained using secondary ion mass spectrometry (SIMS) with the high-resolution ultrastructural images obtained using electron microscopy (EM). We evaluate the image fusion methods with three different case studies selected to broadly represent the typical samples in life science research: (i) histology (unlabeled tissue), (ii) nanotoxicology, and (iii) metabolism (isotopically labeled tissue). We show that the intensity-hue-saturation fusion method often applied for EM-sharpening can result in serious image artifacts, especially in cases where different contrast mechanisms interplay. Here, we introduce and demonstrate Laplacian pyramid fusion as a powerful and more robust alternative method for image fusion. Both physical and technical aspects of correlative image overlay and image fusion specific to SIMS-based correlative microscopy are discussed in detail alongside the advantages, limitations, and the potential artifacts. Quantitative metrics to evaluate the results of image fusion are also discussed.
Comparative evaluation of three-dimensional Gd-EOB-DTPA-enhanced MR fusion imaging with CT fusion imaging in the assessment of treatment effect of radiofrequency ablation of hepatocellular carcinoma.

PubMed

Makino, Yuki; Imai, Yasuharu; Igura, Takumi; Hori, Masatoshi; Fukuda, Kazuto; Sawai, Yoshiyuki; Kogita, Sachiyo; Fujita, Norihiko; Takehara, Tetsuo; Murakami, Takamichi

2015-01-01

To assess the feasibility of fusion of pre- and post-ablation gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid-enhanced magnetic resonance imaging (Gd-EOB-DTPA-MRI) to evaluate the effects of radiofrequency ablation (RFA) of hepatocellular carcinoma (HCC), compared with similarly fused CT images This retrospective study included 67 patients with 92 HCCs treated with RFA. Fusion images of pre- and post-RFA dynamic CT, and pre- and post-RFA Gd-EOB-DTPA-MRI were created, using a rigid registration method. The minimal ablative margin measured on fusion imaging was categorized into three groups: (1) tumor protruding outside the ablation zone boundary, (2) ablative margin 0-<5.0 mm beyond the tumor boundary, and (3) ablative margin ≥5.0 mm beyond the tumor boundary. The categorization of minimal ablative margins was compared between CT and MR fusion images. In 57 (62.0%) HCCs, treatment evaluation was possible both on CT and MR fusion images, and the overall agreement between them for the categorization of minimal ablative margin was good (κ coefficient = 0.676, P < 0.01). MR fusion imaging enabled treatment evaluation in a significantly larger number of HCCs than CT fusion imaging (86/92 [93.5%] vs. 62/92 [67.4%], P < 0.05). Fusion of pre- and post-ablation Gd-EOB-DTPA-MRI is feasible for treatment evaluation after RFA. It may enable accurate treatment evaluation in cases where CT fusion imaging is not helpful.
Autofocus method for automated microscopy using embedded GPUs.

PubMed

Castillo-Secilla, J M; Saval-Calvo, M; Medina-Valdès, L; Cuenca-Asensi, S; Martínez-Álvarez, A; Sánchez, C; Cristóbal, G

2017-03-01

In this paper we present a method for autofocusing images of sputum smears taken from a microscope which combines the finding of the optimal focus distance with an algorithm for extending the depth of field (EDoF). Our multifocus fusion method produces an unique image where all the relevant objects of the analyzed scene are well focused, independently to their distance to the sensor. This process is computationally expensive which makes unfeasible its automation using traditional embedded processors. For this purpose a low-cost optimized implementation is proposed using limited resources embedded GPU integrated on cutting-edge NVIDIA system on chip. The extensive tests performed on different sputum smear image sets show the real-time capabilities of our implementation maintaining the quality of the output image.
[Research progress of multi-model medical image fusion and recognition].

PubMed

Zhou, Tao; Lu, Huiling; Chen, Zhiqiang; Ma, Jingxian

2013-10-01

Medical image fusion and recognition has a wide range of applications, such as focal location, cancer staging and treatment effect assessment. Multi-model medical image fusion and recognition are analyzed and summarized in this paper. Firstly, the question of multi-model medical image fusion and recognition is discussed, and its advantage and key steps are discussed. Secondly, three fusion strategies are reviewed from the point of algorithm, and four fusion recognition structures are discussed. Thirdly, difficulties, challenges and possible future research direction are discussed.
Super-resolution fusion of complementary panoramic images based on cross-selection kernel regression interpolation.

PubMed

Chen, Lidong; Basu, Anup; Zhang, Maojun; Wang, Wei; Liu, Yu

2014-03-20

A complementary catadioptric imaging technique was proposed to solve the problem of low and nonuniform resolution in omnidirectional imaging. To enhance this research, our paper focuses on how to generate a high-resolution panoramic image from the captured omnidirectional image. To avoid the interference between the inner and outer images while fusing the two complementary views, a cross-selection kernel regression method is proposed. First, in view of the complementarity of sampling resolution in the tangential and radial directions between the inner and the outer images, respectively, the horizontal gradients in the expected panoramic image are estimated based on the scattered neighboring pixels mapped from the outer, while the vertical gradients are estimated using the inner image. Then, the size and shape of the regression kernel are adaptively steered based on the local gradients. Furthermore, the neighboring pixels in the next interpolation step of kernel regression are also selected based on the comparison between the horizontal and vertical gradients. In simulation and real-image experiments, the proposed method outperforms existing kernel regression methods and our previous wavelet-based fusion method in terms of both visual quality and objective evaluation.
Data fusion strategies for hazard detection and safe site selection for planetary and small body landings

NASA Astrophysics Data System (ADS)

Câmara, F.; Oliveira, J.; Hormigo, T.; Araújo, J.; Ribeiro, R.; Falcão, A.; Gomes, M.; Dubois-Matra, O.; Vijendran, S.

2015-06-01

This paper discusses the design and evaluation of data fusion strategies to perform tiered fusion of several heterogeneous sensors and a priori data. The aim is to increase robustness and performance of hazard detection and avoidance systems, while enabling safe planetary and small body landings anytime, anywhere. The focus is on Mars and asteroid landing mission scenarios and three distinct data fusion algorithms are introduced and compared. The first algorithm consists of a hybrid camera-LIDAR hazard detection and avoidance system, the H2DAS, in which data fusion is performed at both sensor-level data (reconstruction of the point cloud obtained with a scanning LIDAR using the navigation motion states and correcting the image for motion compensation using IMU data), feature-level data (concatenation of multiple digital elevation maps, obtained from consecutive LIDAR images, to achieve higher accuracy and resolution maps while enabling relative positioning) as well as decision-level data (fusing hazard maps from multiple sensors onto a single image space, with a single grid orientation and spacing). The second method presented is a hybrid reasoning fusion, the HRF, in which innovative algorithms replace the decision-level functions of the previous method, by combining three different reasoning engines—a fuzzy reasoning engine, a probabilistic reasoning engine and an evidential reasoning engine—to produce safety maps. Finally, the third method presented is called Intelligent Planetary Site Selection, the IPSIS, an innovative multi-criteria, dynamic decision-level data fusion algorithm that takes into account historical information for the selection of landing sites and a piloting function with a non-exhaustive landing site search capability, i.e., capable of finding local optima by searching a reduced set of global maps. All the discussed data fusion strategies and algorithms have been integrated, verified and validated in a closed-loop simulation environment. Monte Carlo simulation campaigns were performed for the algorithms performance assessment and benchmarking. The simulations results comprise the landing phases of Mars and Phobos landing mission scenarios.
X-ray imaging crystal spectrometer for extended X-ray sources

DOEpatents

Bitter, Manfred L.; Fraenkel, Ben; Gorman, James L.; Hill, Kenneth W.; Roquemore, A. Lane; Stodiek, Wolfgang; von Goeler, Schweickhard E.

2001-01-01

Spherically or toroidally curved, double focusing crystals are used in a spectrometer for X-ray diagnostics of an extended X-ray source such as a hot plasma produced in a tokomak fusion experiment to provide spatially and temporally resolved data on plasma parameters using the imaging properties for Bragg angles near 45. For a Bragg angle of 45.degree., the spherical crystal focuses a bundle of near parallel X-rays (the cross section of which is determined by the cross section of the crystal) from the plasma to a point on a detector, with parallel rays inclined to the main plain of diffraction focused to different points on the detector. Thus, it is possible to radially image the plasma X-ray emission in different wavelengths simultaneously with a single crystal.
Evaluation of Effective Parameters on Quality of Magnetic Resonance Imaging-computed Tomography Image Fusion in Head and Neck Tumors for Application in Treatment Planning.

PubMed

Shirvani, Atefeh; Jabbari, Keyvan; Amouheidari, Alireza

2017-01-01

In radiation therapy, computed tomography (CT) simulation is used for treatment planning to define the location of tumor. Magnetic resonance imaging (MRI)-CT image fusion leads to more efficient tumor contouring. This work tried to identify the practical issues for the combination of CT and MRI images in real clinical cases. The effect of various factors is evaluated on image fusion quality. In this study, the data of thirty patients with brain tumors were used for image fusion. The effect of several parameters on possibility and quality of image fusion was evaluated. These parameters include angles of the patient's head on the bed, slices thickness, slice gap, and height of the patient's head. According to the results, the first dominating factor on quality of image fusion was the difference slice gap between CT and MRI images (cor = 0.86, P < 0.005) and second factor was the angle between CT and MRI slice in the sagittal plane (cor = 0.75, P < 0.005). In 20% of patients, this angle was more than 28° and image fusion was not efficient. In 17% of patients, difference slice gap in CT and MRI was >4 cm and image fusion quality was <25%. The most important problem in image fusion is that MRI images are taken without regard to their use in treatment planning. In general, parameters related to the patient position during MRI imaging should be chosen to be consistent with CT images of the patient in terms of location and angle.
Automatic image fusion of real-time ultrasound with computed tomography images: a prospective comparison between two auto-registration methods.

PubMed

Cha, Dong Ik; Lee, Min Woo; Kim, Ah Yeong; Kang, Tae Wook; Oh, Young-Taek; Jeong, Ja-Yeon; Chang, Jung-Woo; Ryu, Jiwon; Lee, Kyong Joon; Kim, Jaeil; Bang, Won-Chul; Shin, Dong Kuk; Choi, Sung Jin; Koh, Dalkwon; Seo, Bong Koo; Kim, Kyunga

2017-11-01

Background A major drawback of conventional manual image fusion is that the process may be complex, especially for less-experienced operators. Recently, two automatic image fusion techniques called Positioning and Sweeping auto-registration have been developed. Purpose To compare the accuracy and required time for image fusion of real-time ultrasonography (US) and computed tomography (CT) images between Positioning and Sweeping auto-registration. Material and Methods Eighteen consecutive patients referred for planning US for radiofrequency ablation or biopsy for focal hepatic lesions were enrolled. Image fusion using both auto-registration methods was performed for each patient. Registration error, time required for image fusion, and number of point locks used were compared using the Wilcoxon signed rank test. Results Image fusion was successful in all patients. Positioning auto-registration was significantly faster than Sweeping auto-registration for both initial (median, 11 s [range, 3-16 s] vs. 32 s [range, 21-38 s]; P < 0.001] and complete (median, 34.0 s [range, 26-66 s] vs. 47.5 s [range, 32-90]; P = 0.001] image fusion. Registration error of Positioning auto-registration was significantly higher for initial image fusion (median, 38.8 mm [range, 16.0-84.6 mm] vs. 18.2 mm [6.7-73.4 mm]; P = 0.029), but not for complete image fusion (median, 4.75 mm [range, 1.7-9.9 mm] vs. 5.8 mm [range, 2.0-13.0 mm]; P = 0.338]. Number of point locks required to refine the initially fused images was significantly higher with Positioning auto-registration (median, 2 [range, 2-3] vs. 1 [range, 1-2]; P = 0.012]. Conclusion Positioning auto-registration offers faster image fusion between real-time US and pre-procedural CT images than Sweeping auto-registration. The final registration error is similar between the two methods.
Accuracy of volume measurement using 3D ultrasound and development of CT-3D US image fusion algorithm for prostate cancer radiotherapy.

PubMed

Baek, Jihye; Huh, Jangyoung; Kim, Myungsoo; Hyun An, So; Oh, Yoonjin; Kim, DongYoung; Chung, Kwangzoo; Cho, Sungho; Lee, Rena

2013-02-01

To evaluate the accuracy of measuring volumes using three-dimensional ultrasound (3D US), and to verify the feasibility of the replacement of CT-MR fusion images with CT-3D US in radiotherapy treatment planning. Phantoms, consisting of water, contrast agent, and agarose, were manufactured. The volume was measured using 3D US, CT, and MR devices. A CT-3D US and MR-3D US image fusion software was developed using the Insight Toolkit library in order to acquire three-dimensional fusion images. The quality of the image fusion was evaluated using metric value and fusion images. Volume measurement, using 3D US, shows a 2.8 ± 1.5% error, 4.4 ± 3.0% error for CT, and 3.1 ± 2.0% error for MR. The results imply that volume measurement using the 3D US devices has a similar accuracy level to that of CT and MR. Three-dimensional image fusion of CT-3D US and MR-3D US was successfully performed using phantom images. Moreover, MR-3D US image fusion was performed using human bladder images. 3D US could be used in the volume measurement of human bladders and prostates. CT-3D US image fusion could be used in monitoring the target position in each fraction of external beam radiation therapy. Moreover, the feasibility of replacing the CT-MR image fusion to the CT-3D US in radiotherapy treatment planning was verified.
Multispectral image fusion for target detection

NASA Astrophysics Data System (ADS)

Leviner, Marom; Maltz, Masha

2009-09-01

Various different methods to perform multi-spectral image fusion have been suggested, mostly on the pixel level. However, the jury is still out on the benefits of a fused image compared to its source images. We present here a new multi-spectral image fusion method, multi-spectral segmentation fusion (MSSF), which uses a feature level processing paradigm. To test our method, we compared human observer performance in an experiment using MSSF against two established methods: Averaging and Principle Components Analysis (PCA), and against its two source bands, visible and infrared. The task that we studied was: target detection in the cluttered environment. MSSF proved superior to the other fusion methods. Based on these findings, current speculation about the circumstances in which multi-spectral image fusion in general and specific fusion methods in particular would be superior to using the original image sources can be further addressed.
Infrared and visible image fusion with the target marked based on multi-resolution visual attention mechanisms

NASA Astrophysics Data System (ADS)

Huang, Yadong; Gao, Kun; Gong, Chen; Han, Lu; Guo, Yue

2016-03-01

During traditional multi-resolution infrared and visible image fusion processing, the low contrast ratio target may be weakened and become inconspicuous because of the opposite DN values in the source images. So a novel target pseudo-color enhanced image fusion algorithm based on the modified attention model and fast discrete curvelet transformation is proposed. The interesting target regions are extracted from source images by introducing the motion features gained from the modified attention model, and source images are performed the gray fusion via the rules based on physical characteristics of sensors in curvelet domain. The final fusion image is obtained by mapping extracted targets into the gray result with the proper pseudo-color instead. The experiments show that the algorithm can highlight dim targets effectively and improve SNR of fusion image.
Parametric PET/MR Fusion Imaging to Differentiate Aggressive from Indolent Primary Prostate Cancer with Application for Image-Guided Prostate Cancer Biopsies

DTIC Science & Technology

2013-10-01

AD_________________ Award Number: W81XWH-12-1-0597 TITLE: Parametric PET /MR Fusion Imaging to...Parametric PET /MR Fusion Imaging to Differentiate Aggressive from Indolent Primary Prostate Cancer with Application for Image-Guided Prostate Cancer Biopsies...The study investigates whether fusion PET /MRI imaging with 18F-choline PET /CT and diffusion-weighted MRI can be successfully applied to target prostate
Evaluation of Effective Parameters on Quality of Magnetic Resonance Imaging-computed Tomography Image Fusion in Head and Neck Tumors for Application in Treatment Planning

PubMed Central

Shirvani, Atefeh; Jabbari, Keyvan; Amouheidari, Alireza

2017-01-01

Background: In radiation therapy, computed tomography (CT) simulation is used for treatment planning to define the location of tumor. Magnetic resonance imaging (MRI)-CT image fusion leads to more efficient tumor contouring. This work tried to identify the practical issues for the combination of CT and MRI images in real clinical cases. The effect of various factors is evaluated on image fusion quality. Materials and Methods: In this study, the data of thirty patients with brain tumors were used for image fusion. The effect of several parameters on possibility and quality of image fusion was evaluated. These parameters include angles of the patient's head on the bed, slices thickness, slice gap, and height of the patient's head. Results: According to the results, the first dominating factor on quality of image fusion was the difference slice gap between CT and MRI images (cor = 0.86, P < 0.005) and second factor was the angle between CT and MRI slice in the sagittal plane (cor = 0.75, P < 0.005). In 20% of patients, this angle was more than 28° and image fusion was not efficient. In 17% of patients, difference slice gap in CT and MRI was >4 cm and image fusion quality was <25%. Conclusion: The most important problem in image fusion is that MRI images are taken without regard to their use in treatment planning. In general, parameters related to the patient position during MRI imaging should be chosen to be consistent with CT images of the patient in terms of location and angle. PMID:29387672

Potential hazards of viewing 3-D stereoscopic television, cinema and computer games: a review.

PubMed

Howarth, Peter A

2011-03-01

The visual stimulus provided by a 3-D stereoscopic display differs from that of the real world because the image provided to each eye is produced on a flat surface. The distance from the screen to the eye remains fixed, providing a single focal distance, but the introduction of disparity between the images allows objects to be located geometrically in front of, or behind, the screen. Unlike in the real world, the stimulus to accommodation and the stimulus to convergence do not match. Although this mismatch is used positively in some forms of Orthoptic treatment, a number of authors have suggested that it could negatively lead to the development of asthenopic symptoms. From knowledge of the zone of clear, comfortable, single binocular vision one can predict that, for people with normal binocular vision, adverse symptoms will not be present if the discrepancy is small, but are likely if it is large, and that what constitutes 'large' and 'small' are idiosyncratic to the individual. The accommodation-convergence mismatch is not, however, the only difference between the natural and the artificial stimuli. In the former case, an object located in front of, or behind, a fixated object will not only be perceived as double if the images fall outside Panum's fusional areas, but it will also be defocused and blurred. In the latter case, however, it is usual for the producers of cinema, TV or computer game content to provide an image that is in focus over the whole of the display, and as a consequence diplopic images will be sharply in focus. The size of Panum's fusional area is spatial frequency-dependent, and because of this the high spatial frequencies present in the diplopic 3-D image will provide a different stimulus to the fusion system from that found naturally. © 2011 The College of Optometrists.
Infrared and visible image fusion with spectral graph wavelet transform.

PubMed

Yan, Xiang; Qin, Hanlin; Li, Jia; Zhou, Huixin; Zong, Jing-guo

2015-09-01

Infrared and visible image fusion technique is a popular topic in image analysis because it can integrate complementary information and obtain reliable and accurate description of scenes. Multiscale transform theory as a signal representation method is widely used in image fusion. In this paper, a novel infrared and visible image fusion method is proposed based on spectral graph wavelet transform (SGWT) and bilateral filter. The main novelty of this study is that SGWT is used for image fusion. On the one hand, source images are decomposed by SGWT in its transform domain. The proposed approach not only effectively preserves the details of different source images, but also excellently represents the irregular areas of the source images. On the other hand, a novel weighted average method based on bilateral filter is proposed to fuse low- and high-frequency subbands by taking advantage of spatial consistency of natural images. Experimental results demonstrate that the proposed method outperforms seven recently proposed image fusion methods in terms of both visual effect and objective evaluation metrics.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Khan, S. F.; Izumi, N.; Glenn, S.

At the National Ignition Facility, the symmetry of the hot spot of imploding capsules is diagnosed by imaging the emitted x-rays using gated cameras and image plates. The symmetry of an implosion is an important factor in the yield generated from the resulting fusion process. The x-ray images are analyzed by decomposing the image intensity contours into Fourier and Legendre modes. This paper focuses on the additional protocols for the time-integrated shape analysis from image plates. Here, for implosions with temperatures above ~4keV, the hard x-ray background can be utilized to infer the temperature of the hot spot.
Range and Panoramic Image Fusion Into a Textured Range Image for Culture Heritage Documentation

NASA Astrophysics Data System (ADS)

Bila, Z.; Reznicek, J.; Pavelka, K.

2013-07-01

This paper deals with a fusion of range and panoramic images, where the range image is acquired by a 3D laser scanner and the panoramic image is acquired with a digital still camera mounted on a panoramic head and tripod. The fused resulting dataset, called "textured range image", provides more reliable information about the investigated object for conservators and historians, than using both datasets separately. A simple example of fusion of a range and panoramic images, both obtained in St. Francis Xavier Church in town Opařany, is given here. Firstly, we describe the process of data acquisition, then the processing of both datasets into a proper format for following fusion and the process of fusion. The process of fusion can be divided into a two main parts: transformation and remapping. In the first, transformation, part, both images are related by matching similar features detected on both images with a proper detector, which results in transformation matrix enabling transformation of the range image onto a panoramic image. Then, the range data are remapped from the range image space into a panoramic image space and stored as an additional "range" channel. The process of image fusion is validated by comparing similar features extracted on both datasets.
Investigations of image fusion

NASA Astrophysics Data System (ADS)

Zhang, Zhong

1999-12-01

The objective of image fusion is to combine information from multiple images of the same scene. The result of image fusion is a single image which is more suitable for the purpose of human visual perception or further image processing tasks. In this thesis, a region-based fusion algorithm using the wavelet transform is proposed. The identification of important features in each image, such as edges and regions of interest, are used to guide the fusion process. The idea of multiscale grouping is also introduced and a generic image fusion framework based on multiscale decomposition is studied. The framework includes all of the existing multiscale-decomposition- based fusion approaches we found in the literature which did not assume a statistical model for the source images. Comparisons indicate that our framework includes some new approaches which outperform the existing approaches for the cases we consider. Registration must precede our fusion algorithms. So we proposed a hybrid scheme which uses both feature-based and intensity-based methods. The idea of robust estimation of optical flow from time- varying images is employed with a coarse-to-fine multi- resolution approach and feature-based registration to overcome some of the limitations of the intensity-based schemes. Experiments show that this approach is robust and efficient. Assessing image fusion performance in a real application is a complicated issue. In this dissertation, a mixture probability density function model is used in conjunction with the Expectation- Maximization algorithm to model histograms of edge intensity. Some new techniques are proposed for estimating the quality of a noisy image of a natural scene. Such quality measures can be used to guide the fusion. Finally, we study fusion of images obtained from several copies of a new type of camera developed for video surveillance. Our techniques increase the capability and reliability of the surveillance system and provide an easy way to obtain 3-D information of objects in the space monitored by the system.
Sensor fusion for synthetic vision

NASA Technical Reports Server (NTRS)

Pavel, M.; Larimer, J.; Ahumada, A.

1991-01-01

Display methodologies are explored for fusing images gathered by millimeter wave sensors with images rendered from an on-board terrain data base to facilitate visually guided flight and ground operations in low visibility conditions. An approach to fusion based on multiresolution image representation and processing is described which facilitates fusion of images differing in resolution within and between images. To investigate possible fusion methods, a workstation-based simulation environment is being developed.
Ultrasound fusion image error correction using subject-specific liver motion model and automatic image registration.

PubMed

Yang, Minglei; Ding, Hui; Zhu, Lei; Wang, Guangzhi

2016-12-01

Ultrasound fusion imaging is an emerging tool and benefits a variety of clinical applications, such as image-guided diagnosis and treatment of hepatocellular carcinoma and unresectable liver metastases. However, respiratory liver motion-induced misalignment of multimodal images (i.e., fusion error) compromises the effectiveness and practicability of this method. The purpose of this paper is to develop a subject-specific liver motion model and automatic registration-based method to correct the fusion error. An online-built subject-specific motion model and automatic image registration method for 2D ultrasound-3D magnetic resonance (MR) images were combined to compensate for the respiratory liver motion. The key steps included: 1) Build a subject-specific liver motion model for current subject online and perform the initial registration of pre-acquired 3D MR and intra-operative ultrasound images; 2) During fusion imaging, compensate for liver motion first using the motion model, and then using an automatic registration method to further correct the respiratory fusion error. Evaluation experiments were conducted on liver phantom and five subjects. In the phantom study, the fusion error (superior-inferior axis) was reduced from 13.90±2.38mm to 4.26±0.78mm by using the motion model only. The fusion error further decreased to 0.63±0.53mm by using the registration method. The registration method also decreased the rotation error from 7.06±0.21° to 1.18±0.66°. In the clinical study, the fusion error was reduced from 12.90±9.58mm to 6.12±2.90mm by using the motion model alone. Moreover, the fusion error decreased to 1.96±0.33mm by using the registration method. The proposed method can effectively correct the respiration-induced fusion error to improve the fusion image quality. This method can also reduce the error correction dependency on the initial registration of ultrasound and MR images. Overall, the proposed method can improve the clinical practicability of ultrasound fusion imaging. Copyright © 2016 Elsevier Ltd. All rights reserved.
Multiscale image fusion using the undecimated wavelet transform with spectral factorization and nonorthogonal filter banks.

PubMed

Ellmauthaler, Andreas; Pagliari, Carla L; da Silva, Eduardo A B

2013-03-01

Multiscale transforms are among the most popular techniques in the field of pixel-level image fusion. However, the fusion performance of these methods often deteriorates for images derived from different sensor modalities. In this paper, we demonstrate that for such images, results can be improved using a novel undecimated wavelet transform (UWT)-based fusion scheme, which splits the image decomposition process into two successive filtering operations using spectral factorization of the analysis filters. The actual fusion takes place after convolution with the first filter pair. Its significantly smaller support size leads to the minimization of the unwanted spreading of coefficient values around overlapping image singularities. This usually complicates the feature selection process and may lead to the introduction of reconstruction errors in the fused image. Moreover, we will show that the nonsubsampled nature of the UWT allows the design of nonorthogonal filter banks, which are more robust to artifacts introduced during fusion, additionally improving the obtained results. The combination of these techniques leads to a fusion framework, which provides clear advantages over traditional multiscale fusion approaches, independent of the underlying fusion rule, and reduces unwanted side effects such as ringing artifacts in the fused reconstruction.
a Comparative Analysis of Spatiotemporal Data Fusion Models for Landsat and Modis Data

NASA Astrophysics Data System (ADS)

Hazaymeh, K.; Almagbile, A.

2018-04-01

In this study, three documented spatiotemporal data fusion models were applied to Landsat-7 and MODIS surface reflectance, and NDVI. The algorithms included the spatial and temporal adaptive reflectance fusion model (STARFM), sparse representation based on a spatiotemporal reflectance fusion model (SPSTFM), and spatiotemporal image-fusion model (STI-FM). The objectives of this study were to (i) compare the performance of these three fusion models using a one Landsat-MODIS spectral reflectance image pairs using time-series datasets from the Coleambally irrigation area in Australia, and (ii) quantitatively evaluate the accuracy of the synthetic images generated from each fusion model using statistical measurements. Results showed that the three fusion models predicted the synthetic Landsat-7 image with adequate agreements. The STI-FM produced more accurate reconstructions of both Landsat-7 spectral bands and NDVI. Furthermore, it produced surface reflectance images having the highest correlation with the actual Landsat-7 images. This study indicated that STI-FM would be more suitable for spatiotemporal data fusion applications such as vegetation monitoring, drought monitoring, and evapotranspiration.
An FPGA-based heterogeneous image fusion system design method

NASA Astrophysics Data System (ADS)

Song, Le; Lin, Yu-chi; Chen, Yan-hua; Zhao, Mei-rong

2011-08-01

Taking the advantages of FPGA's low cost and compact structure, an FPGA-based heterogeneous image fusion platform is established in this study. Altera's Cyclone IV series FPGA is adopted as the core processor of the platform, and the visible light CCD camera and infrared thermal imager are used as the image-capturing device in order to obtain dualchannel heterogeneous video images. Tailor-made image fusion algorithms such as gray-scale weighted averaging, maximum selection and minimum selection methods are analyzed and compared. VHDL language and the synchronous design method are utilized to perform a reliable RTL-level description. Altera's Quartus II 9.0 software is applied to simulate and implement the algorithm modules. The contrast experiments of various fusion algorithms show that, preferably image quality of the heterogeneous image fusion can be obtained on top of the proposed system. The applied range of the different fusion algorithms is also discussed.
Image fusion based on millimeter-wave for concealed weapon detection

NASA Astrophysics Data System (ADS)

Zhu, Weiwen; Zhao, Yuejin; Deng, Chao; Zhang, Cunlin; Zhang, Yalin; Zhang, Jingshui

2010-11-01

This paper describes a novel multi sensors image fusion technology which is presented for concealed weapon detection (CWD). It is known to all, because of the good transparency of the clothes at millimeter wave band, a millimeter wave radiometer can be used to image and distinguish concealed contraband beneath clothes, for example guns, knives, detonator and so on. As a result, we adopt the passive millimeter wave (PMMW) imaging technology for airport security. However, in consideration of the wavelength of millimeter wave and the single channel mechanical scanning, the millimeter wave image has law optical resolution, which can't meet the need of practical application. Therefore, visible image (VI), which has higher resolution, is proposed for the image fusion with the millimeter wave image to enhance the readability. Before the image fusion, a novel image pre-processing which specifics to the fusion of millimeter wave imaging and visible image is adopted. And in the process of image fusion, multi resolution analysis (MRA) based on Wavelet Transform (WT) is adopted. In this way, the experiment result shows that this method has advantages in concealed weapon detection and has practical significance.
A method based on IHS cylindrical transform model for quality assessment of image fusion

NASA Astrophysics Data System (ADS)

Zhu, Xiaokun; Jia, Yonghong

2005-10-01

Image fusion technique has been widely applied to remote sensing image analysis and processing, and methods for quality assessment of image fusion in remote sensing have also become the research issues at home and abroad. Traditional assessment methods combine calculation of quantitative indexes and visual interpretation to compare fused images quantificationally and qualitatively. However, in the existing assessment methods, there are two defects: on one hand, most imdexes lack the theoretic support to compare different fusion methods. On the hand, there is not a uniform preference for most of the quantitative assessment indexes when they are applied to estimate the fusion effects. That is, the spatial resolution and spectral feature could not be analyzed synchronously by these indexes and there is not a general method to unify the spatial and spectral feature assessment. So in this paper, on the basis of the approximate general model of four traditional fusion methods, including Intensity Hue Saturation(IHS) triangle transform fusion, High Pass Filter(HPF) fusion, Principal Component Analysis(PCA) fusion, Wavelet Transform(WT) fusion, a correlation coefficient assessment method based on IHS cylindrical transform is proposed. By experiments, this method can not only get the evaluation results of spatial and spectral features on the basis of uniform preference, but also can acquire the comparison between fusion image sources and fused images, and acquire differences among fusion methods. Compared with the traditional assessment methods, the new methods is more intuitionistic, and in accord with subjective estimation.
Advances in multi-sensor data fusion: algorithms and applications.

PubMed

Dong, Jiang; Zhuang, Dafang; Huang, Yaohuan; Fu, Jingying

2009-01-01

With the development of satellite and remote sensing techniques, more and more image data from airborne/satellite sensors have become available. Multi-sensor image fusion seeks to combine information from different images to obtain more inferences than can be derived from a single sensor. In image-based application fields, image fusion has emerged as a promising research area since the end of the last century. The paper presents an overview of recent advances in multi-sensor satellite image fusion. Firstly, the most popular existing fusion algorithms are introduced, with emphasis on their recent improvements. Advances in main applications fields in remote sensing, including object identification, classification, change detection and maneuvering targets tracking, are described. Both advantages and limitations of those applications are then discussed. Recommendations are addressed, including: (1) Improvements of fusion algorithms; (2) Development of "algorithm fusion" methods; (3) Establishment of an automatic quality assessment scheme.
Local-global classifier fusion for screening chest radiographs

NASA Astrophysics Data System (ADS)

Ding, Meng; Antani, Sameer; Jaeger, Stefan; Xue, Zhiyun; Candemir, Sema; Kohli, Marc; Thoma, George

2017-03-01

Tuberculosis (TB) is a severe comorbidity of HIV and chest x-ray (CXR) analysis is a necessary step in screening for the infective disease. Automatic analysis of digital CXR images for detecting pulmonary abnormalities is critical for population screening, especially in medical resource constrained developing regions. In this article, we describe steps that improve previously reported performance of NLM's CXR screening algorithms and help advance the state of the art in the field. We propose a local-global classifier fusion method where two complementary classification systems are combined. The local classifier focuses on subtle and partial presentation of the disease leveraging information in radiology reports that roughly indicates locations of the abnormalities. In addition, the global classifier models the dominant spatial structure in the gestalt image using GIST descriptor for the semantic differentiation. Finally, the two complementary classifiers are combined using linear fusion, where the weight of each decision is calculated by the confidence probabilities from the two classifiers. We evaluated our method on three datasets in terms of the area under the Receiver Operating Characteristic (ROC) curve, sensitivity, specificity and accuracy. The evaluation demonstrates the superiority of our proposed local-global fusion method over any single classifier.
Percutaneous Thermal Ablation with Ultrasound Guidance. Fusion Imaging Guidance to Improve Conspicuity of Liver Metastasis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hakime, Antoine, E-mail: thakime@yahoo.com; Yevich, Steven; Tselikas, Lambros

PurposeTo assess whether fusion imaging-guided percutaneous microwave ablation (MWA) can improve visibility and targeting of liver metastasis that were deemed inconspicuous on ultrasound (US).Materials and MethodsMWA of liver metastasis not judged conspicuous enough on US was performed under CT/US fusion imaging guidance. The conspicuity before and after the fusion imaging was graded on a five-point scale, and significance was assessed by Wilcoxon test. Technical success, procedure time, and procedure-related complications were evaluated.ResultsA total of 35 patients with 40 liver metastases (mean size 1.3 ± 0.4 cm) were enrolled. Image fusion improved conspicuity sufficiently to allow fusion-targeted MWA in 33 patients. The time requiredmore » for image fusion processing and tumors’ identification averaged 10 ± 2.1 min (range 5–14). Initial conspicuity on US by inclusion criteria was 1.2 ± 0.4 (range 0–2), while conspicuity after localization on fusion imaging was 3.5 ± 1 (range 1–5, p < 0.001). Technical success rate was 83% (33/40) in intention-to-treat analysis and 100% in analysis of treated tumors. There were no major procedure-related complications.ConclusionsFusion imaging broadens the scope of US-guided MWA to metastasis lacking adequate conspicuity on conventional US. Fusion imaging is an effective tool to increase the conspicuity of liver metastases that were initially deemed non visualizable on conventional US imaging.« less
Image fusion via nonlocal sparse K-SVD dictionary learning.

PubMed

Li, Ying; Li, Fangyi; Bai, Bendu; Shen, Qiang

2016-03-01

Image fusion aims to merge two or more images captured via various sensors of the same scene to construct a more informative image by integrating their details. Generally, such integration is achieved through the manipulation of the representations of the images concerned. Sparse representation plays an important role in the effective description of images, offering a great potential in a variety of image processing tasks, including image fusion. Supported by sparse representation, in this paper, an approach for image fusion by the use of a novel dictionary learning scheme is proposed. The nonlocal self-similarity property of the images is exploited, not only at the stage of learning the underlying description dictionary but during the process of image fusion. In particular, the property of nonlocal self-similarity is combined with the traditional sparse dictionary. This results in an improved learned dictionary, hereafter referred to as the nonlocal sparse K-SVD dictionary (where K-SVD stands for the K times singular value decomposition that is commonly used in the literature), and abbreviated to NL_SK_SVD. The performance of the NL_SK_SVD dictionary is applied for image fusion using simultaneous orthogonal matching pursuit. The proposed approach is evaluated with different types of images, and compared with a number of alternative image fusion techniques. The resultant superior fused images using the present approach demonstrates the efficacy of the NL_SK_SVD dictionary in sparse image representation.
Research on HDR image fusion algorithm based on Laplace pyramid weight transform with extreme low-light CMOS

NASA Astrophysics Data System (ADS)

Guan, Wen; Li, Li; Jin, Weiqi; Qiu, Su; Zou, Yan

2015-10-01

Extreme-Low-Light CMOS has been widely applied in the field of night-vision as a new type of solid image sensor. But if the illumination in the scene has drastic changes or the illumination is too strong, Extreme-Low-Light CMOS can't both clearly present the high-light scene and low-light region. According to the partial saturation problem in the field of night-vision, a HDR image fusion algorithm based on the Laplace Pyramid was researched. The overall gray value and the contrast of the low light image is very low. We choose the fusion strategy based on regional average gradient for the top layer of the long exposure image and short exposure image, which has rich brightness and textural features. The remained layers which represent the edge feature information of the target are based on the fusion strategy based on regional energy. In the process of source image reconstruction with Laplacian pyramid image, we compare the fusion results with four kinds of basal images. The algorithm is tested using Matlab and compared with the different fusion strategies. We use information entropy, average gradient and standard deviation these three objective evaluation parameters for the further analysis of the fusion result. Different low illumination environment experiments show that the algorithm in this paper can rapidly get wide dynamic range while keeping high entropy. Through the verification of this algorithm features, there is a further application prospect of the optimized algorithm. Keywords: high dynamic range imaging, image fusion, multi-exposure image, weight coefficient, information fusion, Laplacian pyramid transform.
Multimodal medical image fusion by combining gradient minimization smoothing filter and non-subsampled directional filter bank

NASA Astrophysics Data System (ADS)

Zhang, Cheng; Wenbo, Mei; Huiqian, Du; Zexian, Wang

2018-04-01

A new algorithm was proposed for medical images fusion in this paper, which combined gradient minimization smoothing filter (GMSF) with non-sampled directional filter bank (NSDFB). In order to preserve more detail information, a multi scale edge preserving decomposition framework (MEDF) was used to decompose an image into a base image and a series of detail images. For the fusion of base images, the local Gaussian membership function is applied to construct the fusion weighted factor. For the fusion of detail images, NSDFB was applied to decompose each detail image into multiple directional sub-images that are fused by pulse coupled neural network (PCNN) respectively. The experimental results demonstrate that the proposed algorithm is superior to the compared algorithms in both visual effect and objective assessment.
Spatial focalization of pheromone/MAPK signaling triggers commitment to cell–cell fusion

PubMed Central

Merlini, Laura

2016-01-01

Cell fusion is universal in eukaryotes for fertilization and development, but what signals this process is unknown. Here, we show in Schizosaccharomyces pombe that fusion does not require a dedicated signal but is triggered by spatial focalization of the same pheromone–GPCR (G-protein-coupled receptor)–MAPK signaling cascade that drives earlier mating events. Autocrine cells expressing the receptor for their own pheromone trigger fusion attempts independently of cell–cell contact by concentrating pheromone release at the fusion focus, a dynamic actin aster underlying the secretion of cell wall hydrolases. Pheromone receptor and MAPK cascade are similarly enriched at the fusion focus, concomitant with fusion commitment in wild-type mating pairs. This focalization promotes cell fusion by immobilizing the fusion focus, thus driving local cell wall dissolution. We propose that fusion commitment is imposed by a local increase in MAPK concentration at the fusion focus, driven by a positive feedback between fusion focus formation and focalization of pheromone release and perception. PMID:27798845
Fusion of infrared and visible images based on BEMD and NSDFB

NASA Astrophysics Data System (ADS)

Zhu, Pan; Huang, Zhanhua; Lei, Hai

2016-07-01

This paper presents a new fusion method based on the adaptive multi-scale decomposition of bidimensional empirical mode decomposition (BEMD) and the flexible directional expansion of nonsubsampled directional filter banks (NSDFB) for visible-infrared images. Compared with conventional multi-scale fusion methods, BEMD is non-parametric and completely data-driven, which is relatively more suitable for non-linear signals decomposition and fusion. NSDFB can provide direction filtering on the decomposition levels to capture more geometrical structure of the source images effectively. In our fusion framework, the entropies of the two patterns of source images are firstly calculated and the residue of the image whose entropy is larger is extracted to make it highly relevant with the other source image. Then, the residue and the other source image are decomposed into low-frequency sub-bands and a sequence of high-frequency directional sub-bands in different scales by using BEMD and NSDFB. In this fusion scheme, two relevant fusion rules are used in low-frequency sub-bands and high-frequency directional sub-bands, respectively. Finally, the fused image is obtained by applying corresponding inverse transform. Experimental results indicate that the proposed fusion algorithm can obtain state-of-the-art performance for visible-infrared images fusion in both aspects of objective assessment and subjective visual quality even for the source images obtained in different conditions. Furthermore, the fused results have high contrast, remarkable target information and rich details information that are more suitable for human visual characteristics or machine perception.

[Contrast-enhanced ultrasound (CEUS) and image fusion for procedures of liver interventions].

PubMed

Jung, E M; Clevert, D A

2018-06-01

Contrast-enhanced ultrasound (CEUS) is becoming increasingly important for the detection and characterization of malignant liver lesions and allows percutaneous treatment when surgery is not possible. Contrast-enhanced ultrasound image fusion with computed tomography (CT) and magnetic resonance imaging (MRI) opens up further options for the targeted investigation of a modified tumor treatment. Ultrasound image fusion offers the potential for real-time imaging and can be combined with other cross-sectional imaging techniques as well as CEUS. With the implementation of ultrasound contrast agents and image fusion, ultrasound has been improved in the detection and characterization of liver lesions in comparison to other cross-sectional imaging techniques. In addition, this method can also be used for intervention procedures. The success rate of fusion-guided biopsies or CEUS-guided tumor ablation lies between 80 and 100% in the literature. Ultrasound-guided image fusion using CT or MRI data, in combination with CEUS, can facilitate diagnosis and therapy follow-up after liver interventions. In addition to the primary applications of image fusion in the diagnosis and treatment of liver lesions, further useful indications can be integrated into daily work. These include, for example, intraoperative and vascular applications as well applications in other organ systems.
Automated analysis of hot spot X-ray images at the National Ignition Facility

NASA Astrophysics Data System (ADS)

Khan, S. F.; Izumi, N.; Glenn, S.; Tommasini, R.; Benedetti, L. R.; Ma, T.; Pak, A.; Kyrala, G. A.; Springer, P.; Bradley, D. K.; Town, R. P. J.

2016-11-01

At the National Ignition Facility, the symmetry of the hot spot of imploding capsules is diagnosed by imaging the emitted x-rays using gated cameras and image plates. The symmetry of an implosion is an important factor in the yield generated from the resulting fusion process. The x-ray images are analyzed by decomposing the image intensity contours into Fourier and Legendre modes. This paper focuses on the additional protocols for the time-integrated shape analysis from image plates. For implosions with temperatures above ˜4 keV, the hard x-ray background can be utilized to infer the temperature of the hot spot.
Automated analysis of hot spot X-ray images at the National Ignition Facility

DOE PAGES

Khan, S. F.; Izumi, N.; Glenn, S.; ...

2016-09-02

At the National Ignition Facility, the symmetry of the hot spot of imploding capsules is diagnosed by imaging the emitted x-rays using gated cameras and image plates. The symmetry of an implosion is an important factor in the yield generated from the resulting fusion process. The x-ray images are analyzed by decomposing the image intensity contours into Fourier and Legendre modes. This paper focuses on the additional protocols for the time-integrated shape analysis from image plates. Here, for implosions with temperatures above ~4keV, the hard x-ray background can be utilized to infer the temperature of the hot spot.
Automated analysis of hot spot X-ray images at the National Ignition Facility

DOE Office of Scientific and Technical Information (OSTI.GOV)

Khan, S. F., E-mail: khan9@llnl.gov; Izumi, N.; Glenn, S.

At the National Ignition Facility, the symmetry of the hot spot of imploding capsules is diagnosed by imaging the emitted x-rays using gated cameras and image plates. The symmetry of an implosion is an important factor in the yield generated from the resulting fusion process. The x-ray images are analyzed by decomposing the image intensity contours into Fourier and Legendre modes. This paper focuses on the additional protocols for the time-integrated shape analysis from image plates. For implosions with temperatures above ∼4 keV, the hard x-ray background can be utilized to infer the temperature of the hot spot.
Automated analysis of hot spot X-ray images at the National Ignition Facility.

PubMed

Khan, S F; Izumi, N; Glenn, S; Tommasini, R; Benedetti, L R; Ma, T; Pak, A; Kyrala, G A; Springer, P; Bradley, D K; Town, R P J

2016-11-01

At the National Ignition Facility, the symmetry of the hot spot of imploding capsules is diagnosed by imaging the emitted x-rays using gated cameras and image plates. The symmetry of an implosion is an important factor in the yield generated from the resulting fusion process. The x-ray images are analyzed by decomposing the image intensity contours into Fourier and Legendre modes. This paper focuses on the additional protocols for the time-integrated shape analysis from image plates. For implosions with temperatures above ∼4 keV, the hard x-ray background can be utilized to infer the temperature of the hot spot.
Fusion of GFP and phase contrast images with complex shearlet transform and Haar wavelet-based energy rule.

PubMed

Qiu, Chenhui; Wang, Yuanyuan; Guo, Yanen; Xia, Shunren

2018-03-14

Image fusion techniques can integrate the information from different imaging modalities to get a composite image which is more suitable for human visual perception and further image processing tasks. Fusing green fluorescent protein (GFP) and phase contrast images is very important for subcellular localization, functional analysis of protein and genome expression. The fusion method of GFP and phase contrast images based on complex shearlet transform (CST) is proposed in this paper. Firstly the GFP image is converted to IHS model and its intensity component is obtained. Secondly the CST is performed on the intensity component and the phase contrast image to acquire the low-frequency subbands and the high-frequency subbands. Then the high-frequency subbands are merged by the absolute-maximum rule while the low-frequency subbands are merged by the proposed Haar wavelet-based energy (HWE) rule. Finally the fused image is obtained by performing the inverse CST on the merged subbands and conducting IHS-to-RGB conversion. The proposed fusion method is tested on a number of GFP and phase contrast images and compared with several popular image fusion methods. The experimental results demonstrate that the proposed fusion method can provide better fusion results in terms of subjective quality and objective evaluation. © 2018 Wiley Periodicals, Inc.
Dual wavelength imaging allows analysis of membrane fusion of influenza virus inside cells.

PubMed

Sakai, Tatsuya; Ohuchi, Masanobu; Imai, Masaki; Mizuno, Takafumi; Kawasaki, Kazunori; Kuroda, Kazumichi; Yamashina, Shohei

2006-02-01

Influenza virus hemagglutinin (HA) is a determinant of virus infectivity. Therefore, it is important to determine whether HA of a new influenza virus, which can potentially cause pandemics, is functional against human cells. The novel imaging technique reported here allows rapid analysis of HA function by visualizing viral fusion inside cells. This imaging was designed to detect fusion changing the spectrum of the fluorescence-labeled virus. Using this imaging, we detected the fusion between a virus and a very small endosome that could not be detected previously, indicating that the imaging allows highly sensitive detection of viral fusion.
Stereotactic radiation treatment planning and follow-up studies involving fused multimodality imaging.

PubMed

Hamm, Klaus D; Surber, Gunnar; Schmücking, Michael; Wurm, Reinhard E; Aschenbach, Rene; Kleinert, Gabriele; Niesen, A; Baum, Richard P

2004-11-01

Innovative new software solutions may enable image fusion to produce the desired data superposition for precise target definition and follow-up studies in radiosurgery/stereotactic radiotherapy in patients with intracranial lesions. The aim is to integrate the anatomical and functional information completely into the radiation treatment planning and to achieve an exact comparison for follow-up examinations. Special conditions and advantages of BrainLAB's fully automatic image fusion system are evaluated and described for this purpose. In 458 patients, the radiation treatment planning and some follow-up studies were performed using an automatic image fusion technique involving the use of different imaging modalities. Each fusion was visually checked and corrected as necessary. The computerized tomography (CT) scans for radiation treatment planning (slice thickness 1.25 mm), as well as stereotactic angiography for arteriovenous malformations, were acquired using head fixation with stereotactic arc or, in the case of stereotactic radiotherapy, with a relocatable stereotactic mask. Different magnetic resonance (MR) imaging sequences (T1, T2, and fluid-attenuated inversion-recovery images) and positron emission tomography (PET) scans were obtained without head fixation. Fusion results and the effects on radiation treatment planning and follow-up studies were analyzed. The precision level of the results of the automatic fusion depended primarily on the image quality, especially the slice thickness and the field homogeneity when using MR images, as well as on patient movement during data acquisition. Fully automated image fusion of different MR, CT, and PET studies was performed for each patient. Only in a few cases was it necessary to correct the fusion manually after visual evaluation. These corrections were minor and did not materially affect treatment planning. High-quality fusion of thin slices of a region of interest with a complete head data set could be performed easily. The target volume for radiation treatment planning could be accurately delineated using multimodal information provided by CT, MR, angiography, and PET studies. The fusion of follow-up image data sets yielded results that could be successfully compared and quantitatively evaluated. Depending on the quality of the originally acquired image, automated image fusion can be a very valuable tool, allowing for fast (approximately 1-2 minute) and precise fusion of all relevant data sets. Fused multimodality imaging improves the target volume definition for radiation treatment planning. High-quality follow-up image data sets should be acquired for image fusion to provide exactly comparable slices and volumetric results that will contribute to quality contol.
A new multi-spectral feature level image fusion method for human interpretation

NASA Astrophysics Data System (ADS)

Leviner, Marom; Maltz, Masha

2009-03-01

Various different methods to perform multi-spectral image fusion have been suggested, mostly on the pixel level. However, the jury is still out on the benefits of a fused image compared to its source images. We present here a new multi-spectral image fusion method, multi-spectral segmentation fusion (MSSF), which uses a feature level processing paradigm. To test our method, we compared human observer performance in a three-task experiment using MSSF against two established methods: averaging and principle components analysis (PCA), and against its two source bands, visible and infrared. The three tasks that we studied were: (1) simple target detection, (2) spatial orientation, and (3) camouflaged target detection. MSSF proved superior to the other fusion methods in all three tests; MSSF also outperformed the source images in the spatial orientation and camouflaged target detection tasks. Based on these findings, current speculation about the circumstances in which multi-spectral image fusion in general and specific fusion methods in particular would be superior to using the original image sources can be further addressed.
Designing Image Operators for MRI-PET Image Fusion of the Brain

NASA Astrophysics Data System (ADS)

Márquez, Jorge; Gastélum, Alfonso; Padilla, Miguel A.

2006-09-01

Our goal is to obtain images combining in a useful and precise way the information from 3D volumes of medical imaging sets. We address two modalities combining anatomy (Magnetic Resonance Imaging or MRI) and functional information (Positron Emission Tomography or PET). Commercial imaging software offers image fusion tools based on fixed blending or color-channel combination of two modalities, and color Look-Up Tables (LUTs), without considering the anatomical and functional character of the image features. We used a sensible approach for image fusion taking advantage mainly from the HSL (Hue, Saturation and Luminosity) color space, in order to enhance the fusion results. We further tested operators for gradient and contour extraction to enhance anatomical details, plus other spatial-domain filters for functional features corresponding to wide point-spread-function responses in PET images. A set of image-fusion operators was formulated and tested on PET and MRI acquisitions.
Infrared and visible image fusion method based on saliency detection in sparse domain

NASA Astrophysics Data System (ADS)

Liu, C. H.; Qi, Y.; Ding, W. R.

2017-06-01

Infrared and visible image fusion is a key problem in the field of multi-sensor image fusion. To better preserve the significant information of the infrared and visible images in the final fused image, the saliency maps of the source images is introduced into the fusion procedure. Firstly, under the framework of the joint sparse representation (JSR) model, the global and local saliency maps of the source images are obtained based on sparse coefficients. Then, a saliency detection model is proposed, which combines the global and local saliency maps to generate an integrated saliency map. Finally, a weighted fusion algorithm based on the integrated saliency map is developed to achieve the fusion progress. The experimental results show that our method is superior to the state-of-the-art methods in terms of several universal quality evaluation indexes, as well as in the visual quality.
Segment fusion of ToF-SIMS images.

PubMed

Milillo, Tammy M; Miller, Mary E; Fischione, Remo; Montes, Angelina; Gardella, Joseph A

2016-06-08

The imaging capabilities of time-of-flight secondary ion mass spectrometry (ToF-SIMS) have not been used to their full potential in the analysis of polymer and biological samples. Imaging has been limited by the size of the dataset and the chemical complexity of the sample being imaged. Pixel and segment based image fusion algorithms commonly used in remote sensing, ecology, geography, and geology provide a way to improve spatial resolution and classification of biological images. In this study, a sample of Arabidopsis thaliana was treated with silver nanoparticles and imaged with ToF-SIMS. These images provide insight into the uptake mechanism for the silver nanoparticles into the plant tissue, giving new understanding to the mechanism of uptake of heavy metals in the environment. The Munechika algorithm was programmed in-house and applied to achieve pixel based fusion, which improved the spatial resolution of the image obtained. Multispectral and quadtree segment or region based fusion algorithms were performed using ecognition software, a commercially available remote sensing software suite, and used to classify the images. The Munechika fusion improved the spatial resolution for the images containing silver nanoparticles, while the segment fusion allowed classification and fusion based on the tissue types in the sample, suggesting potential pathways for the uptake of the silver nanoparticles.
Decision-Level Fusion of Spatially Scattered Multi-Modal Data for Nondestructive Inspection of Surface Defects

PubMed Central

Heideklang, René; Shokouhi, Parisa

2016-01-01

This article focuses on the fusion of flaw indications from multi-sensor nondestructive materials testing. Because each testing method makes use of a different physical principle, a multi-method approach has the potential of effectively differentiating actual defect indications from the many false alarms, thus enhancing detection reliability. In this study, we propose a new technique for aggregating scattered two- or three-dimensional sensory data. Using a density-based approach, the proposed method explicitly addresses localization uncertainties such as registration errors. This feature marks one of the major of advantages of this approach over pixel-based image fusion techniques. We provide guidelines on how to set all the key parameters and demonstrate the technique’s robustness. Finally, we apply our fusion approach to experimental data and demonstrate its capability to locate small defects by substantially reducing false alarms under conditions where no single-sensor method is adequate. PMID:26784200
[Efficacy of fusion image for the preoperative assessment of anatomical variation of the anterior choroidal artery].

PubMed

Aoki, Yasuko; Endo, Hidenori; Niizuma, Kuniyasu; Inoue, Takashi; Shimizu, Hiroaki; Tominaga, Teiji

2013-12-01

We report two cases with internal carotid artery(ICA)aneurysms, in which fusion image effectively indicated the anatomical variations of the anterior choroidal artery (AchoA). Fusion image was obtained using fusion application software (Integrated Registration, Advantage Workstation VS4, GE Healthcare). When the artery passed through the choroidal fissure, it was diagnosed as AchoA. Case 1 had an aneurysm at the left ICA. Left internal carotid angiography (ICAG) showed that an artery arising from the aneurysmal neck supplied the medial occipital lobe. Fusion image showed that this artery had a branch passing through the choroidal fissure, which was diagnosed as hyperplastic AchoA. Case 2 had an aneurysm at the supraclinoid segment of the right ICA. AchoA or posterior communicating artery (PcomA) were not detected by the right ICAG. Fusion image obtained from 3D vertebral angiography (VAG) and MRI showed that the right AchoA arose from the right PcomA. Fusion image obtained from the right ICAG and the left VAG suggested that the aneurysm was located on the ICA where the PcomA regressed. Fusion image is an effective tool for assessing anatomical variations of AchoA. The present method is simple and quick for obtaining a fusion image that can be used in a real-time clinical setting.
Multispectral medical image fusion in Contourlet domain for computer based diagnosis of Alzheimer's disease.

PubMed

Bhateja, Vikrant; Moin, Aisha; Srivastava, Anuja; Bao, Le Nguyen; Lay-Ekuakille, Aimé; Le, Dac-Nhuong

2016-07-01

Computer based diagnosis of Alzheimer's disease can be performed by dint of the analysis of the functional and structural changes in the brain. Multispectral image fusion deliberates upon fusion of the complementary information while discarding the surplus information to achieve a solitary image which encloses both spatial and spectral details. This paper presents a Non-Sub-sampled Contourlet Transform (NSCT) based multispectral image fusion model for computer-aided diagnosis of Alzheimer's disease. The proposed fusion methodology involves color transformation of the input multispectral image. The multispectral image in YIQ color space is decomposed using NSCT followed by dimensionality reduction using modified Principal Component Analysis algorithm on the low frequency coefficients. Further, the high frequency coefficients are enhanced using non-linear enhancement function. Two different fusion rules are then applied to the low-pass and high-pass sub-bands: Phase congruency is applied to low frequency coefficients and a combination of directive contrast and normalized Shannon entropy is applied to high frequency coefficients. The superiority of the fusion response is depicted by the comparisons made with the other state-of-the-art fusion approaches (in terms of various fusion metrics).
Multispectral medical image fusion in Contourlet domain for computer based diagnosis of Alzheimer’s disease

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bhateja, Vikrant, E-mail: bhateja.vikrant@gmail.com, E-mail: nhuongld@hus.edu.vn; Moin, Aisha; Srivastava, Anuja

Computer based diagnosis of Alzheimer’s disease can be performed by dint of the analysis of the functional and structural changes in the brain. Multispectral image fusion deliberates upon fusion of the complementary information while discarding the surplus information to achieve a solitary image which encloses both spatial and spectral details. This paper presents a Non-Sub-sampled Contourlet Transform (NSCT) based multispectral image fusion model for computer-aided diagnosis of Alzheimer’s disease. The proposed fusion methodology involves color transformation of the input multispectral image. The multispectral image in YIQ color space is decomposed using NSCT followed by dimensionality reduction using modified Principal Componentmore » Analysis algorithm on the low frequency coefficients. Further, the high frequency coefficients are enhanced using non-linear enhancement function. Two different fusion rules are then applied to the low-pass and high-pass sub-bands: Phase congruency is applied to low frequency coefficients and a combination of directive contrast and normalized Shannon entropy is applied to high frequency coefficients. The superiority of the fusion response is depicted by the comparisons made with the other state-of-the-art fusion approaches (in terms of various fusion metrics).« less
Enhancing hyperspectral spatial resolution using multispectral image fusion: A wavelet approach

NASA Astrophysics Data System (ADS)

Jazaeri, Amin

High spectral and spatial resolution images have a significant impact in remote sensing applications. Because both spatial and spectral resolutions of spaceborne sensors are fixed by design and it is not possible to further increase the spatial or spectral resolution, techniques such as image fusion must be applied to achieve such goals. This dissertation introduces the concept of wavelet fusion between hyperspectral and multispectral sensors in order to enhance the spectral and spatial resolution of a hyperspectral image. To test the robustness of this concept, images from Hyperion (hyperspectral sensor) and Advanced Land Imager (multispectral sensor) were first co-registered and then fused using different wavelet algorithms. A regression-based fusion algorithm was also implemented for comparison purposes. The results show that the fused images using a combined bi-linear wavelet-regression algorithm have less error than other methods when compared to the ground truth. In addition, a combined regression-wavelet algorithm shows more immunity to misalignment of the pixels due to the lack of proper registration. The quantitative measures of average mean square error show that the performance of wavelet-based methods degrades when the spatial resolution of hyperspectral images becomes eight times less than its corresponding multispectral image. Regardless of what method of fusion is utilized, the main challenge in image fusion is image registration, which is also a very time intensive process. Because the combined regression wavelet technique is computationally expensive, a hybrid technique based on regression and wavelet methods was also implemented to decrease computational overhead. However, the gain in faster computation was offset by the introduction of more error in the outcome. The secondary objective of this dissertation is to examine the feasibility and sensor requirements for image fusion for future NASA missions in order to be able to perform onboard image fusion. In this process, the main challenge of image registration was resolved by registering the input images using transformation matrices of previously acquired data. The composite image resulted from the fusion process remarkably matched the ground truth, indicating the possibility of real time onboard fusion processing.
A novel fusion framework of visible light and infrared images based on singular value decomposition and adaptive DUAL-PCNN in NSST domain

NASA Astrophysics Data System (ADS)

Cheng, Boyang; Jin, Longxu; Li, Guoning

2018-06-01

Visible light and infrared images fusion has been a significant subject in imaging science. As a new contribution to this field, a novel fusion framework of visible light and infrared images based on adaptive dual-channel unit-linking pulse coupled neural networks with singular value decomposition (ADS-PCNN) in non-subsampled shearlet transform (NSST) domain is present in this paper. First, the source images are decomposed into multi-direction and multi-scale sub-images by NSST. Furthermore, an improved novel sum modified-Laplacian (INSML) of low-pass sub-image and an improved average gradient (IAVG) of high-pass sub-images are input to stimulate the ADS-PCNN, respectively. To address the large spectral difference between infrared and visible light and the occurrence of black artifacts in fused images, a local structure information operator (LSI), which comes from local area singular value decomposition in each source image, is regarded as the adaptive linking strength that enhances fusion accuracy. Compared with PCNN models in other studies, the proposed method simplifies certain peripheral parameters, and the time matrix is utilized to decide the iteration number adaptively. A series of images from diverse scenes are used for fusion experiments and the fusion results are evaluated subjectively and objectively. The results of the subjective and objective evaluation show that our algorithm exhibits superior fusion performance and is more effective than the existing typical fusion techniques.
Satellite image fusion based on principal component analysis and high-pass filtering.

PubMed

Metwalli, Mohamed R; Nasr, Ayman H; Allah, Osama S Farag; El-Rabaie, S; Abd El-Samie, Fathi E

2010-06-01

This paper presents an integrated method for the fusion of satellite images. Several commercial earth observation satellites carry dual-resolution sensors, which provide high spatial resolution or simply high-resolution (HR) panchromatic (pan) images and low-resolution (LR) multi-spectral (MS) images. Image fusion methods are therefore required to integrate a high-spectral-resolution MS image with a high-spatial-resolution pan image to produce a pan-sharpened image with high spectral and spatial resolutions. Some image fusion methods such as the intensity, hue, and saturation (IHS) method, the principal component analysis (PCA) method, and the Brovey transform (BT) method provide HR MS images, but with low spectral quality. Another family of image fusion methods, such as the high-pass-filtering (HPF) method, operates on the basis of the injection of high frequency components from the HR pan image into the MS image. This family of methods provides less spectral distortion. In this paper, we propose the integration of the PCA method and the HPF method to provide a pan-sharpened MS image with superior spatial resolution and less spectral distortion. The experimental results show that the proposed fusion method retains the spectral characteristics of the MS image and, at the same time, improves the spatial resolution of the pan-sharpened image.
Remote sensing fusion based on guided image filtering

NASA Astrophysics Data System (ADS)

Zhao, Wenfei; Dai, Qinling; Wang, Leiguang

2015-12-01

In this paper, we propose a novel remote sensing fusion approach based on guided image filtering. The fused images can well preserve the spectral features of the original multispectral (MS) images, meanwhile, enhance the spatial details information. Four quality assessment indexes are also introduced to evaluate the fusion effect when compared with other fusion methods. Experiments carried out on Gaofen-2, QuickBird, WorldView-2 and Landsat-8 images. And the results show an excellent performance of the proposed method.

Hierarchical Multi-atlas Label Fusion with Multi-scale Feature Representation and Label-specific Patch Partition

PubMed Central

Wu, Guorong; Kim, Minjeong; Sanroma, Gerard; Wang, Qian; Munsell, Brent C.; Shen, Dinggang

2014-01-01

Multi-atlas patch-based label fusion methods have been successfully used to improve segmentation accuracy in many important medical image analysis applications. In general, to achieve label fusion a single target image is first registered to several atlas images, after registration a label is assigned to each target point in the target image by determining the similarity between the underlying target image patch (centered at the target point) and the aligned image patch in each atlas image. To achieve the highest level of accuracy during the label fusion process it’s critical the chosen patch similarity measurement accurately captures the tissue/shape appearance of the anatomical structure. One major limitation of existing state-of-the-art label fusion methods is that they often apply a fixed size image patch throughout the entire label fusion procedure. Doing so may severely affect the fidelity of the patch similarity measurement, which in turn may not adequately capture complex tissue appearance patterns expressed by the anatomical structure. To address this limitation, we advance state-of-the-art by adding three new label fusion contributions: First, each image patch now characterized by a multi-scale feature representation that encodes both local and semi-local image information. Doing so will increase the accuracy of the patch-based similarity measurement. Second, to limit the possibility of the patch-based similarity measurement being wrongly guided by the presence of multiple anatomical structures in the same image patch, each atlas image patch is further partitioned into a set of label-specific partial image patches according to the existing labels. Since image information has now been semantically divided into different patterns, these new label-specific atlas patches make the label fusion process more specific and flexible. Lastly, in order to correct target points that are mislabeled during label fusion, a hierarchically approach is used to improve the label fusion results. In particular, a coarse-to-fine iterative label fusion approach is used that gradually reduces the patch size. To evaluate the accuracy of our label fusion approach, the proposed method was used to segment the hippocampus in the ADNI dataset and 7.0 tesla MR images, sub-cortical regions in LONI LBPA40 dataset, mid-brain regions in SATA dataset from MICCAI 2013 segmentation challenge, and a set of key internal gray matter structures in IXI dataset. In all experiments, the segmentation results of the proposed hierarchical label fusion method with multi-scale feature representations and label-specific atlas patches are more accurate than several well-known state-of-the-art label fusion methods. PMID:25463474
Evaluation of image registration in PET/CT of the liver and recommendations for optimized imaging.

PubMed

Vogel, Wouter V; van Dalen, Jorn A; Wiering, Bas; Huisman, Henkjan; Corstens, Frans H M; Ruers, Theo J M; Oyen, Wim J G

2007-06-01

Multimodality PET/CT of the liver can be performed with an integrated (hybrid) PET/CT scanner or with software fusion of dedicated PET and CT. Accurate anatomic correlation and good image quality of both modalities are important prerequisites, regardless of the applied method. Registration accuracy is influenced by breathing motion differences on PET and CT, which may also have impact on (attenuation correction-related) artifacts, especially in the upper abdomen. The impact of these issues was evaluated for both hybrid PET/CT and software fusion, focused on imaging of the liver. Thirty patients underwent hybrid PET/CT, 20 with CT during expiration breath-hold (EB) and 10 with CT during free breathing (FB). Ten additional patients underwent software fusion of dedicated PET and dedicated expiration breath-hold CT (SF). The image registration accuracy was evaluated at the location of liver borders on CT and uncorrected PET images and at the location of liver lesions. Attenuation-correction artifacts were evaluated by comparison of liver borders on uncorrected and attenuation-corrected PET images. CT images were evaluated for the presence of breathing artifacts. In EB, 40% of patients had an absolute registration error of the diaphragm in the craniocaudal direction of >1 cm (range, -16 to 44 mm), and 45% of lesions were mispositioned >1 cm. In 50% of cases, attenuation-correction artifacts caused a deformation of the liver dome on PET of >1 cm. Poor compliance to breath-hold instructions caused CT artifacts in 55% of cases. In FB, 30% had registration errors of >1 cm (range, -4 to 16 mm) and PET artifacts were less extensive, but all CT images had breathing artifacts. As SF allows independent alignment of PET and CT, no registration errors or artifacts of >1 cm of the diaphragm occurred. Hybrid PET/CT of the liver may have significant registration errors and artifacts related to breathing motion. The extent of these issues depends on the selected breathing protocol and the speed of the CT scanner. No protocol or scanner can guarantee perfect image fusion. On the basis of these findings, recommendations were formulated with regard to scanner requirements, breathing protocols, and reporting.
Quality assessment of remote sensing image fusion using feature-based fourth-order correlation coefficient

NASA Astrophysics Data System (ADS)

Ma, Dan; Liu, Jun; Chen, Kai; Li, Huali; Liu, Ping; Chen, Huijuan; Qian, Jing

2016-04-01

In remote sensing fusion, the spatial details of a panchromatic (PAN) image and the spectrum information of multispectral (MS) images will be transferred into fused images according to the characteristics of the human visual system. Thus, a remote sensing image fusion quality assessment called feature-based fourth-order correlation coefficient (FFOCC) is proposed. FFOCC is based on the feature-based coefficient concept. Spatial features related to spatial details of the PAN image and spectral features related to the spectrum information of MS images are first extracted from the fused image. Then, the fourth-order correlation coefficient between the spatial and spectral features is calculated and treated as the assessment result. FFOCC was then compared with existing widely used indices, such as Erreur Relative Globale Adimensionnelle de Synthese, and quality assessed with no reference. Results of the fusion and distortion experiments indicate that the FFOCC is consistent with subjective evaluation. FFOCC significantly outperforms the other indices in evaluating fusion images that are produced by different fusion methods and that are distorted in spatial and spectral features by blurring, adding noise, and changing intensity. All the findings indicate that the proposed method is an objective and effective quality assessment for remote sensing image fusion.
A fast fusion scheme for infrared and visible light images in NSCT domain

NASA Astrophysics Data System (ADS)

Zhao, Chunhui; Guo, Yunting; Wang, Yulei

2015-09-01

Fusion of infrared and visible light images is an effective way to obtain a simultaneous visualization of details of background provided by visible light image and hiding target information provided by infrared image, which is more suitable for browsing and further processing. Two crucial components for infrared and visual light image fusion are improving its fusion performance as well as reducing its computational burden. In this paper, a novel fusion algorithm named pixel information estimation is proposed, which determines the weights by evaluating the information of pixel and is well applied in visible light and infrared image fusion with better fusion quality and lower time-consumption. Besides, a fast realization of non-subsampled contourlet transform is also proposed in this paper to improve the computational efficiency. To verify the advantage of the proposed method, this paper compares it with several popular ones in six evaluation metrics over four different image groups. Experimental results show that the proposed algorithm gets a more effective result with much less time consuming and performs well in both subjective evaluation and objective indicators.
Different source image fusion based on FPGA

NASA Astrophysics Data System (ADS)

Luo, Xiao; Piao, Yan

2016-03-01

The fusion technology of video image is to make the video obtained by different image sensors complementary to each other by some technical means, so as to obtain the video information which is rich in information and suitable for the human eye system. Infrared cameras in harsh environments such as when smoke, fog and low light situations penetrating power, but the ability to obtain the details of the image is poor, does not meet the human visual system. Single visible light imaging can be rich in detail, high resolution images and for the visual system, but the visible image easily affected by the external environment. Infrared image and visible image fusion process involved in the video image fusion algorithm complexity and high calculation capacity, have occupied more memory resources, high clock rate requirements, such as software, c ++, c, etc. to achieve more, but based on Hardware platform less. In this paper, based on the imaging characteristics of infrared images and visible light images, the software and hardware are combined to obtain the registration parameters through software matlab, and the gray level weighted average method is used to implement the hardware platform. Information fusion, and finally the fusion image can achieve the goal of effectively improving the acquisition of information to increase the amount of information in the image.
[Perceptual sharpness metric for visible and infrared color fusion images].

PubMed

Gao, Shao-Shu; Jin, Wei-Qi; Wang, Xia; Wang, Ling-Xue; Luo, Yuan

2012-12-01

For visible and infrared color fusion images, objective sharpness assessment model is proposed to measure the clarity of detail and edge definition of the fusion image. Firstly, the contrast sensitivity functions (CSF) of the human visual system is used to reduce insensitive frequency components under certain viewing conditions. Secondly, perceptual contrast model, which takes human luminance masking effect into account, is proposed based on local band-limited contrast model. Finally, the perceptual contrast is calculated in the region of interest (contains image details and edges) in the fusion image to evaluate image perceptual sharpness. Experimental results show that the proposed perceptual sharpness metrics provides better predictions, which are more closely matched to human perceptual evaluations, than five existing sharpness (blur) metrics for color images. The proposed perceptual sharpness metrics can evaluate the perceptual sharpness for color fusion images effectively.
Tools and Methods for the Registration and Fusion of Remotely Sensed Data

NASA Technical Reports Server (NTRS)

Goshtasby, Arthur Ardeshir; LeMoigne, Jacqueline

2010-01-01

Tools and methods for image registration were reviewed. Methods for the registration of remotely sensed data at NASA were discussed. Image fusion techniques were reviewed. Challenges in registration of remotely sensed data were discussed. Examples of image registration and image fusion were given.
Multimodality Tumor Delineation and Predictive Modelling via Fuzzy-Fusion Deformable Models and Biological Potential Functions

NASA Astrophysics Data System (ADS)

Wasserman, Richard Marc

The radiation therapy treatment planning (RTTP) process may be subdivided into three planning stages: gross tumor delineation, clinical target delineation, and modality dependent target definition. The research presented will focus on the first two planning tasks. A gross tumor target delineation methodology is proposed which focuses on the integration of MRI, CT, and PET imaging data towards the generation of a mathematically optimal tumor boundary. The solution to this problem is formulated within a framework integrating concepts from the fields of deformable modelling, region growing, fuzzy logic, and data fusion. The resulting fuzzy fusion algorithm can integrate both edge and region information from multiple medical modalities to delineate optimal regions of pathological tissue content. The subclinical boundaries of an infiltrating neoplasm cannot be determined explicitly via traditional imaging methods and are often defined to extend a fixed distance from the gross tumor boundary. In order to improve the clinical target definition process an estimation technique is proposed via which tumor growth may be modelled and subclinical growth predicted. An in vivo, macroscopic primary brain tumor growth model is presented, which may be fit to each patient undergoing treatment, allowing for the prediction of future growth and consequently the ability to estimate subclinical local invasion. Additionally, the patient specific in vivo tumor model will be of significant utility in multiple diagnostic clinical applications.
Benchmarking of data fusion algorithms in support of earth observation based Antarctic wildlife monitoring

NASA Astrophysics Data System (ADS)

Witharana, Chandi; LaRue, Michelle A.; Lynch, Heather J.

2016-03-01

Remote sensing is a rapidly developing tool for mapping the abundance and distribution of Antarctic wildlife. While both panchromatic and multispectral imagery have been used in this context, image fusion techniques have received little attention. We tasked seven widely-used fusion algorithms: Ehlers fusion, hyperspherical color space fusion, high-pass fusion, principal component analysis (PCA) fusion, University of New Brunswick fusion, and wavelet-PCA fusion to resolution enhance a series of single-date QuickBird-2 and Worldview-2 image scenes comprising penguin guano, seals, and vegetation. Fused images were assessed for spectral and spatial fidelity using a variety of quantitative quality indicators and visual inspection methods. Our visual evaluation elected the high-pass fusion algorithm and the University of New Brunswick fusion algorithm as best for manual wildlife detection while the quantitative assessment suggested the Gram-Schmidt fusion algorithm and the University of New Brunswick fusion algorithm as best for automated classification. The hyperspherical color space fusion algorithm exhibited mediocre results in terms of spectral and spatial fidelities. The PCA fusion algorithm showed spatial superiority at the expense of spectral inconsistencies. The Ehlers fusion algorithm and the wavelet-PCA algorithm showed the weakest performances. As remote sensing becomes a more routine method of surveying Antarctic wildlife, these benchmarks will provide guidance for image fusion and pave the way for more standardized products for specific types of wildlife surveys.
A Fusion Algorithm for GFP Image and Phase Contrast Image of Arabidopsis Cell Based on SFL-Contourlet Transform

PubMed Central

Feng, Peng; Wang, Jing; Wei, Biao; Mi, Deling

2013-01-01

A hybrid multiscale and multilevel image fusion algorithm for green fluorescent protein (GFP) image and phase contrast image of Arabidopsis cell is proposed in this paper. Combining intensity-hue-saturation (IHS) transform and sharp frequency localization Contourlet transform (SFL-CT), this algorithm uses different fusion strategies for different detailed subbands, which include neighborhood consistency measurement (NCM) that can adaptively find balance between color background and gray structure. Also two kinds of neighborhood classes based on empirical model are taken into consideration. Visual information fidelity (VIF) as an objective criterion is introduced to evaluate the fusion image. The experimental results of 117 groups of Arabidopsis cell image from John Innes Center show that the new algorithm cannot only make the details of original images well preserved but also improve the visibility of the fusion image, which shows the superiority of the novel method to traditional ones. PMID:23476716
Counter sniper: a localization system based on dual thermal imager

NASA Astrophysics Data System (ADS)

He, Yuqing; Liu, Feihu; Wu, Zheng; Jin, Weiqi; Du, Benfang

2010-11-01

Sniper tactics is widely used in modern warfare, which puts forward the urgent requirement of counter sniper detection devices. This paper proposed the anti-sniper detection system based on a dual-thermal imaging system. Combining the infrared characteristics of the muzzle flash and bullet trajectory of binocular infrared images obtained by the dual-infrared imaging system, the exact location of the sniper was analyzed and calculated. This paper mainly focuses on the system design method, which includes the structure and parameter selection. It also analyzes the exact location calculation method based on the binocular stereo vision and image analysis, and give the fusion result as the sniper's position.
Development of a fusion approach selection tool

NASA Astrophysics Data System (ADS)

Pohl, C.; Zeng, Y.

2015-06-01

During the last decades number and quality of available remote sensing satellite sensors for Earth observation has grown significantly. The amount of available multi-sensor images along with their increased spatial and spectral resolution provides new challenges to Earth scientists. With a Fusion Approach Selection Tool (FAST) the remote sensing community would obtain access to an optimized and improved image processing technology. Remote sensing image fusion is a mean to produce images containing information that is not inherent in the single image alone. In the meantime the user has access to sophisticated commercialized image fusion techniques plus the option to tune the parameters of each individual technique to match the anticipated application. This leaves the operator with an uncountable number of options to combine remote sensing images, not talking about the selection of the appropriate images, resolution and bands. Image fusion can be a machine and time-consuming endeavour. In addition it requires knowledge about remote sensing, image fusion, digital image processing and the application. FAST shall provide the user with a quick overview of processing flows to choose from to reach the target. FAST will ask for available images, application parameters and desired information to process this input to come out with a workflow to quickly obtain the best results. It will optimize data and image fusion techniques. It provides an overview on the possible results from which the user can choose the best. FAST will enable even inexperienced users to use advanced processing methods to maximize the benefit of multi-sensor image exploitation.
A novel framework of tissue membrane systems for image fusion.

PubMed

Zhang, Zulin; Yi, Xinzhong; Peng, Hong

2014-01-01

This paper proposes a tissue membrane system-based framework to deal with the optimal image fusion problem. A spatial domain fusion algorithm is given, and a tissue membrane system of multiple cells is used as its computing framework. Based on the multicellular structure and inherent communication mechanism of the tissue membrane system, an improved velocity-position model is developed. The performance of the fusion framework is studied with comparison of several traditional fusion methods as well as genetic algorithm (GA)-based and differential evolution (DE)-based spatial domain fusion methods. Experimental results show that the proposed fusion framework is superior or comparable to the other methods and can be efficiently used for image fusion.
Multi-atlas label fusion using hybrid of discriminative and generative classifiers for segmentation of cardiac MR images.

PubMed

Sedai, Suman; Garnavi, Rahil; Roy, Pallab; Xi Liang

2015-08-01

Multi-atlas segmentation first registers each atlas image to the target image and transfers the label of atlas image to the coordinate system of the target image. The transferred labels are then combined, using a label fusion algorithm. In this paper, we propose a novel label fusion method which aggregates discriminative learning and generative modeling for segmentation of cardiac MR images. First, a probabilistic Random Forest classifier is trained as a discriminative model to obtain the prior probability of a label at the given voxel of the target image. Then, a probability distribution of image patches is modeled using Gaussian Mixture Model for each label, providing the likelihood of the voxel belonging to the label. The final label posterior is obtained by combining the classification score and the likelihood score under Bayesian rule. Comparative study performed on MICCAI 2013 SATA Segmentation Challenge demonstrates that our proposed hybrid label fusion algorithm is accurate than other five state-of-the-art label fusion methods. The proposed method obtains dice similarity coefficient of 0.94 and 0.92 in segmenting epicardium and endocardium respectively. Moreover, our label fusion method achieves more accurate segmentation results compared to four other label fusion methods.
Log-Gabor Energy Based Multimodal Medical Image Fusion in NSCT Domain

PubMed Central

Yang, Yong; Tong, Song; Huang, Shuying; Lin, Pan

2014-01-01

Multimodal medical image fusion is a powerful tool in clinical applications such as noninvasive diagnosis, image-guided radiotherapy, and treatment planning. In this paper, a novel nonsubsampled Contourlet transform (NSCT) based method for multimodal medical image fusion is presented, which is approximately shift invariant and can effectively suppress the pseudo-Gibbs phenomena. The source medical images are initially transformed by NSCT followed by fusing low- and high-frequency components. The phase congruency that can provide a contrast and brightness-invariant representation is applied to fuse low-frequency coefficients, whereas the Log-Gabor energy that can efficiently determine the frequency coefficients from the clear and detail parts is employed to fuse the high-frequency coefficients. The proposed fusion method has been compared with the discrete wavelet transform (DWT), the fast discrete curvelet transform (FDCT), and the dual tree complex wavelet transform (DTCWT) based image fusion methods and other NSCT-based methods. Visually and quantitatively experimental results indicate that the proposed fusion method can obtain more effective and accurate fusion results of multimodal medical images than other algorithms. Further, the applicability of the proposed method has been testified by carrying out a clinical example on a woman affected with recurrent tumor images. PMID:25214889
[A study on medical image fusion].

PubMed

Zhang, Er-hu; Bian, Zheng-zhong

2002-09-01

Five algorithms with its advantages and disadvantage for medical image fusion are analyzed. Four kinds of quantitative evaluation criteria for the quality of image fusion algorithms are proposed and these will give us some guidance for future research.
Infrared and visual image fusion method based on discrete cosine transform and local spatial frequency in discrete stationary wavelet transform domain

NASA Astrophysics Data System (ADS)

Jin, Xin; Jiang, Qian; Yao, Shaowen; Zhou, Dongming; Nie, Rencan; Lee, Shin-Jye; He, Kangjian

2018-01-01

In order to promote the performance of infrared and visual image fusion and provide better visual effects, this paper proposes a hybrid fusion method for infrared and visual image by the combination of discrete stationary wavelet transform (DSWT), discrete cosine transform (DCT) and local spatial frequency (LSF). The proposed method has three key processing steps. Firstly, DSWT is employed to decompose the important features of the source image into a series of sub-images with different levels and spatial frequencies. Secondly, DCT is used to separate the significant details of the sub-images according to the energy of different frequencies. Thirdly, LSF is applied to enhance the regional features of DCT coefficients, and it can be helpful and useful for image feature extraction. Some frequently-used image fusion methods and evaluation metrics are employed to evaluate the validity of the proposed method. The experiments indicate that the proposed method can achieve good fusion effect, and it is more efficient than other conventional image fusion methods.
PET-CT image fusion using random forest and à-trous wavelet transform.

PubMed

Seal, Ayan; Bhattacharjee, Debotosh; Nasipuri, Mita; Rodríguez-Esparragón, Dionisio; Menasalvas, Ernestina; Gonzalo-Martin, Consuelo

2018-03-01

New image fusion rules for multimodal medical images are proposed in this work. Image fusion rules are defined by random forest learning algorithm and a translation-invariant à-trous wavelet transform (AWT). The proposed method is threefold. First, source images are decomposed into approximation and detail coefficients using AWT. Second, random forest is used to choose pixels from the approximation and detail coefficients for forming the approximation and detail coefficients of the fused image. Lastly, inverse AWT is applied to reconstruct fused image. All experiments have been performed on 198 slices of both computed tomography and positron emission tomography images of a patient. A traditional fusion method based on Mallat wavelet transform has also been implemented on these slices. A new image fusion performance measure along with 4 existing measures has been presented, which helps to compare the performance of 2 pixel level fusion methods. The experimental results clearly indicate that the proposed method outperforms the traditional method in terms of visual and quantitative qualities and the new measure is meaningful. Copyright © 2017 John Wiley & Sons, Ltd.
Image Fusion of CT and MR with Sparse Representation in NSST Domain

PubMed Central

Qiu, Chenhui; Wang, Yuanyuan; Zhang, Huan

2017-01-01

Multimodal image fusion techniques can integrate the information from different medical images to get an informative image that is more suitable for joint diagnosis, preoperative planning, intraoperative guidance, and interventional treatment. Fusing images of CT and different MR modalities are studied in this paper. Firstly, the CT and MR images are both transformed to nonsubsampled shearlet transform (NSST) domain. So the low-frequency components and high-frequency components are obtained. Then the high-frequency components are merged using the absolute-maximum rule, while the low-frequency components are merged by a sparse representation- (SR-) based approach. And the dynamic group sparsity recovery (DGSR) algorithm is proposed to improve the performance of the SR-based approach. Finally, the fused image is obtained by performing the inverse NSST on the merged components. The proposed fusion method is tested on a number of clinical CT and MR images and compared with several popular image fusion methods. The experimental results demonstrate that the proposed fusion method can provide better fusion results in terms of subjective quality and objective evaluation. PMID:29250134
Image Fusion of CT and MR with Sparse Representation in NSST Domain.

PubMed

Qiu, Chenhui; Wang, Yuanyuan; Zhang, Huan; Xia, Shunren

2017-01-01

Multimodal image fusion techniques can integrate the information from different medical images to get an informative image that is more suitable for joint diagnosis, preoperative planning, intraoperative guidance, and interventional treatment. Fusing images of CT and different MR modalities are studied in this paper. Firstly, the CT and MR images are both transformed to nonsubsampled shearlet transform (NSST) domain. So the low-frequency components and high-frequency components are obtained. Then the high-frequency components are merged using the absolute-maximum rule, while the low-frequency components are merged by a sparse representation- (SR-) based approach. And the dynamic group sparsity recovery (DGSR) algorithm is proposed to improve the performance of the SR-based approach. Finally, the fused image is obtained by performing the inverse NSST on the merged components. The proposed fusion method is tested on a number of clinical CT and MR images and compared with several popular image fusion methods. The experimental results demonstrate that the proposed fusion method can provide better fusion results in terms of subjective quality and objective evaluation.

Sensor and information fusion for improved hostile fire situational awareness

NASA Astrophysics Data System (ADS)

Scanlon, Michael V.; Ludwig, William D.

2010-04-01

A research-oriented Army Technology Objective (ATO) named Sensor and Information Fusion for Improved Hostile Fire Situational Awareness uniquely focuses on the underpinning technologies to detect and defeat any hostile threat; before, during, and after its occurrence. This is a joint effort led by the Army Research Laboratory, with the Armaments and the Communications and Electronics Research, Development, and Engineering Centers (CERDEC and ARDEC) partners. It addresses distributed sensor fusion and collaborative situational awareness enhancements, focusing on the underpinning technologies to detect/identify potential hostile shooters prior to firing a shot and to detect/classify/locate the firing point of hostile small arms, mortars, rockets, RPGs, and missiles after the first shot. A field experiment conducted addressed not only diverse modality sensor performance and sensor fusion benefits, but gathered useful data to develop and demonstrate the ad hoc networking and dissemination of relevant data and actionable intelligence. Represented at this field experiment were various sensor platforms such as UGS, soldier-worn, manned ground vehicles, UGVs, UAVs, and helicopters. This ATO continues to evaluate applicable technologies to include retro-reflection, UV, IR, visible, glint, LADAR, radar, acoustic, seismic, E-field, narrow-band emission and image processing techniques to detect the threats with very high confidence. Networked fusion of multi-modal data will reduce false alarms and improve actionable intelligence by distributing grid coordinates, detection report features, and imagery of threats.
Enhanced image fusion using directional contrast rules in fuzzy transform domain.

PubMed

Nandal, Amita; Rosales, Hamurabi Gamboa

2016-01-01

In this paper a novel image fusion algorithm based on directional contrast in fuzzy transform (FTR) domain is proposed. Input images to be fused are first divided into several non-overlapping blocks. The components of these sub-blocks are fused using directional contrast based fuzzy fusion rule in FTR domain. The fused sub-blocks are then transformed into original size blocks using inverse-FTR. Further, these inverse transformed blocks are fused according to select maximum based fusion rule for reconstructing the final fused image. The proposed fusion algorithm is both visually and quantitatively compared with other standard and recent fusion algorithms. Experimental results demonstrate that the proposed method generates better results than the other methods.
Multiscale infrared and visible image fusion using gradient domain guided image filtering

NASA Astrophysics Data System (ADS)

Zhu, Jin; Jin, Weiqi; Li, Li; Han, Zhenghao; Wang, Xia

2018-03-01

For better surveillance with infrared and visible imaging, a novel hybrid multiscale decomposition fusion method using gradient domain guided image filtering (HMSD-GDGF) is proposed in this study. In this method, hybrid multiscale decomposition with guided image filtering and gradient domain guided image filtering of source images are first applied before the weight maps of each scale are obtained using a saliency detection technology and filtering means with three different fusion rules at different scales. The three types of fusion rules are for small-scale detail level, large-scale detail level, and base level. Finally, the target becomes more salient and can be more easily detected in the fusion result, with the detail information of the scene being fully displayed. After analyzing the experimental comparisons with state-of-the-art fusion methods, the HMSD-GDGF method has obvious advantages in fidelity of salient information (including structural similarity, brightness, and contrast), preservation of edge features, and human visual perception. Therefore, visual effects can be improved by using the proposed HMSD-GDGF method.
A new evaluation method research for fusion quality of infrared and visible images

NASA Astrophysics Data System (ADS)

Ge, Xingguo; Ji, Yiguo; Tao, Zhongxiang; Tian, Chunyan; Ning, Chengda

2017-03-01

In order to objectively evaluate the fusion effect of infrared and visible image, a fusion evaluation method for infrared and visible images based on energy-weighted average structure similarity and edge information retention value is proposed for drawbacks of existing evaluation methods. The evaluation index of this method is given, and the infrared and visible image fusion results under different algorithms and environments are made evaluation experiments on the basis of this index. The experimental results show that the objective evaluation index is consistent with the subjective evaluation results obtained from this method, which shows that the method is a practical and effective fusion image quality evaluation method.
The optimal algorithm for Multi-source RS image fusion.

PubMed

Fu, Wei; Huang, Shui-Guang; Li, Zeng-Shun; Shen, Hao; Li, Jun-Shuai; Wang, Peng-Yuan

2016-01-01

In order to solve the issue which the fusion rules cannot be self-adaptively adjusted by using available fusion methods according to the subsequent processing requirements of Remote Sensing (RS) image, this paper puts forward GSDA (genetic-iterative self-organizing data analysis algorithm) by integrating the merit of genetic arithmetic together with the advantage of iterative self-organizing data analysis algorithm for multi-source RS image fusion. The proposed algorithm considers the wavelet transform of the translation invariance as the model operator, also regards the contrast pyramid conversion as the observed operator. The algorithm then designs the objective function by taking use of the weighted sum of evaluation indices, and optimizes the objective function by employing GSDA so as to get a higher resolution of RS image. As discussed above, the bullet points of the text are summarized as follows.•The contribution proposes the iterative self-organizing data analysis algorithm for multi-source RS image fusion.•This article presents GSDA algorithm for the self-adaptively adjustment of the fusion rules.•This text comes up with the model operator and the observed operator as the fusion scheme of RS image based on GSDA. The proposed algorithm opens up a novel algorithmic pathway for multi-source RS image fusion by means of GSDA.
The usefulness of (18)F-FDG PET/MRI fusion image in diagnosing pancreatic tumor: comparison with (18)F-FDG PET/CT.

PubMed

Nagamachi, Shigeki; Nishii, Ryuichi; Wakamatsu, Hideyuki; Mizutani, Youichi; Kiyohara, Shogo; Fujita, Seigo; Futami, Shigemi; Sakae, Tatefumi; Furukoji, Eiji; Tamura, Shozo; Arita, Hideo; Chijiiwa, Kazuo; Kawai, Keiichi

2013-07-01

This study aimed at demonstrating the feasibility of retrospectively fused (18)F FDG-PET and MRI (PET/MRI fusion image) in diagnosing pancreatic tumor, in particular differentiating malignant tumor from benign lesions. In addition, we evaluated additional findings characterizing pancreatic lesions by FDG-PET/MRI fusion image. We analyzed retrospectively 119 patients: 96 cancers and 23 benign lesions. FDG-PET/MRI fusion images (PET/T1 WI or PET/T2WI) were made by dedicated software using 1.5 Tesla (T) MRI image and FDG-PET images. These images were interpreted by two well-trained radiologists without knowledge of clinical information and compared with FDG-PET/CT images. We compared the differential diagnostic capability between PET/CT and FDG-PET/MRI fusion image. In addition, we evaluated additional findings such as tumor structure and tumor invasion. FDG-PET/MRI fusion image significantly improved accuracy compared with that of PET/CT (96.6 vs. 86.6 %). As additional finding, dilatation of main pancreatic duct was noted in 65.9 % of solid types and in 22.6 % of cystic types, on PET/MRI-T2 fusion image. Similarly, encasement of adjacent vessels was noted in 43.1 % of solid types and in 6.5 % of cystic types. Particularly in cystic types, intra-tumor structures such as mural nodule (35.4 %) or intra-cystic septum (74.2 %) were detected additionally. Besides, PET/MRI-T2 fusion image could detect extra benign cystic lesions (9.1 % in solid type and 9.7 % in cystic type) that were not noted by PET/CT. In diagnosing pancreatic lesions, FDG-PET/MRI fusion image was useful in differentiating pancreatic cancer from benign lesions. Furthermore, it was helpful in evaluating relationship between lesions and surrounding tissues as well as in detecting extra benign cysts.
Weber-aware weighted mutual information evaluation for infrared-visible image fusion

NASA Astrophysics Data System (ADS)

Luo, Xiaoyan; Wang, Shining; Yuan, Ding

2016-10-01

A performance metric for infrared and visible image fusion is proposed based on Weber's law. To indicate the stimulus of source images, two Weber components are provided. One is differential excitation to reflect the spectral signal of visible and infrared images, and the other is orientation to capture the scene structure feature. By comparing the corresponding Weber component in infrared and visible images, the source pixels can be marked with different dominant properties in intensity or structure. If the pixels have the same dominant property label, the pixels are grouped to calculate the mutual information (MI) on the corresponding Weber components between dominant source and fused images. Then, the final fusion metric is obtained via weighting the group-wise MI values according to the number of pixels in different groups. Experimental results demonstrate that the proposed metric performs well on popular image fusion cases and outperforms other image fusion metrics.
Poster — Thur Eve — 09: Evaluation of electrical impedance and computed tomography fusion algorithms using an anthropomorphic phantom

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chugh, Brige Paul; Krishnan, Kalpagam; Liu, Jeff

2014-08-15

Integration of biological conductivity information provided by Electrical Impedance Tomography (EIT) with anatomical information provided by Computed Tomography (CT) imaging could improve the ability to characterize tissues in clinical applications. In this paper, we report results of our study which compared the fusion of EIT with CT using three different image fusion algorithms, namely: weighted averaging, wavelet fusion, and ROI indexing. The ROI indexing method of fusion involves segmenting the regions of interest from the CT image and replacing the pixels with the pixels of the EIT image. The three algorithms were applied to a CT and EIT image ofmore » an anthropomorphic phantom, constructed out of five acrylic contrast targets with varying diameter embedded in a base of gelatin bolus. The imaging performance was assessed using Detectability and Structural Similarity Index Measure (SSIM). Wavelet fusion and ROI-indexing resulted in lower Detectability (by 35% and 47%, respectively) yet higher SSIM (by 66% and 73%, respectively) than weighted averaging. Our results suggest that wavelet fusion and ROI-indexing yielded more consistent and optimal fusion performance than weighted averaging.« less
Radar image and data fusion for natural hazards characterisation

USGS Publications Warehouse

Lu, Zhong; Dzurisin, Daniel; Jung, Hyung-Sup; Zhang, Jixian; Zhang, Yonghong

2010-01-01

Fusion of synthetic aperture radar (SAR) images through interferometric, polarimetric and tomographic processing provides an all - weather imaging capability to characterise and monitor various natural hazards. This article outlines interferometric synthetic aperture radar (InSAR) processing and products and their utility for natural hazards characterisation, provides an overview of the techniques and applications related to fusion of SAR/InSAR images with optical and other images and highlights the emerging SAR fusion technologies. In addition to providing precise land - surface digital elevation maps, SAR - derived imaging products can map millimetre - scale elevation changes driven by volcanic, seismic and hydrogeologic processes, by landslides and wildfires and other natural hazards. With products derived from the fusion of SAR and other images, scientists can monitor the progress of flooding, estimate water storage changes in wetlands for improved hydrological modelling predictions and assessments of future flood impacts and map vegetation structure on a global scale and monitor its changes due to such processes as fire, volcanic eruption and deforestation. With the availability of SAR images in near real - time from multiple satellites in the near future, the fusion of SAR images with other images and data is playing an increasingly important role in understanding and forecasting natural hazards.
Image fusion-guided portal vein puncture during transjugular intrahepatic portosystemic shunt placement.

PubMed

Rouabah, K; Varoquaux, A; Caporossi, J M; Louis, G; Jacquier, A; Bartoli, J M; Moulin, G; Vidal, V

2016-11-01

The purpose of this study was to assess the feasibility and utility of image fusion (Easy-TIPS) obtained from pre-procedure CT angiography and per-procedure real-time fluoroscopy for portal vein puncture during transjugular intrahepatic portosystemic shunt (TIPS) placement. Eighteen patients (15 men, 3 women) with a mean age of 63 years (range: 48-81 years; median age, 65 years) were included in the study. All patients underwent TIPS placement by two groups of radiologists (one group with radiologists of an experience<3 years and one with an experience≥3 years) using fusion imaging obtained from three-dimensional computed tomography angiography of the portal vein and real-time fluoroscopic images of the portal vein. Image fusion was used to guide the portal vein puncture during TIPS placement. At the end of the procedure, the interventional radiologists evaluated the utility of fusion imaging for portal vein puncture during TIPS placement. Mismatch between three-dimensional computed tomography angiography and real-time fluoroscopic images of the portal vein on image fusion was quantitatively analyzed. Posttreatment CT time, number of the puncture attempts, total radiation exposure and radiation from the retrograde portography were also recorded. Image fusion was considered useful for portal vein puncture in 13/18 TIPS procedures (72%). The mean posttreatment time to obtain fusion images was 16.4minutes. 3D volume rendered CT angiography images was strictly superimposed on direct portography in 10/18 procedures (56%). The mismatch mean value was 0.69cm in height and 0.28cm laterally. A mean number of 4.6 portal vein puncture attempts was made. Eight patients required less than three attempts. The mean radiation dose from retrograde portography was 421.2dGy.cm 2 , corresponding to a mean additional exposure of 19%. Fusion imaging resulting from image fusion from pre-procedural CT angiography is feasible, safe and makes portal puncture easier during TIPS placement. Copyright © 2016 Editions françaises de radiologie. Published by Elsevier Masson SAS. All rights reserved.
Image Fusion During Vascular and Nonvascular Image-Guided Procedures☆

PubMed Central

Abi-Jaoudeh, Nadine; Kobeiter, Hicham; Xu, Sheng; Wood, Bradford J.

2013-01-01

Image fusion may be useful in any procedure where previous imaging such as positron emission tomography, magnetic resonance imaging, or contrast-enhanced computed tomography (CT) defines information that is referenced to the procedural imaging, to the needle or catheter, or to an ultrasound transducer. Fusion of prior and intraoperative imaging provides real-time feedback on tumor location or margin, metabolic activity, device location, or vessel location. Multimodality image fusion in interventional radiology was initially introduced for biopsies and ablations, especially for lesions only seen on arterial phase CT, magnetic resonance imaging, or positron emission tomography/CT but has more recently been applied to other vascular and nonvascular procedures. Two different types of platforms are commonly used for image fusion and navigation: (1) electromagnetic tracking and (2) cone-beam CT. Both technologies would be reviewed as well as their strengths and weaknesses, indications, when to use one vs the other, tips and guidance to streamline use, and early evidence defining clinical benefits of these rapidly evolving, commercially available and emerging techniques. PMID:23993079
Information recovery through image sequence fusion under wavelet transformation

NASA Astrophysics Data System (ADS)

He, Qiang

2010-04-01

Remote sensing is widely applied to provide information of areas with limited ground access with applications such as to assess the destruction from natural disasters and to plan relief and recovery operations. However, the data collection of aerial digital images is constrained by bad weather, atmospheric conditions, and unstable camera or camcorder. Therefore, how to recover the information from the low-quality remote sensing images and how to enhance the image quality becomes very important for many visual understanding tasks, such like feature detection, object segmentation, and object recognition. The quality of remote sensing imagery can be improved through meaningful combination of the employed images captured from different sensors or from different conditions through information fusion. Here we particularly address information fusion to remote sensing images under multi-resolution analysis in the employed image sequences. The image fusion is to recover complete information by integrating multiple images captured from the same scene. Through image fusion, a new image with high-resolution or more perceptive for human and machine is created from a time series of low-quality images based on image registration between different video frames.
Surgical planning and manual image fusion based on 3D model facilitate laparoscopic partial nephrectomy for intrarenal tumors.

PubMed

Chen, Yuanbo; Li, Hulin; Wu, Dingtao; Bi, Keming; Liu, Chunxiao

2014-12-01

Construction of three-dimensional (3D) model of renal tumor facilitated surgical planning and imaging guidance of manual image fusion in laparoscopic partial nephrectomy (LPN) for intrarenal tumors. Fifteen patients with intrarenal tumors underwent LPN between January and December 2012. Computed tomography-based reconstruction of the 3D models of renal tumors was performed using Mimics 12.1 software. Surgical planning was performed through morphometry and multi-angle visual views of the tumor model. Two-step manual image fusion superimposed 3D model images onto 2D laparoscopic images. The image fusion was verified by intraoperative ultrasound. Imaging-guided laparoscopic hilar clamping and tumor excision was performed. Manual fusion time, patient demographics, surgical details, and postoperative treatment parameters were analyzed. The reconstructed 3D tumor models accurately represented the patient's physiological anatomical landmarks. The surgical planning markers were marked successfully. Manual image fusion was flexible and feasible with fusion time of 6 min (5-7 min). All surgeries were completed laparoscopically. The median tumor excision time was 5.4 min (3.5-10 min), whereas the median warm ischemia time was 25.5 min (16-32 min). Twelve patients (80 %) demonstrated renal cell carcinoma on final pathology, and all surgical margins were negative. No tumor recurrence was detected after a media follow-up of 1 year (3-15 months). The surgical planning and two-step manual image fusion based on 3D model of renal tumor facilitated visible-imaging-guided tumor resection with negative margin in LPN for intrarenal tumor. It is promising and moves us one step closer to imaging-guided surgery.
CTA with fluoroscopy image fusion guidance in endovascular complex aortic aneurysm repair.

PubMed

Sailer, A M; de Haan, M W; Peppelenbosch, A G; Jacobs, M J; Wildberger, J E; Schurink, G W H

2014-04-01

To evaluate the effect of intraoperative guidance by means of live fluoroscopy image fusion with computed tomography angiography (CTA) on iodinated contrast material volume, procedure time, and fluoroscopy time in endovascular thoraco-abdominal aortic repair. CTA with fluoroscopy image fusion road-mapping was prospectively evaluated in patients with complex aortic aneurysms who underwent fenestrated and/or branched endovascular repair (FEVAR/BEVAR). Total iodinated contrast material volume, overall procedure time, and fluoroscopy time were compared between the fusion group (n = 31) and case controls (n = 31). Reasons for potential fusion image inaccuracy were analyzed. Fusion imaging was feasible in all patients. Fusion image road-mapping was used for navigation and positioning of the devices and catheter guidance during access to target vessels. Iodinated contrast material volume and procedure time were significantly lower in the fusion group than in case controls (159 mL [95% CI 132-186 mL] vs. 199 mL [95% CI 170-229 mL], p = .037 and 5.2 hours [95% CI 4.5-5.9 hours] vs. 6.3 hours (95% CI 5.4-7.2 hours), p = .022). No significant differences in fluoroscopy time were observed (p = .38). Respiration-related vessel displacement, vessel elongation, and displacement by stiff devices as well as patient movement were identified as reasons for fusion image inaccuracy. Image fusion guidance provides added value in complex endovascular interventions. The technology significantly reduces iodinated contrast material dose and procedure time. Copyright © 2014 European Society for Vascular Surgery. Published by Elsevier Ltd. All rights reserved.
Energy-resolved neutron imaging for inertial confinement fusion

NASA Astrophysics Data System (ADS)

Moran, M. J.; Haan, S. W.; Hatchett, S. P.; Izumi, N.; Koch, J. A.; Lerche, R. A.; Phillips, T. W.

2003-03-01

The success of the National Ignition Facility program will depend on diagnostic measurements which study the performance of inertial confinement fusion (ICF) experiments. Neutron yield, fusion-burn time history, and images are examples of important diagnostics. Neutron and x-ray images will record the geometries of compressed targets during the fusion-burn process. Such images provide a critical test of the accuracy of numerical modeling of ICF experiments. They also can provide valuable information in cases where experiments produce unexpected results. Although x-ray and neutron images provide similar data, they do have significant differences. X-ray images represent the distribution of high-temperature regions where fusion occurs, while neutron images directly reveal the spatial distribution of fusion-neutron emission. X-ray imaging has the advantage of a relatively straightforward path to the imaging system design. Neutron imaging, by using energy-resolved detection, offers the intriguing advantage of being able to provide independent images of burning and nonburning regions of the nuclear fuel. The usefulness of energy-resolved neutron imaging depends on both the information content of the data and on the quality of the data that can be recorded. The information content will relate to the characteristic neutron spectra that are associated with emission from different regions of the source. Numerical modeling of ICF fusion burn will be required to interpret the corresponding energy-dependent images. The exercise will be useful only if the images can be recorded with sufficient definition to reveal the spatial and energy-dependent features of interest. Several options are being evaluated with respect to the feasibility of providing the desired simultaneous spatial and energy resolution.
Real-time FDG PET Guidance during Biopsies and Radiofrequency Ablation Using Multimodality Fusion with Electromagnetic Navigation

PubMed Central

Kadoury, Samuel; Abi-Jaoudeh, Nadine; Levy, Elliot B.; Maass-Moreno, Roberto; Krücker, Jochen; Dalal, Sandeep; Xu, Sheng; Glossop, Neil; Wood, Bradford J.

2011-01-01

Purpose: To assess the feasibility of combined electromagnetic device tracking and computed tomography (CT)/ultrasonography (US)/fluorine 18 fluorodeoxyglucose (FDG) positron emission tomography (PET) fusion for real-time feedback during percutaneous and intraoperative biopsies and hepatic radiofrequency (RF) ablation. Materials and Methods: In this HIPAA-compliant, institutional review board–approved prospective study with written informed consent, 25 patients (17 men, eight women) underwent 33 percutaneous and three intraoperative biopsies of 36 FDG-avid targets between November 2007 and August 2010. One patient underwent biopsy and RF ablation of an FDG-avid hepatic focus. Targets demonstrated heterogeneous FDG uptake or were not well seen or were totally inapparent at conventional imaging. Preprocedural FDG PET scans were rigidly registered through a semiautomatic method to intraprocedural CT scans. Coaxial biopsy needle introducer tips and RF ablation electrode guider needle tips containing electromagnetic sensor coils were spatially tracked through an electromagnetic field generator. Real-time US scans were registered through a fiducial-based method, allowing US scans to be fused with intraprocedural CT and preacquired FDG PET scans. A visual display of US/CT image fusion with overlaid coregistered FDG PET targets was used for guidance; navigation software enabled real-time biopsy needle and needle electrode navigation and feedback. Results: Successful fusion of real-time US to coregistered CT and FDG PET scans was achieved in all patients. Thirty-one of 36 biopsies were diagnostic (malignancy in 18 cases, benign processes in 13 cases). RF ablation resulted in resolution of targeted FDG avidity, with no local treatment failure during short follow-up (56 days). Conclusion: Combined electromagnetic device tracking and image fusion with real-time feedback may facilitate biopsies and ablations of focal FDG PET abnormalities that would be challenging with conventional image guidance. © RSNA, 2011 Supplemental material: http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.11101985/-/DC1 PMID:21734159
Multi-atlas based segmentation using probabilistic label fusion with adaptive weighting of image similarity measures.

PubMed

Sjöberg, C; Ahnesjö, A

2013-06-01

Label fusion multi-atlas approaches for image segmentation can give better segmentation results than single atlas methods. We present a multi-atlas label fusion strategy based on probabilistic weighting of distance maps. Relationships between image similarities and segmentation similarities are estimated in a learning phase and used to derive fusion weights that are proportional to the probability for each atlas to improve the segmentation result. The method was tested using a leave-one-out strategy on a database of 21 pre-segmented prostate patients for different image registrations combined with different image similarity scorings. The probabilistic weighting yields results that are equal or better compared to both fusion with equal weights and results using the STAPLE algorithm. Results from the experiments demonstrate that label fusion by weighted distance maps is feasible, and that probabilistic weighted fusion improves segmentation quality more the stronger the individual atlas segmentation quality depends on the corresponding registered image similarity. The regions used for evaluation of the image similarity measures were found to be more important than the choice of similarity measure. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
The Research on Dryland Crop Classification Based on the Fusion of SENTINEL-1A SAR and Optical Images

NASA Astrophysics Data System (ADS)

Liu, F.; Chen, T.; He, J.; Wen, Q.; Yu, F.; Gu, X.; Wang, Z.

2018-04-01

In recent years, the quick upgrading and improvement of SAR sensors provide beneficial complements for the traditional optical remote sensing in the aspects of theory, technology and data. In this paper, Sentinel-1A SAR data and GF-1 optical data were selected for image fusion, and more emphases were put on the dryland crop classification under a complex crop planting structure, regarding corn and cotton as the research objects. Considering the differences among various data fusion methods, the principal component analysis (PCA), Gram-Schmidt (GS), Brovey and wavelet transform (WT) methods were compared with each other, and the GS and Brovey methods were proved to be more applicable in the study area. Then, the classification was conducted based on the object-oriented technique process. And for the GS, Brovey fusion images and GF-1 optical image, the nearest neighbour algorithm was adopted to realize the supervised classification with the same training samples. Based on the sample plots in the study area, the accuracy assessment was conducted subsequently. The values of overall accuracy and kappa coefficient of fusion images were all higher than those of GF-1 optical image, and GS method performed better than Brovey method. In particular, the overall accuracy of GS fusion image was 79.8 %, and the Kappa coefficient was 0.644. Thus, the results showed that GS and Brovey fusion images were superior to optical images for dryland crop classification. This study suggests that the fusion of SAR and optical images is reliable for dryland crop classification under a complex crop planting structure.
Fusion imaging of contrast-enhanced ultrasound and contrast-enhanced CT or MRI before radiofrequency ablation for liver cancers.

PubMed

Bo, Xiao-Wan; Xu, Hui-Xiong; Wang, Dan; Guo, Le-Hang; Sun, Li-Ping; Li, Xiao-Long; Zhao, Chong-Ke; He, Ya-Ping; Liu, Bo-Ji; Li, Dan-Dan; Zhang, Kun

2016-11-01

To investigate the usefulness of fusion imaging of contrast-enhanced ultrasound (CEUS) and CECT/CEMRI before percutaneous ultrasound-guided radiofrequency ablation (RFA) for liver cancers. 45 consecutive patients with 70 liver lesions were included between March 2013 and October 2015, and all the lesions were identified on CEMRI/CECT prior to inclusion in the study. Planning ultrasound for percutaneous RFA was performed using conventional ultrasound, ultrasound-CECT/CEMRI and CEUS and CECT/CEMRI fusion imaging during the same session. The numbers of the conspicuous lesions on ultrasound and fusion imaging were recorded. RFA was performed according to the results of fusion imaging. Complete response (CR) rate was calculated and the complications were recorded. On conventional ultrasound, 25 (35.7%) of the 70 lesions were conspicuous, whereas 45 (64.3%) were inconspicuous. Ultrasound-CECT/CEMRI fusion imaging detected additional 24 lesions thus increased the number of the conspicuous lesions to 49 (70.0%) (70.0% vs 35.7%; p < 0.001 in comparison with conventional ultrasound). With the use of CEUS and CECT/CEMRI fusion imaging, the number of the conspicuous lesions further increased to 67 (95.7%, 67/70) (95.7% vs 70.0%, 95.7% vs 35.7%; both p < 0.001 in comparison with ultrasound and ultrasound-CECT/CEMRI fusion imaging, respectively). With the assistance of CEUS and CECT/CEMRI fusion imaging, the confidence level of the operator for performing RFA improved significantly with regard to visualization of the target lesions (p = 0.001). The CR rate for RFA was 97.0% (64/66) in accordance to the CECT/CEMRI results 1 month later. No procedure-related deaths and major complications occurred during and after RFA. Fusion of CEUS and CECT/CEMRI improves the visualization of those inconspicuous lesions on conventional ultrasound. It also facilitates improvement in the RFA operators' confidence and CR of RFA. Advances in knowledge: CEUS and CECT/CEMRI fusion imaging is better than both conventional ultrasound and ultrasound-CECT/CEMRI fusion imaging for lesion visualization and improves the operator confidence, thus it should be recommended to be used as a routine in ultrasound-guided percutaneous RFA procedures for liver cancer.
Fusion imaging of contrast-enhanced ultrasound and contrast-enhanced CT or MRI before radiofrequency ablation for liver cancers

PubMed Central

Bo, Xiao-Wan; Wang, Dan; Guo, Le-Hang; Sun, Li-Ping; Li, Xiao-Long; Zhao, Chong-Ke; He, Ya-Ping; Liu, Bo-Ji; Li, Dan-Dan; Zhang, Kun

2016-01-01

Objective: To investigate the usefulness of fusion imaging of contrast-enhanced ultrasound (CEUS) and CECT/CEMRI before percutaneous ultrasound-guided radiofrequency ablation (RFA) for liver cancers. Methods: 45 consecutive patients with 70 liver lesions were included between March 2013 and October 2015, and all the lesions were identified on CEMRI/CECT prior to inclusion in the study. Planning ultrasound for percutaneous RFA was performed using conventional ultrasound, ultrasound-CECT/CEMRI and CEUS and CECT/CEMRI fusion imaging during the same session. The numbers of the conspicuous lesions on ultrasound and fusion imaging were recorded. RFA was performed according to the results of fusion imaging. Complete response (CR) rate was calculated and the complications were recorded. Results: On conventional ultrasound, 25 (35.7%) of the 70 lesions were conspicuous, whereas 45 (64.3%) were inconspicuous. Ultrasound-CECT/CEMRI fusion imaging detected additional 24 lesions thus increased the number of the conspicuous lesions to 49 (70.0%) (70.0% vs 35.7%; p < 0.001 in comparison with conventional ultrasound). With the use of CEUS and CECT/CEMRI fusion imaging, the number of the conspicuous lesions further increased to 67 (95.7%, 67/70) (95.7% vs 70.0%, 95.7% vs 35.7%; both p < 0.001 in comparison with ultrasound and ultrasound-CECT/CEMRI fusion imaging, respectively). With the assistance of CEUS and CECT/CEMRI fusion imaging, the confidence level of the operator for performing RFA improved significantly with regard to visualization of the target lesions (p = 0.001). The CR rate for RFA was 97.0% (64/66) in accordance to the CECT/CEMRI results 1 month later. No procedure-related deaths and major complications occurred during and after RFA. Conclusion: Fusion of CEUS and CECT/CEMRI improves the visualization of those inconspicuous lesions on conventional ultrasound. It also facilitates improvement in the RFA operators' confidence and CR of RFA. Advances in knowledge: CEUS and CECT/CEMRI fusion imaging is better than both conventional ultrasound and ultrasound-CECT/CEMRI fusion imaging for lesion visualization and improves the operator confidence, thus it should be recommended to be used as a routine in ultrasound-guided percutaneous RFA procedures for liver cancer. PMID:27626506

Detecting fiducials affected by trombone delay in ARC and the main laser alignment at the National Ignition Facility

NASA Astrophysics Data System (ADS)

Awwal, Abdul A. S.; Bliss, Erlan S.; Miller Kamm, Victoria; Leach, Richard R.; Roberts, Randy; Rushford, Michael C.; Lowe-Webb, Roger; Wilhelmsen, Karl

2015-09-01

Four of the 192 beams of the National Ignition Facility (NIF) are currently being diverted into the Advanced Radiographic Capability (ARC) system to generate a sequence of short (1-50 picoseconds) 1053 nm laser pulses. When focused onto high Z wires in vacuum, these pulses create high energy x-ray pulses capable of penetrating the dense, imploding fusion fuel plasma during ignition scale experiments. The transmitted x-rays imaged with x-ray diagnostics can create movie radiographs that are expected to provide unprecedented insight into the implosion dynamics. The resulting images will serve as a diagnostic for tuning the experimental parameters towards successful fusion reactions. Beam delays introduced into the ARC pulses via independent, free-space optical trombones create the desired x-ray image sequence, or movie. However, these beam delays cause optical distortion of various alignment fiducials viewed by alignment sensors in the NIF and ARC beamlines. This work describes how the position of circular alignment fiducials is estimated in the presence of distortion.
Heterogeneous Vision Data Fusion for Independently Moving Cameras

DTIC Science & Technology

2010-03-01

target detection , tracking , and identification over a large terrain. The goal of the project is to investigate and evaluate the existing image...fusion algorithms, develop new real-time algorithms for Category-II image fusion, and apply these algorithms in moving target detection and tracking . The...moving target detection and classification. 15. SUBJECT TERMS Image Fusion, Target Detection , Moving Cameras, IR Camera, EO Camera 16. SECURITY
Evaluation of MRI-US Fusion Technology in Sports-Related Musculoskeletal Injuries.

PubMed

Wong-On, Manuel; Til-Pérez, Lluís; Balius, Ramón

2015-06-01

A combination of magnetic resonance imaging (MRI) with real-time high-resolution ultrasound (US) known as fusion imaging may improve visualization of musculoskeletal (MSK) sports medicine injuries. The aim of this study was to evaluate the applicability of MRI-US fusion technology in MSK sports medicine. This study was conducted by the medical services of the FC Barcelona. The participants included volunteers and referred athletes with symptomatic and asymptomatic MSK injuries. All cases underwent MRI which was loaded into the US system for manual registration on the live US image and fusion imaging examination. After every test, an evaluation form was completed in terms of advantages, disadvantages, and anatomic fusion landmarks. From November 2014 to March 2015, we evaluated 20 subjects who underwent fusion imaging, 5 non-injured volunteers and 15 injured athletes, 11 symptomatic and 4 asymptomatic, age range 16-50 years, mean 22. We describe some of the anatomic landmarks used to guide fusion in different regions. This technology allowed us to examine muscle and tendon injuries simultaneously in US and MRI, and the correlation of both techniques, especially low-grade muscular injuries. This has also helped compensate for the limited field of view with US. It improves spatial orientation of cartilage, labrum and meniscal injuries. However, a high-quality MRI image is essential in achieving an adequate fusion image, and 3D sequences need to be added in MRI protocols to improve navigation. The combination of real-time MRI and US image fusion and navigation is relatively easy to perform and is helping to improve understanding of MSK injuries. However, it requires specific skills in MSK imaging and still needs further research in sports-related injuries. Toshiba Medical Systems Corporation.
An automatic fuzzy-based multi-temporal brain digital subtraction angiography image fusion algorithm using curvelet transform and content selection strategy.

PubMed

Momeni, Saba; Pourghassem, Hossein

2014-08-01

Recently image fusion has prominent role in medical image processing and is useful to diagnose and treat many diseases. Digital subtraction angiography is one of the most applicable imaging to diagnose brain vascular diseases and radiosurgery of brain. This paper proposes an automatic fuzzy-based multi-temporal fusion algorithm for 2-D digital subtraction angiography images. In this algorithm, for blood vessel map extraction, the valuable frames of brain angiography video are automatically determined to form the digital subtraction angiography images based on a novel definition of vessel dispersion generated by injected contrast material. Our proposed fusion scheme contains different fusion methods for high and low frequency contents based on the coefficient characteristic of wrapping second generation of curvelet transform and a novel content selection strategy. Our proposed content selection strategy is defined based on sample correlation of the curvelet transform coefficients. In our proposed fuzzy-based fusion scheme, the selection of curvelet coefficients are optimized by applying weighted averaging and maximum selection rules for the high frequency coefficients. For low frequency coefficients, the maximum selection rule based on local energy criterion is applied to better visual perception. Our proposed fusion algorithm is evaluated on a perfect brain angiography image dataset consisting of one hundred 2-D internal carotid rotational angiography videos. The obtained results demonstrate the effectiveness and efficiency of our proposed fusion algorithm in comparison with common and basic fusion algorithms.
Quantitative image fusion in infrared radiometry

NASA Astrophysics Data System (ADS)

Romm, Iliya; Cukurel, Beni

2018-05-01

Towards high-accuracy infrared radiance estimates, measurement practices and processing techniques aimed to achieve quantitative image fusion using a set of multi-exposure images of a static scene are reviewed. The conventional non-uniformity correction technique is extended, as the original is incompatible with quantitative fusion. Recognizing the inherent limitations of even the extended non-uniformity correction, an alternative measurement methodology, which relies on estimates of the detector bias using self-calibration, is developed. Combining data from multi-exposure images, two novel image fusion techniques that ultimately provide high tonal fidelity of a photoquantity are considered: ‘subtract-then-fuse’, which conducts image subtraction in the camera output domain and partially negates the bias frame contribution common to both the dark and scene frames; and ‘fuse-then-subtract’, which reconstructs the bias frame explicitly and conducts image fusion independently for the dark and the scene frames, followed by subtraction in the photoquantity domain. The performances of the different techniques are evaluated for various synthetic and experimental data, identifying the factors contributing to potential degradation of the image quality. The findings reflect the superiority of the ‘fuse-then-subtract’ approach, conducting image fusion via per-pixel nonlinear weighted least squares optimization.
Spiking Cortical Model Based Multimodal Medical Image Fusion by Combining Entropy Information with Weber Local Descriptor

PubMed Central

Zhang, Xuming; Ren, Jinxia; Huang, Zhiwen; Zhu, Fei

2016-01-01

Multimodal medical image fusion (MIF) plays an important role in clinical diagnosis and therapy. Existing MIF methods tend to introduce artifacts, lead to loss of image details or produce low-contrast fused images. To address these problems, a novel spiking cortical model (SCM) based MIF method has been proposed in this paper. The proposed method can generate high-quality fused images using the weighting fusion strategy based on the firing times of the SCM. In the weighting fusion scheme, the weight is determined by combining the entropy information of pulse outputs of the SCM with the Weber local descriptor operating on the firing mapping images produced from the pulse outputs. The extensive experiments on multimodal medical images show that compared with the numerous state-of-the-art MIF methods, the proposed method can preserve image details very well and avoid the introduction of artifacts effectively, and thus it significantly improves the quality of fused images in terms of human vision and objective evaluation criteria such as mutual information, edge preservation index, structural similarity based metric, fusion quality index, fusion similarity metric and standard deviation. PMID:27649190
Spiking Cortical Model Based Multimodal Medical Image Fusion by Combining Entropy Information with Weber Local Descriptor.

PubMed

Zhang, Xuming; Ren, Jinxia; Huang, Zhiwen; Zhu, Fei

2016-09-15

Multimodal medical image fusion (MIF) plays an important role in clinical diagnosis and therapy. Existing MIF methods tend to introduce artifacts, lead to loss of image details or produce low-contrast fused images. To address these problems, a novel spiking cortical model (SCM) based MIF method has been proposed in this paper. The proposed method can generate high-quality fused images using the weighting fusion strategy based on the firing times of the SCM. In the weighting fusion scheme, the weight is determined by combining the entropy information of pulse outputs of the SCM with the Weber local descriptor operating on the firing mapping images produced from the pulse outputs. The extensive experiments on multimodal medical images show that compared with the numerous state-of-the-art MIF methods, the proposed method can preserve image details very well and avoid the introduction of artifacts effectively, and thus it significantly improves the quality of fused images in terms of human vision and objective evaluation criteria such as mutual information, edge preservation index, structural similarity based metric, fusion quality index, fusion similarity metric and standard deviation.
Time efficient Gabor fused master slave optical coherence tomography

NASA Astrophysics Data System (ADS)

Cernat, Ramona; Bradu, Adrian; Rivet, Sylvain; Podoleanu, Adrian

2018-02-01

In this paper the benefits in terms of operation time that Master/Slave (MS) implementation of optical coherence tomography can bring in comparison to Gabor fused (GF) employing conventional fast Fourier transform based OCT are presented. The Gabor Fusion/Master Slave Optical Coherence Tomography architecture proposed here does not need any data stitching. Instead, a subset of en-face images is produced for each focus position inside the sample to be imaged, using a reduced number of theoretically inferred Master masks. These en-face images are then assembled into a final volume. When the channelled spectra are digitized into 1024 sampling points, and more than 4 focus positions are required to produce the final volume, the Master Slave implementation of the instrument is faster than the conventional fast Fourier transform based procedure.
Landcover classification in MRF context using Dempster-Shafer fusion for multisensor imagery.

PubMed

Sarkar, Anjan; Banerjee, Anjan; Banerjee, Nilanjan; Brahma, Siddhartha; Kartikeyan, B; Chakraborty, Manab; Majumder, K L

2005-05-01

This work deals with multisensor data fusion to obtain landcover classification. The role of feature-level fusion using the Dempster-Shafer rule and that of data-level fusion in the MRF context is studied in this paper to obtain an optimally segmented image. Subsequently, segments are validated and classification accuracy for the test data is evaluated. Two examples of data fusion of optical images and a synthetic aperture radar image are presented, each set having been acquired on different dates. Classification accuracies of the technique proposed are compared with those of some recent techniques in literature for the same image data.
Taxonomy of multi-focal nematode image stacks by a CNN based image fusion approach.

PubMed

Liu, Min; Wang, Xueping; Zhang, Hongzhong

2018-03-01

In the biomedical field, digital multi-focal images are very important for documentation and communication of specimen data, because the morphological information for a transparent specimen can be captured in form of a stack of high-quality images. Given biomedical image stacks containing multi-focal images, how to efficiently extract effective features from all layers to classify the image stacks is still an open question. We present to use a deep convolutional neural network (CNN) image fusion based multilinear approach for the taxonomy of multi-focal image stacks. A deep CNN based image fusion technique is used to combine relevant information of multi-focal images within a given image stack into a single image, which is more informative and complete than any single image in the given stack. Besides, multi-focal images within a stack are fused along 3 orthogonal directions, and multiple features extracted from the fused images along different directions are combined by canonical correlation analysis (CCA). Because multi-focal image stacks represent the effect of different factors - texture, shape, different instances within the same class and different classes of objects, we embed the deep CNN based image fusion method within a multilinear framework to propose an image fusion based multilinear classifier. The experimental results on nematode multi-focal image stacks demonstrated that the deep CNN image fusion based multilinear classifier can reach a higher classification rate (95.7%) than that by the previous multilinear based approach (88.7%), even we only use the texture feature instead of the combination of texture and shape features as in the previous work. The proposed deep CNN image fusion based multilinear approach shows great potential in building an automated nematode taxonomy system for nematologists. It is effective to classify multi-focal image stacks. Copyright © 2018 Elsevier B.V. All rights reserved.
Image fusion

NASA Technical Reports Server (NTRS)

Pavel, M.

1993-01-01

The topics covered include the following: a system overview of the basic components of a system designed to improve the ability of a pilot to fly through low-visibility conditions such as fog; the role of visual sciences; fusion issues; sensor characterization; sources of information; image processing; and image fusion.
A Standard Mammography Unit - Standard 3D Ultrasound Probe Fusion Prototype: First Results.

PubMed

Schulz-Wendtland, Rüdiger; Jud, Sebastian M; Fasching, Peter A; Hartmann, Arndt; Radicke, Marcus; Rauh, Claudia; Uder, Michael; Wunderle, Marius; Gass, Paul; Langemann, Hanna; Beckmann, Matthias W; Emons, Julius

2017-06-01

The combination of different imaging modalities through the use of fusion devices promises significant diagnostic improvement for breast pathology. The aim of this study was to evaluate image quality and clinical feasibility of a prototype fusion device (fusion prototype) constructed from a standard tomosynthesis mammography unit and a standard 3D ultrasound probe using a new method of breast compression. Imaging was performed on 5 mastectomy specimens from patients with confirmed DCIS or invasive carcinoma (BI-RADS ™ 6). For the preclinical fusion prototype an ABVS system ultrasound probe from an Acuson S2000 was integrated into a MAMMOMAT Inspiration (both Siemens Healthcare Ltd) and, with the aid of a newly developed compression plate, digital mammogram and automated 3D ultrasound images were obtained. The quality of digital mammogram images produced by the fusion prototype was comparable to those produced using conventional compression. The newly developed compression plate did not influence the applied x-ray dose. The method was not more labour intensive or time-consuming than conventional mammography. From the technical perspective, fusion of the two modalities was achievable. In this study, using only a few mastectomy specimens, the fusion of an automated 3D ultrasound machine with a standard mammography unit delivered images of comparable quality to conventional mammography. The device allows simultaneous ultrasound - the second important imaging modality in complementary breast diagnostics - without increasing examination time or requiring additional staff.
Fusion method of SAR and optical images for urban object extraction

NASA Astrophysics Data System (ADS)

Jia, Yonghong; Blum, Rick S.; Li, Fangfang

2007-11-01

A new image fusion method of SAR, Panchromatic (Pan) and multispectral (MS) data is proposed. First of all, SAR texture is extracted by ratioing the despeckled SAR image to its low pass approximation, and is used to modulate high pass details extracted from the available Pan image by means of the á trous wavelet decomposition. Then, high pass details modulated with the texture is applied to obtain the fusion product by HPFM (High pass Filter-based Modulation) fusion method. A set of image data including co-registered Landsat TM, ENVISAT SAR and SPOT Pan is used for the experiment. The results demonstrate accurate spectral preservation on vegetated regions, bare soil, and also on textured areas (buildings and road network) where SAR texture information enhances the fusion product, and the proposed approach is effective for image interpret and classification.
Improved medical image fusion based on cascaded PCA and shift invariant wavelet transforms.

PubMed

Reena Benjamin, J; Jayasree, T

2018-02-01

In the medical field, radiologists need more informative and high-quality medical images to diagnose diseases. Image fusion plays a vital role in the field of biomedical image analysis. It aims to integrate the complementary information from multimodal images, producing a new composite image which is expected to be more informative for visual perception than any of the individual input images. The main objective of this paper is to improve the information, to preserve the edges and to enhance the quality of the fused image using cascaded principal component analysis (PCA) and shift invariant wavelet transforms. A novel image fusion technique based on cascaded PCA and shift invariant wavelet transforms is proposed in this paper. PCA in spatial domain extracts relevant information from the large dataset based on eigenvalue decomposition, and the wavelet transform operating in the complex domain with shift invariant properties brings out more directional and phase details of the image. The significance of maximum fusion rule applied in dual-tree complex wavelet transform domain enhances the average information and morphological details. The input images of the human brain of two different modalities (MRI and CT) are collected from whole brain atlas data distributed by Harvard University. Both MRI and CT images are fused using cascaded PCA and shift invariant wavelet transform method. The proposed method is evaluated based on three main key factors, namely structure preservation, edge preservation, contrast preservation. The experimental results and comparison with other existing fusion methods show the superior performance of the proposed image fusion framework in terms of visual and quantitative evaluations. In this paper, a complex wavelet-based image fusion has been discussed. The experimental results demonstrate that the proposed method enhances the directional features as well as fine edge details. Also, it reduces the redundant details, artifacts, distortions.
Feasibility of three-dimensional magnetic resonance angiography-fluoroscopy image fusion technique in guiding complex endovascular aortic procedures in patients with renal insufficiency.

PubMed

Schwein, Adeline; Chinnadurai, Ponraj; Shah, Dipan J; Lumsden, Alan B; Bechara, Carlos F; Bismuth, Jean

2017-05-01

Three-dimensional image fusion of preoperative computed tomography (CT) angiography with fluoroscopy using intraoperative noncontrast cone-beam CT (CBCT) has been shown to improve endovascular procedures by reducing procedure length, radiation dose, and contrast media volume. However, patients with a contraindication to CT angiography (renal insufficiency, iodinated contrast allergy) may not benefit from this image fusion technique. The primary objective of this study was to evaluate the feasibility of magnetic resonance angiography (MRA) and fluoroscopy image fusion using noncontrast CBCT as a guidance tool during complex endovascular aortic procedures, especially in patients with renal insufficiency. All endovascular aortic procedures done under MRA image fusion guidance at a single-center were retrospectively reviewed. The patients had moderate to severe renal insufficiency and underwent diagnostic contrast-enhanced magnetic resonance imaging after gadolinium or ferumoxytol injection. Relevant vascular landmarks electronically marked in MRA images were overlaid on real-time two-dimensional fluoroscopy for image guidance, after image fusion with noncontrast intraoperative CBCT. Technical success, time for image registration, procedure time, fluoroscopy time, number of digital subtraction angiography (DSA) acquisitions before stent deployment or vessel catheterization, and renal function before and after the procedure were recorded. The image fusion accuracy was qualitatively evaluated on a binary scale by three physicians after review of image data showing virtual landmarks from MRA on fluoroscopy. Between November 2012 and March 2016, 10 patients underwent endovascular procedures for aortoiliac aneurysmal disease or aortic dissection using MRA image fusion guidance. All procedures were technically successful. A paired t-test analysis showed no difference between preimaging and postoperative renal function (P = .6). The mean time required for MRA-CBCT image fusion was 4:09 ± 01:31 min:sec. Total fluoroscopy time was 20.1 ± 6.9 minutes. Five of 10 patients (50%) underwent stent graft deployment without any predeployment DSA acquisition. Three of six vessels (50%) were cannulated under image fusion guidance without any precannulation DSA runs, and the remaining vessels were cannulated after one planning DSA acquisition. Qualitative evaluation showed 14 of 22 virtual landmarks (63.6%) from MRA overlaid on fluoroscopy were completely accurate, without the need for adjustment. Five of eight incorrect virtual landmarks (iliac and visceral arteries) resulted from vessel deformation caused by endovascular devices. Ferumoxytol or gadolinium-enhanced MRA imaging and image fusion with fluoroscopy using noncontrast CBCT is feasible and allows patients with renal insufficiency to benefit from optimal guidance during complex endovascular aortic procedures, while preserving their residual renal function. Copyright © 2016 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.
Improved detection probability of low level light and infrared image fusion system

NASA Astrophysics Data System (ADS)

Luo, Yuxiang; Fu, Rongguo; Zhang, Junju; Wang, Wencong; Chang, Benkang

2018-02-01

Low level light(LLL) image contains rich information on environment details, but is easily affected by the weather. In the case of smoke, rain, cloud or fog, much target information will lose. Infrared image, which is from the radiation produced by the object itself, can be "active" to obtain the target information in the scene. However, the image contrast and resolution is bad, the ability of the acquisition of target details is very poor, and the imaging mode does not conform to the human visual habit. The fusion of LLL and infrared image can make up for the deficiency of each sensor and give play to the advantages of single sensor. At first, we show the hardware design of fusion circuit. Then, through the recognition probability calculation of the target(one person) and the background image(trees), we find that the trees detection probability of LLL image is higher than that of the infrared image, and the person detection probability of the infrared image is obviously higher than that of LLL image. The detection probability of fusion image for one person and trees is higher than that of single detector. Therefore, image fusion can significantly enlarge recognition probability and improve detection efficiency.
Improvement of ablative margins by the intraoperative use of CEUS-CT/MR image fusion in hepatocellular carcinoma.

PubMed

Li, Kai; Su, Zhong-Zhen; Xu, Er-Jiao; Ju, Jin-Xiu; Meng, Xiao-Chun; Zheng, Rong-Qin

2016-04-18

To assess whether intraoperative use of contrast-enhanced ultrasound (CEUS)-CT/MR image fusion can accurately evaluate ablative margin (AM) and guide supplementary ablation to improve AM after hepatocellular carcinoma (HCC) ablation. Ninety-eight patients with 126 HCCs designated to undergo thermal ablation treatment were enrolled in this prospective study. CEUS-CT/MR image fusion was performed intraoperatively to evaluate whether 5-mm AM was covered by the ablative area. If possible, supplementary ablation was applied at the site of inadequate AM. The CEUS image quality, the time used for CEUS-CT/MR image fusion and the success rate of image fusion were recorded. Local tumor progression (LTP) was observed during follow-up. Clinical factors including AM were examined to identify risk factors for LTP. The success rate of image fusion was 96.2% (126/131), and the duration required for image fusion was 4.9 ± 2.0 (3-13) min. The CEUS image quality was good in 36.1% (53/147) and medium in 63.9% (94/147) of the cases. By supplementary ablation, 21.8% (12/55) of lesions with inadequate AMs became adequate AMs. During follow-up, there were 5 LTPs in lesions with inadequate AMs and 1 LTP in lesions with adequate AMs. Multivariate analysis showed that AM was the only independent risk factor for LTP (hazard ratio, 9.167; 95% confidence interval, 1.070-78.571; p = 0.043). CEUS-CT/MR image fusion is feasible for intraoperative use and can serve as an accurate method to evaluate AMs and guide supplementary ablation to lower inadequate AMs.
Volume curtaining: a focus+context effect for multimodal volume visualization

NASA Astrophysics Data System (ADS)

Fairfield, Adam J.; Plasencia, Jonathan; Jang, Yun; Theodore, Nicholas; Crawford, Neil R.; Frakes, David H.; Maciejewski, Ross

2014-03-01

In surgical preparation, physicians will often utilize multimodal imaging scans to capture complementary information to improve diagnosis and to drive patient-specific treatment. These imaging scans may consist of data from magnetic resonance imaging (MR), computed tomography (CT), or other various sources. The challenge in using these different modalities is that the physician must mentally map the two modalities together during the diagnosis and planning phase. Furthermore, the different imaging modalities will be generated at various resolutions as well as slightly different orientations due to patient placement during scans. In this work, we present an interactive system for multimodal data fusion, analysis and visualization. Developed with partners from neurological clinics, this work discusses initial system requirements and physician feedback at the various stages of component development. Finally, we present a novel focus+context technique for the interactive exploration of coregistered multi-modal data.
Remote Sensing Image Fusion Method Based on Nonsubsampled Shearlet Transform and Sparse Representation

NASA Astrophysics Data System (ADS)

Moonon, Altan-Ulzii; Hu, Jianwen; Li, Shutao

2015-12-01

The remote sensing image fusion is an important preprocessing technique in remote sensing image processing. In this paper, a remote sensing image fusion method based on the nonsubsampled shearlet transform (NSST) with sparse representation (SR) is proposed. Firstly, the low resolution multispectral (MS) image is upsampled and color space is transformed from Red-Green-Blue (RGB) to Intensity-Hue-Saturation (IHS). Then, the high resolution panchromatic (PAN) image and intensity component of MS image are decomposed by NSST to high and low frequency coefficients. The low frequency coefficients of PAN and the intensity component are fused by the SR with the learned dictionary. The high frequency coefficients of intensity component and PAN image are fused by local energy based fusion rule. Finally, the fused result is obtained by performing inverse NSST and inverse IHS transform. The experimental results on IKONOS and QuickBird satellites demonstrate that the proposed method provides better spectral quality and superior spatial information in the fused image than other remote sensing image fusion methods both in visual effect and object evaluation.
Multimodality imaging of reporter gene expression using a novel fusion vector in living cells and animals

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gambhir, Sanjiv; Pritha, Ray

Novel double and triple fusion reporter gene constructs harboring distinct imagable reporter genes are provided, as well as applications for the use of such double and triple fusion constructs in living cells and in living animals using distinct imaging technologies.

Multimodality imaging of reporter gene expression using a novel fusion vector in living cells and animals

DOEpatents

Gambhir, Sanjiv; Pritha, Ray

2015-07-14

Novel double and triple fusion reporter gene constructs harboring distinct imagable reporter genes are provided, as well as applications for the use of such double and triple fusion constructs in living cells and in living animals using distinct imaging technologies.
Infrared and visible image fusion scheme based on NSCT and low-level visual features

NASA Astrophysics Data System (ADS)

Li, Huafeng; Qiu, Hongmei; Yu, Zhengtao; Zhang, Yafei

2016-05-01

Multi-scale transform (MST) is an efficient tool for image fusion. Recently, many fusion methods have been developed based on different MSTs, and they have shown potential application in many fields. In this paper, we propose an effective infrared and visible image fusion scheme in nonsubsampled contourlet transform (NSCT) domain, in which the NSCT is firstly employed to decompose each of the source images into a series of high frequency subbands and one low frequency subband. To improve the fusion performance we designed two new activity measures for fusion of the lowpass subbands and the highpass subbands. These measures are developed based on the fact that the human visual system (HVS) percept the image quality mainly according to its some low-level features. Then, the selection principles of different subbands are presented based on the corresponding activity measures. Finally, the merged subbands are constructed according to the selection principles, and the final fused image is produced by applying the inverse NSCT on these merged subbands. Experimental results demonstrate the effectiveness and superiority of the proposed method over the state-of-the-art fusion methods in terms of both visual effect and objective evaluation results.
Image fusion pitfalls for cranial radiosurgery.

PubMed

Jonker, Benjamin P

2013-01-01

Stereotactic radiosurgery requires imaging to define both the stereotactic space in which the treatment is delivered and the target itself. Image fusion is the process of using rotation and translation to bring a second image set into alignment with the first image set. This allows the potential concurrent use of multiple image sets to define the target and stereotactic space. While a single magnetic resonance imaging (MRI) sequence alone can be used for delineation of the target and fiducials, there may be significant advantages to using additional imaging sets including other MRI sequences, computed tomography (CT) scans, and advanced imaging sets such as catheter-based angiography, diffusor tension imaging-based fiber tracking and positon emission tomography in order to more accurately define the target and surrounding critical structures. Stereotactic space is usually defined by detection of fiducials on the stereotactic head frame or mask system. Unfortunately MRI sequences are susceptible to geometric distortion, whereas CT scans do not face this problem (although they have poorer resolution of the target in most cases). Thus image fusion can allow the definition of stereotactic space to proceed from the geometrically accurate CT images at the same time as using MRI to define the target. The use of image fusion is associated with risk of error introduced by inaccuracies of the fusion process, as well as workflow changes that if not properly accounted for can mislead the treating clinician. The purpose of this review is to describe the uses of image fusion in stereotactic radiosurgery as well as its potential pitfalls.
Evaluation of the ablation margin of hepatocellular carcinoma using CEUS-CT/MR image fusion in a phantom model and in patients.

PubMed

Li, Kai; Su, Zhongzhen; Xu, Erjiao; Huang, Qiannan; Zeng, Qingjing; Zheng, Rongqin

2017-01-19

To assess the accuracy of contrast-enhanced ultrasound (CEUS)-CT/MR image fusion in evaluating the radiofrequency ablative margin (AM) of hepatocellular carcinoma (HCC) based on a custom-made phantom model and in HCC patients. Twenty-four phantoms were randomly divided into a complete ablation group (n = 6) and an incomplete ablation group (n = 18). After radiofrequency ablation (RFA), the AM was evaluated using ultrasound (US)-CT image fusion, and the results were compared with the AM results that were directly measured in a gross specimen. CEUS-CT/MR image fusion and CT-CT / MR-MR image fusion were used to evaluate the AM in 37 tumors from 33 HCC patients who underwent RFA. The sensitivity, specificity, and accuracy of US-CT image fusion for evaluating AM in the phantom model were 93.8, 85.7 and 91.3%, respectively. The maximal thicknesses of the residual AM were 3.5 ± 2.0 mm and 3.2 ± 2.0 mm in the US-CT image fusion and gross specimen, respectively. No significant difference was observed between the US-CT image fusion and direct measurements of the AM of HCC. In the clinical study, the success rate of the AM evaluation was 100% for both CEUS-CT/MR and CT-CT/MR-MR, and the duration was 8.5 ± 2.8 min (range: 4-12 min) and 13.5 ± 4.5 min (range: 8-16 min) for CEUS-CT/MR and CT-CT/MR-MR, respectively. The sensitivity, specificity, and accuracy of CEUS-CT/MR imaging for evaluating the AM were 100.0, 80.0, and 90.0%, respectively. A phantom model composed of carrageenan gel and additives was suitable for the evaluation of HCC AM. CEUS-CT/MR image fusion can be used to evaluate HCC AM with high accuracy.
BP fusion model for the detection of oil spills on the sea by remote sensing

NASA Astrophysics Data System (ADS)

Chen, Weiwei; An, Jubai; Zhang, Hande; Lin, Bin

2003-06-01

Oil spills are very serious marine pollution in many countries. In order to detect and identify the oil-spilled on the sea by remote sensor, scientists have to conduct a research work on the remote sensing image. As to the detection of oil spills on the sea, edge detection is an important technology in image processing. There are many algorithms of edge detection developed for image processing. These edge detection algorithms always have their own advantages and disadvantages in the image processing. Based on the primary requirements of edge detection of the oil spills" image on the sea, computation time and detection accuracy, we developed a fusion model. The model employed a BP neural net to fuse the detection results of simple operators. The reason we selected BP neural net as the fusion technology is that the relation between simple operators" result of edge gray level and the image"s true edge gray level is nonlinear, while BP neural net is good at solving the nonlinear identification problem. Therefore in this paper we trained a BP neural net by some oil spill images, then applied the BP fusion model on the edge detection of other oil spill images and obtained a good result. In this paper the detection result of some gradient operators and Laplacian operator are also compared with the result of BP fusion model to analysis the fusion effect. At last the paper pointed out that the fusion model has higher accuracy and higher speed in the processing oil spill image"s edge detection.
Multisource image fusion method using support value transform.

PubMed

Zheng, Sheng; Shi, Wen-Zhong; Liu, Jian; Zhu, Guang-Xi; Tian, Jin-Wen

2007-07-01

With the development of numerous imaging sensors, many images can be simultaneously pictured by various sensors. However, there are many scenarios where no one sensor can give the complete picture. Image fusion is an important approach to solve this problem and produces a single image which preserves all relevant information from a set of different sensors. In this paper, we proposed a new image fusion method using the support value transform, which uses the support value to represent the salient features of image. This is based on the fact that, in support vector machines (SVMs), the data with larger support values have a physical meaning in the sense that they reveal relative more importance of the data points for contributing to the SVM model. The mapped least squares SVM (mapped LS-SVM) is used to efficiently compute the support values of image. The support value analysis is developed by using a series of multiscale support value filters, which are obtained by filling zeros in the basic support value filter deduced from the mapped LS-SVM to match the resolution of the desired level. Compared with the widely used image fusion methods, such as the Laplacian pyramid, discrete wavelet transform methods, the proposed method is an undecimated transform-based approach. The fusion experiments are undertaken on multisource images. The results demonstrate that the proposed approach is effective and is superior to the conventional image fusion methods in terms of the pertained quantitative fusion evaluation indexes, such as quality of visual information (Q(AB/F)), the mutual information, etc.
Application of Sensor Fusion to Improve Uav Image Classification

NASA Astrophysics Data System (ADS)

Jabari, S.; Fathollahi, F.; Zhang, Y.

2017-08-01

Image classification is one of the most important tasks of remote sensing projects including the ones that are based on using UAV images. Improving the quality of UAV images directly affects the classification results and can save a huge amount of time and effort in this area. In this study, we show that sensor fusion can improve image quality which results in increasing the accuracy of image classification. Here, we tested two sensor fusion configurations by using a Panchromatic (Pan) camera along with either a colour camera or a four-band multi-spectral (MS) camera. We use the Pan camera to benefit from its higher sensitivity and the colour or MS camera to benefit from its spectral properties. The resulting images are then compared to the ones acquired by a high resolution single Bayer-pattern colour camera (here referred to as HRC). We assessed the quality of the output images by performing image classification tests. The outputs prove that the proposed sensor fusion configurations can achieve higher accuracies compared to the images of the single Bayer-pattern colour camera. Therefore, incorporating a Pan camera on-board in the UAV missions and performing image fusion can help achieving higher quality images and accordingly higher accuracy classification results.
Change detection in synthetic aperture radar images based on image fusion and fuzzy clustering.

PubMed

Gong, Maoguo; Zhou, Zhiqiang; Ma, Jingjing

2012-04-01

This paper presents an unsupervised distribution-free change detection approach for synthetic aperture radar (SAR) images based on an image fusion strategy and a novel fuzzy clustering algorithm. The image fusion technique is introduced to generate a difference image by using complementary information from a mean-ratio image and a log-ratio image. In order to restrain the background information and enhance the information of changed regions in the fused difference image, wavelet fusion rules based on an average operator and minimum local area energy are chosen to fuse the wavelet coefficients for a low-frequency band and a high-frequency band, respectively. A reformulated fuzzy local-information C-means clustering algorithm is proposed for classifying changed and unchanged regions in the fused difference image. It incorporates the information about spatial context in a novel fuzzy way for the purpose of enhancing the changed information and of reducing the effect of speckle noise. Experiments on real SAR images show that the image fusion strategy integrates the advantages of the log-ratio operator and the mean-ratio operator and gains a better performance. The change detection results obtained by the improved fuzzy clustering algorithm exhibited lower error than its preexistences.
Multimodality Image Fusion-Guided Procedures: Technique, Accuracy, and Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abi-Jaoudeh, Nadine, E-mail: naj@mail.nih.gov; Kruecker, Jochen, E-mail: jochen.kruecker@philips.com; Kadoury, Samuel, E-mail: samuel.kadoury@polymtl.ca

2012-10-15

Personalized therapies play an increasingly critical role in cancer care: Image guidance with multimodality image fusion facilitates the targeting of specific tissue for tissue characterization and plays a role in drug discovery and optimization of tailored therapies. Positron-emission tomography (PET), magnetic resonance imaging (MRI), and contrast-enhanced computed tomography (CT) may offer additional information not otherwise available to the operator during minimally invasive image-guided procedures, such as biopsy and ablation. With use of multimodality image fusion for image-guided interventions, navigation with advanced modalities does not require the physical presence of the PET, MRI, or CT imaging system. Several commercially available methodsmore » of image-fusion and device navigation are reviewed along with an explanation of common tracking hardware and software. An overview of current clinical applications for multimodality navigation is provided.« less
Adaptive polarization image fusion based on regional energy dynamic weighted average

NASA Astrophysics Data System (ADS)

Zhao, Yong-Qiang; Pan, Quan; Zhang, Hong-Cai

2005-11-01

According to the principle of polarization imaging and the relation between Stokes parameters and the degree of linear polarization, there are much redundant and complementary information in polarized images. Since man-made objects and natural objects can be easily distinguished in images of degree of linear polarization and images of Stokes parameters contain rich detailed information of the scene, the clutters in the images can be removed efficiently while the detailed information can be maintained by combining these images. An algorithm of adaptive polarization image fusion based on regional energy dynamic weighted average is proposed in this paper to combine these images. Through an experiment and simulations, most clutters are removed by this algorithm. The fusion method is used for different light conditions in simulation, and the influence of lighting conditions on the fusion results is analyzed.
Data fusion of Landsat TM and IRS images in forest classification

Treesearch

Guangxing Wang; Markus Holopainen; Eero Lukkarinen

2000-01-01

Data fusion of Landsat TM images and Indian Remote Sensing satellite panchromatic image (IRS-1C PAN) was studied and compared to the use of TM or IRS image only. The aim was to combine the high spatial resolution of IRS-1C PAN to the high spectral resolution of Landsat TM images using a data fusion algorithm. The ground truth of the study was based on a sample of 1,020...
Comparison of conventional ultrasonography and ultrasonography-computed tomography fusion imaging for target identification using digital/real hybrid phantoms: a preliminary study.

PubMed

Soyama, Takeshi; Sakuhara, Yusuke; Kudo, Kohsuke; Abo, Daisuke; Wang, Jeff; Ito, Yoichi M; Hasegawa, Yu; Shirato, Hiroki

2016-07-01

This preliminary study compared ultrasonography-computed tomography (US-CT) fusion imaging and conventional ultrasonography (US) for accuracy and time required for target identification using a combination of real phantoms and sets of digitally modified computed tomography (CT) images (digital/real hybrid phantoms). In this randomized prospective study, 27 spheres visible on B-mode US were placed at depths of 3.5, 8.5, and 13.5 cm (nine spheres each). All 27 spheres were digitally erased from the CT images, and a radiopaque sphere was digitally placed at each of the 27 locations to create 27 different sets of CT images. Twenty clinicians were instructed to identify the sphere target using US alone and fusion imaging. The accuracy of target identification of the two methods was compared using McNemar's test. The mean time required for target identification and error distances were compared using paired t tests. At all three depths, target identification was more accurate and the mean time required for target identification was significantly less with US-CT fusion imaging than with US alone, and the mean error distances were also shorter with US-CT fusion imaging. US-CT fusion imaging was superior to US alone in terms of accurate and rapid identification of target lesions.
A robust color image fusion for low light level and infrared images

NASA Astrophysics Data System (ADS)

Liu, Chao; Zhang, Xiao-hui; Hu, Qing-ping; Chen, Yong-kang

2016-09-01

The low light level and infrared color fusion technology has achieved great success in the field of night vision, the technology is designed to make the hot target of fused image pop out with intenser colors, represent the background details with a nearest color appearance to nature, and improve the ability in target discovery, detection and identification. The low light level images have great noise under low illumination, and that the existing color fusion methods are easily to be influenced by low light level channel noise. To be explicit, when the low light level image noise is very large, the quality of the fused image decreases significantly, and even targets in infrared image would be submerged by the noise. This paper proposes an adaptive color night vision technology, the noise evaluation parameters of low light level image is introduced into fusion process, which improve the robustness of the color fusion. The color fuse results are still very good in low-light situations, which shows that this method can effectively improve the quality of low light level and infrared fused image under low illumination conditions.
Wavelet Fusion for Concealed Object Detection Using Passive Millimeter Wave Sequence Images

NASA Astrophysics Data System (ADS)

Chen, Y.; Pang, L.; Liu, H.; Xu, X.

2018-04-01

PMMW imaging system can create interpretable imagery on the objects concealed under clothing, which gives the great advantage to the security check system. Paper addresses wavelet fusion to detect concealed objects using passive millimeter wave (PMMW) sequence images. According to PMMW real-time imager acquired image characteristics and storage methods firstly, using the sum of squared difference (SSD) as the image-related parameters to screen the sequence images. Secondly, the selected images are optimized using wavelet fusion algorithm. Finally, the concealed objects are detected by mean filter, threshold segmentation and edge detection. The experimental results show that this method improves the detection effect of concealed objects by selecting the most relevant images from PMMW sequence images and using wavelet fusion to enhance the information of the concealed objects. The method can be effectively applied to human body concealed object detection in millimeter wave video.
Progressive multi-atlas label fusion by dictionary evolution.

PubMed

Song, Yantao; Wu, Guorong; Bahrami, Khosro; Sun, Quansen; Shen, Dinggang

2017-02-01

Accurate segmentation of anatomical structures in medical images is important in recent imaging based studies. In the past years, multi-atlas patch-based label fusion methods have achieved a great success in medical image segmentation. In these methods, the appearance of each input image patch is first represented by an atlas patch dictionary (in the image domain), and then the latent label of the input image patch is predicted by applying the estimated representation coefficients to the corresponding anatomical labels of the atlas patches in the atlas label dictionary (in the label domain). However, due to the generally large gap between the patch appearance in the image domain and the patch structure in the label domain, the estimated (patch) representation coefficients from the image domain may not be optimal for the final label fusion, thus reducing the labeling accuracy. To address this issue, we propose a novel label fusion framework to seek for the suitable label fusion weights by progressively constructing a dynamic dictionary in a layer-by-layer manner, where the intermediate dictionaries act as a sequence of guidance to steer the transition of (patch) representation coefficients from the image domain to the label domain. Our proposed multi-layer label fusion framework is flexible enough to be applied to the existing labeling methods for improving their label fusion performance, i.e., by extending their single-layer static dictionary to the multi-layer dynamic dictionary. The experimental results show that our proposed progressive label fusion method achieves more accurate hippocampal segmentation results for the ADNI dataset, compared to the counterpart methods using only the single-layer static dictionary. Copyright © 2016 Elsevier B.V. All rights reserved.
Radiomic biomarkers from PET/CT multi-modality fusion images for the prediction of immunotherapy response in advanced non-small cell lung cancer patients

NASA Astrophysics Data System (ADS)

Mu, Wei; Qi, Jin; Lu, Hong; Schabath, Matthew; Balagurunathan, Yoganand; Tunali, Ilke; Gillies, Robert James

2018-02-01

Purpose: Investigate the ability of using complementary information provided by the fusion of PET/CT images to predict immunotherapy response in non-small cell lung cancer (NSCLC) patients. Materials and methods: We collected 64 patients diagnosed with primary NSCLC treated with anti PD-1 checkpoint blockade. Using PET/CT images, fused images were created following multiple methodologies, resulting in up to 7 different images for the tumor region. Quantitative image features were extracted from the primary image (PET/CT) and the fused images, which included 195 from primary images and 1235 features from the fusion images. Three clinical characteristics were also analyzed. We then used support vector machine (SVM) classification models to identify discriminant features that predict immunotherapy response at baseline. Results: A SVM built with 87 fusion features and 13 primary PET/CT features on validation dataset had an accuracy and area under the ROC curve (AUROC) of 87.5% and 0.82, respectively, compared to a model built with 113 original PET/CT features on validation dataset 78.12% and 0.68. Conclusion: The fusion features shows better ability to predict immunotherapy response prediction compared to individual image features.
Image-guided techniques in renal and hepatic interventions.

PubMed

Najmaei, Nima; Mostafavi, Kamal; Shahbazi, Sahar; Azizian, Mahdi

2013-12-01

Development of new imaging technologies and advances in computing power have enabled the physicians to perform medical interventions on the basis of high-quality 3D and/or 4D visualization of the patient's organs. Preoperative imaging has been used for planning the surgery, whereas intraoperative imaging has been widely employed to provide visual feedback to a clinician when he or she is performing the procedure. In the past decade, such systems demonstrated great potential in image-guided minimally invasive procedures on different organs, such as brain, heart, liver and kidneys. This article focuses on image-guided interventions and surgery in renal and hepatic surgeries. A comprehensive search of existing electronic databases was completed for the period of 2000-2011. Each contribution was assessed by the authors for relevance and inclusion. The contributions were categorized on the basis of the type of operation/intervention, imaging modality and specific techniques such as image fusion and augmented reality, and organ motion tracking. As a result, detailed classification and comparative study of various contributions in image-guided renal and hepatic interventions are provided. In addition, the potential future directions have been sketched. With a detailed review of the literature, potential future trends in development of image-guided abdominal interventions are identified, namely, growing use of image fusion and augmented reality, computer-assisted and/or robot-assisted interventions, development of more accurate registration and navigation techniques, and growing applications of intraoperative magnetic resonance imaging. Copyright © 2012 John Wiley & Sons, Ltd.
Ultrasound-ultrasound image overlay fusion improves real-time control of radiofrequency ablation margin in the treatment of hepatocellular carcinoma.

PubMed

Minami, Yasunori; Minami, Tomohiro; Hagiwara, Satoru; Ida, Hiroshi; Ueshima, Kazuomi; Nishida, Naoshi; Murakami, Takamichi; Kudo, Masatoshi

2018-05-01

To assess the clinical feasibility of US-US image overlay fusion with evaluation of the ablative margin in radiofrequency ablation (RFA) for hepatocellular carcinoma (HCC). Fifty-three patients with 68 HCCs measuring 0.9-4.0 cm who underwent RFA guided by US-US overlay image fusion were included in this retrospective study. By an overlay of pre-/postoperative US, the tumor image could be projected onto the ablative hyperechoic zone. Therefore, the ablative margin three-dimensionally could be shown during the RFA procedure. US-US image overlay was compared to dynamic CT a few days after RFA for assessment of early treatment response. Accuracy of graded response was calculated, and the performance of US-US image overlay fusion was compared with that of CT using a Kappa agreement test. Technically effective ablation was achieved in a single session, and 59 HCCs (86.8 %) succeeded in obtaining a 5-mm margin on CT. The response with US-US image overlay correctly predicted early CT evaluation with an accuracy of 92.6 % (63/68) (k = 0.67; 95 % CI: 0.39-0.95). US-US image overlay fusion can be proposed as a feasible guidance in RFA with a safety margin and predicts early response of treatment assessment with high accuracy. • US-US image overlay fusion visualizes the ablative margin during RFA procedure. • Visualizing the margin during the procedure can prompt immediate complementary treatment. • US image fusion correlates with the results of early evaluation CT.
[Experience of Fusion image guided system in endonasal endoscopic surgery].

PubMed

Wen, Jingying; Zhen, Hongtao; Shi, Lili; Cao, Pingping; Cui, Yonghua

2015-08-01

To review endonasal endoscopic surgeries aided by Fusion image guided system, and to explore the application value of Fusion image guided system in endonasal endoscopic surgeries. Retrospective research. Sixty cases of endonasal endoscopic surgeries aided by Fusion image guided system were analysed including chronic rhinosinusitis with polyp (n = 10), fungus sinusitis (n = 5), endoscopic optic nerve decompression (n = 16), inverted papilloma of the paranasal sinus (n = 9), ossifying fibroma of sphenoid bone (n = 1), malignance of the paranasal sinus (n = 9), cerebrospinal fluid leak (n = 5), hemangioma of orbital apex (n = 2) and orbital reconstruction (n = 3). Sixty cases of endonasal endoscopic surgeries completed successfully without any complications. Fusion image guided system can help to identify the ostium of paranasal sinus, lamina papyracea and skull base. Fused CT-CTA images, or fused MR-MRA images can help to localize the optic nerve or internal carotid arteiy . Fused CT-MR images can help to detect the range of the tumor. It spent (7.13 ± 1.358) minutes for image guided system to do preoperative preparation and the surgical navigation accuracy reached less than 1mm after proficient. There was no device localization problem because of block or head set loosed. Fusion image guided system make endonasal endoscopic surgery to be a true microinvasive and exact surgery. It spends less preoperative preparation time, has high surgical navigation accuracy, improves the surgical safety and reduces the surgical complications.
Application of imaging fusion combining contrast-enhanced ultrasound and magnetic resonance imaging in detection of hepatic cellular carcinomas undetectable by conventional ultrasound.

PubMed

Dong, Yi; Wang, Wen-Ping; Mao, Feng; Ji, Zheng-Biao; Huang, Bei-Jian

2016-04-01

The aim of this study is to explore the value of volume navigation image fusion-assisted contrast-enhanced ultrasound (CEUS) in detection for radiofrequency ablation guidance of hepatocellular carcinomas (HCCs), which were undetectable on conventional ultrasound. From May 2012 to May 2014, 41 patients with 49 HCCs were included in this study. All lesions were detected by dynamic magnetic resonance imaging (MRI) and planned for radiofrequency ablation but were undetectable on conventional ultrasound. After a bolus injection of 2.4 ml SonoVue® (Bracco, Italy), LOGIQ E9 ultrasound system with volume navigation system (version R1.0.5, GE Healthcare, Milwaukee, WI, USA) was used to fuse CEUS and MRI images. The fusion time, fusion success rate, lesion enhancement pattern, and detection rate were analyzed. Image fusions were conducted successfully in 49 HCCs, the technical success rate was 100%. The average fusion time was (9.2 ± 2.1) min (6-12 min). The mean diameter of HCCs was 25.2 ± 5.3 mm (mean ± SD), and mean depth was 41.8 ± 17.2 mm. The detection rate of HCCs using CEUS/MRI imaging fusion (95.9%, 47/49) was significantly higher than CEUS (42.9%, 21/49) (P < 0.05). For small HCCs (diameter, 1-2 cm), the detection rate using imaging fusion (96.9%, 32/33) was also significantly higher than CEUS (18.2%, 6/33) (P < 0.01). All HCCs displayed a rapid wash-in pattern in the arterial phase of CEUS. Imaging fusion combining CEUS and MRI is a promising technique to improve the detection, precise localization, and accurate diagnosis of undetectable HCCs on conventional ultrasound, especially small and atypical HCCs. © 2015 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.

Dynamic image fusion and general observer preference

NASA Astrophysics Data System (ADS)

Burks, Stephen D.; Doe, Joshua M.

2010-04-01

Recent developments in image fusion give the user community many options for ways of presenting the imagery to an end-user. Individuals at the US Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate have developed an electronic system that allows users to quickly and efficiently determine optimal image fusion algorithms and color parameters based upon collected imagery and videos from environments that are typical to observers in a military environment. After performing multiple multi-band data collections in a variety of military-like scenarios, different waveband, fusion algorithm, image post-processing, and color choices are presented to observers as an output of the fusion system. The observer preferences can give guidelines as to how specific scenarios should affect the presentation of fused imagery.
Enhanced EDX images by fusion of multimodal SEM images using pansharpening techniques.

PubMed

Franchi, G; Angulo, J; Moreaud, M; Sorbier, L

2018-01-01

The goal of this paper is to explore the potential interest of image fusion in the context of multimodal scanning electron microscope (SEM) imaging. In particular, we aim at merging the backscattered electron images that usually have a high spatial resolution but do not provide enough discriminative information to physically classify the nature of the sample, with energy-dispersive X-ray spectroscopy (EDX) images that have discriminative information but a lower spatial resolution. The produced images are named enhanced EDX. To achieve this goal, we have compared the results obtained with classical pansharpening techniques for image fusion with an original approach tailored for multimodal SEM fusion of information. Quantitative assessment is obtained by means of two SEM images and a simulated dataset produced by a software based on PENELOPE. © 2017 The Authors Journal of Microscopy © 2017 Royal Microscopical Society.
Image fusion pitfalls for cranial radiosurgery

PubMed Central

Jonker, Benjamin P.

2013-01-01

Stereotactic radiosurgery requires imaging to define both the stereotactic space in which the treatment is delivered and the target itself. Image fusion is the process of using rotation and translation to bring a second image set into alignment with the first image set. This allows the potential concurrent use of multiple image sets to define the target and stereotactic space. While a single magnetic resonance imaging (MRI) sequence alone can be used for delineation of the target and fiducials, there may be significant advantages to using additional imaging sets including other MRI sequences, computed tomography (CT) scans, and advanced imaging sets such as catheter-based angiography, diffusor tension imaging-based fiber tracking and positon emission tomography in order to more accurately define the target and surrounding critical structures. Stereotactic space is usually defined by detection of fiducials on the stereotactic head frame or mask system. Unfortunately MRI sequences are susceptible to geometric distortion, whereas CT scans do not face this problem (although they have poorer resolution of the target in most cases). Thus image fusion can allow the definition of stereotactic space to proceed from the geometrically accurate CT images at the same time as using MRI to define the target. The use of image fusion is associated with risk of error introduced by inaccuracies of the fusion process, as well as workflow changes that if not properly accounted for can mislead the treating clinician. The purpose of this review is to describe the uses of image fusion in stereotactic radiosurgery as well as its potential pitfalls. PMID:23682338
Magnetic resonance-transcranial ultrasound fusion imaging: A novel tool for brain electrode location.

PubMed

Walter, Uwe; Müller, Jan-Uwe; Rösche, Johannes; Kirsch, Michael; Grossmann, Annette; Benecke, Reiner; Wittstock, Matthias; Wolters, Alexander

2016-03-01

A combination of preoperative magnetic resonance imaging (MRI) with real-time transcranial ultrasound, known as fusion imaging, may improve postoperative control of deep brain stimulation (DBS) electrode location. Fusion imaging, however, employs a weak magnetic field for tracking the position of the ultrasound transducer and the patient's head. Here we assessed its feasibility, safety, and clinical relevance in patients with DBS. Eighteen imaging sessions were conducted in 15 patients (7 women; aged 52.4 ± 14.4 y) with DBS of subthalamic nucleus (n = 6), globus pallidus interna (n = 5), ventro-intermediate (n = 3), or anterior (n = 1) thalamic nucleus and clinically suspected lead displacement. Minimum distance between DBS generator and magnetic field transmitter was kept at 65 cm. The pre-implantation MRI dataset was loaded into the ultrasound system for the fusion imaging examination. The DBS lead position was rated using validated criteria. Generator DBS parameters and neurological state of patients were monitored. Magnetic resonance-ultrasound fusion imaging and volume navigation were feasible in all cases and provided with real-time imaging capabilities of DBS lead and its location within the superimposed magnetic resonance images. Of 35 assessed lead locations, 30 were rated optimal, three suboptimal, and two displaced. In two cases, electrodes were re-implanted after confirming their inappropriate location on computed tomography (CT) scan. No influence of fusion imaging on clinical state of patients, or on DBS implantable pulse generator function, was found. Magnetic resonance-ultrasound real-time fusion imaging of DBS electrodes is safe with distinct precautions and improves assessment of electrode location. It may lower the need for repeated CT or MRI scans in DBS patients. © 2015 International Parkinson and Movement Disorder Society.
PubMed Central

Schulz-Wendtland, Rüdiger; Jud, Sebastian M.; Fasching, Peter A.; Hartmann, Arndt; Radicke, Marcus; Rauh, Claudia; Uder, Michael; Wunderle, Marius; Gass, Paul; Langemann, Hanna; Beckmann, Matthias W.; Emons, Julius

2017-01-01

Aim The combination of different imaging modalities through the use of fusion devices promises significant diagnostic improvement for breast pathology. The aim of this study was to evaluate image quality and clinical feasibility of a prototype fusion device (fusion prototype) constructed from a standard tomosynthesis mammography unit and a standard 3D ultrasound probe using a new method of breast compression. Materials and Methods Imaging was performed on 5 mastectomy specimens from patients with confirmed DCIS or invasive carcinoma (BI-RADS ™ 6). For the preclinical fusion prototype an ABVS system ultrasound probe from an Acuson S2000 was integrated into a MAMMOMAT Inspiration (both Siemens Healthcare Ltd) and, with the aid of a newly developed compression plate, digital mammogram and automated 3D ultrasound images were obtained. Results The quality of digital mammogram images produced by the fusion prototype was comparable to those produced using conventional compression. The newly developed compression plate did not influence the applied x-ray dose. The method was not more labour intensive or time-consuming than conventional mammography. From the technical perspective, fusion of the two modalities was achievable. Conclusion In this study, using only a few mastectomy specimens, the fusion of an automated 3D ultrasound machine with a standard mammography unit delivered images of comparable quality to conventional mammography. The device allows simultaneous ultrasound – the second important imaging modality in complementary breast diagnostics – without increasing examination time or requiring additional staff. PMID:28713173
Super-resolution algorithm based on sparse representation and wavelet preprocessing for remote sensing imagery

NASA Astrophysics Data System (ADS)

Ren, Ruizhi; Gu, Lingjia; Fu, Haoyang; Sun, Chenglin

2017-04-01

An effective super-resolution (SR) algorithm is proposed for actual spectral remote sensing images based on sparse representation and wavelet preprocessing. The proposed SR algorithm mainly consists of dictionary training and image reconstruction. Wavelet preprocessing is used to establish four subbands, i.e., low frequency, horizontal, vertical, and diagonal high frequency, for an input image. As compared to the traditional approaches involving the direct training of image patches, the proposed approach focuses on the training of features derived from these four subbands. The proposed algorithm is verified using different spectral remote sensing images, e.g., moderate-resolution imaging spectroradiometer (MODIS) images with different bands, and the latest Chinese Jilin-1 satellite images with high spatial resolution. According to the visual experimental results obtained from the MODIS remote sensing data, the SR images using the proposed SR algorithm are superior to those using a conventional bicubic interpolation algorithm or traditional SR algorithms without preprocessing. Fusion algorithms, e.g., standard intensity-hue-saturation, principal component analysis, wavelet transform, and the proposed SR algorithms are utilized to merge the multispectral and panchromatic images acquired by the Jilin-1 satellite. The effectiveness of the proposed SR algorithm is assessed by parameters such as peak signal-to-noise ratio, structural similarity index, correlation coefficient, root-mean-square error, relative dimensionless global error in synthesis, relative average spectral error, spectral angle mapper, and the quality index Q4, and its performance is better than that of the standard image fusion algorithms.
A systematic screen for morphological abnormalities during fission yeast sexual reproduction identifies a mechanism of actin aster formation for cell fusion

PubMed Central

Groux, Raphaël; Vincenzetti, Vincent

2017-01-01

In non-motile fungi, sexual reproduction relies on strong morphogenetic changes in response to pheromone signaling. We report here on a systematic screen for morphological abnormalities of the mating process in fission yeast Schizosaccharomyces pombe. We derived a homothallic (self-fertile) collection of viable deletions, which, upon visual screening, revealed a plethora of phenotypes affecting all stages of the mating process, including cell polarization, cell fusion and sporulation. Cell fusion relies on the formation of the fusion focus, an aster-like F-actin structure that is marked by strong local accumulation of the myosin V Myo52, which concentrates secretion at the fusion site. A secondary screen for fusion-defective mutants identified the myosin V Myo51-associated coiled-coil proteins Rng8 and Rng9 as critical for the coalescence of the fusion focus. Indeed, rng8Δ and rng9Δ mutant cells exhibit multiple stable dots at the cell-cell contact site, instead of the single focus observed in wildtype. Rng8 and Rng9 accumulate on the fusion focus, dependent on Myo51 and tropomyosin Cdc8. A tropomyosin mutant allele, which compromises Rng8/9 localization but not actin binding, similarly leads to multiple stable dots instead of a single focus. By contrast, myo51 deletion does not strongly affect fusion focus coalescence. We propose that focusing of the actin filaments in the fusion aster primarily relies on Rng8/9-dependent cross-linking of tropomyosin-actin filaments. PMID:28410370
Fusion Imaging: A Novel Staging Modality in Testis Cancer

PubMed Central

Sterbis, Joseph R.; Rice, Kevin R.; Javitt, Marcia C.; Schenkman, Noah S.; Brassell, Stephen A.

2010-01-01

Objective: Computed tomography and chest radiographs provide the standard imaging for staging, treatment, and surveillance of testicular germ cell neoplasms. Positron emission tomography has recently been utilized for staging, but is somewhat limited in its ability to provide anatomic localization. Fusion imaging combines the metabolic information provided by positron emission tomography with the anatomic precision of computed tomography. To the best of our knowledge, this represents the first study of the effectiveness using fusion imaging in evaluation of patients with testis cancer. Methods: A prospective study of 49 patients presenting to Walter Reed Army Medical Center with testicular cancer from 2003 to 2009 was performed. Fusion imaging was compared with conventional imaging, tumor markers, pathologic results, and clinical follow-up. Results: There were 14 true positives, 33 true negatives, 1 false positive, and 1 false negative. Sensitivity, specificity, positive predictive value, and negative predictive value were 93.3, 97.0, 93.3, and 97.0% respectively. In 11 patient scenarios, fusion imaging differed from conventional imaging. Utility was found in superior lesion detection compared to helical computed tomography due to anatomical/functional image co-registration, detection of micrometastasis in lymph nodes (pathologic nodes < 1cm), surveillance for recurrence post-chemotherapy, differentiating fibrosis from active disease in nodes < 2.5cm, and acting as a quality assurance measure to computed tomography alone. Conclusions: In addition to demonstrating a sensitivity and specificity comparable or superior to conventional imaging, fusion imaging shows promise in providing additive data that may assist in clinical decision-making. PMID:21103077
Fusion imaging: a novel staging modality in testis cancer.

PubMed

Sterbis, Joseph R; Rice, Kevin R; Javitt, Marcia C; Schenkman, Noah S; Brassell, Stephen A

2010-11-05

Computed tomography and chest radiographs provide the standard imaging for staging, treatment, and surveillance of testicular germ cell neoplasms. Positron emission tomography has recently been utilized for staging, but is somewhat limited in its ability to provide anatomic localization. Fusion imaging combines the metabolic information provided by positron emission tomography with the anatomic precision of computed tomography. To the best of our knowledge, this represents the first study of the effectiveness using fusion imaging in evaluation of patients with testis cancer. A prospective study of 49 patients presenting to Walter Reed Army Medical Center with testicular cancer from 2003 to 2009 was performed. Fusion imaging was compared with conventional imaging, tumor markers, pathologic results, and clinical follow-up. There were 14 true positives, 33 true negatives, 1 false positive, and 1 false negative. Sensitivity, specificity, positive predictive value, and negative predictive value were 93.3, 97.0, 93.3, and 97.0% respectively. In 11 patient scenarios, fusion imaging differed from conventional imaging. Utility was found in superior lesion detection compared to helical computed tomography due to anatomical/functional image co-registration, detection of micrometastasis in lymph nodes (pathologic nodes < 1cm), surveillance for recurrence post-chemotherapy, differentiating fibrosis from active disease in nodes < 2.5cm, and acting as a quality assurance measure to computed tomography alone. In addition to demonstrating a sensitivity and specificity comparable or superior to conventional imaging, fusion imaging shows promise in providing additive data that may assist in clinical decision-making.
Added Value of Contrast-Enhanced Ultrasound on Biopsies of Focal Hepatic Lesions Invisible on Fusion Imaging Guidance.

PubMed

Kang, Tae Wook; Lee, Min Woo; Song, Kyoung Doo; Kim, Mimi; Kim, Seung Soo; Kim, Seong Hyun; Ha, Sang Yun

2017-01-01

To assess whether contrast-enhanced ultrasonography (CEUS) with Sonazoid can improve the lesion conspicuity and feasibility of percutaneous biopsies for focal hepatic lesions invisible on fusion imaging of real-time ultrasonography (US) with computed tomography/magnetic resonance images, and evaluate its impact on clinical decision making. The Institutional Review Board approved this retrospective study. Between June 2013 and January 2015, 711 US-guided percutaneous biopsies were performed for focal hepatic lesions. Biopsies were performed using CEUS for guidance if lesions were invisible on fusion imaging. We retrospectively evaluated the number of target lesions initially invisible on fusion imaging that became visible after applying CEUS, using a 4-point scale. Technical success rates of biopsies were evaluated based on histopathological results. In addition, the occurrence of changes in clinical decision making was assessed. Among 711 patients, 16 patients (2.3%) were included in the study. The median size of target lesions was 1.1 cm (range, 0.5-1.9 cm) in pre-procedural imaging. After CEUS, 15 of 16 (93.8%) focal hepatic lesions were visualized. The conspicuity score was significantly increased after adding CEUS, as compared to that on fusion imaging (p < 0.001). The technical success rate of biopsy was 87.6% (14/16). After biopsy, there were changes in clinical decision making for 11 of 16 patients (68.8%). The addition of CEUS could improve the conspicuity of focal hepatic lesions invisible on fusion imaging. This dual guidance using CEUS and fusion imaging may affect patient management via changes in clinical decision-making.
Engineering Considerations for the Self-Energizing Magnetoplasmadynamic (MPD)-Type Fusion Plasma Thruster

DTIC Science & Technology

1992-02-01

Feasibility studies Of dense plasma focus (DPF) device as a fusion propulsion thruster have been performed. Both conventional and spin-polarized D...uncertainties remain in the validity of scaling laws on capacitor mass at high current beyond 1 MA. Fusion Propulsion, Dense Plasma Focus , Magnetoplasmadynamic Thruster, Advanced Fuel, D-3He Fusion, Spin-Polarized Fusion.
Evaluation of treatment response after chemoembolisation (TACE) in hepatocellular carcinoma using real time image fusion of contrast-enhanced ultrasound (CEUS) and computed tomography (CT)--preliminary results.

PubMed

Wobser, Hella; Wiest, Reiner; Salzberger, Bernd; Wohlgemuth, Walter Alexander; Stroszczynski, Christian; Jung, Ernst-Michael

2014-01-01

To evaluate treatment response of hepatocellular carcinoma (HCC) after transarterial chemoembolization (TACE) with a new real-time imaging fusion technique of contrast-enhanced ultrasound (CEUS) with multi-slice detection computed tomography (CT) in comparison to conventional post-interventional follow-up. 40 patients with HCC (26 male, ages 46-81 years) were evaluated 24 hours after TACE using CEUS with ultrasound volume navigation and image fusion with CT compared to non-enhanced CT and follow-up contrast-enhanced CT after 6-8 weeks. Reduction of tumor vascularization to less than 25% was regarded as "successful" treatment, whereas reduction to levels >25% was considered as "partial" treatment response. Homogenous lipiodol retention was regarded as successful treatment in non-enhanced CT. Post-interventional image fusion of CEUS with CT was feasible in all 40 patients. In 24 patients (24/40), post-interventional image fusion with CEUS revealed residual tumor vascularity, that was confirmed by contrast-enhanced CT 6-8 weeks later in 24/24 patients. In 16 patients (16/40), post-interventional image fusion with CEUS demonstrated successful treatment, but follow-up CT detected residual viable tumor (6/16). Non-enhanced CT did not identify any case of treatment failure. Image fusion with CEUS assessed treatment efficacy with a specificity of 100%, sensitivity of 80% and a positive predictive value of 1 (negative predictive value 0.63). Image fusion of CEUS with CT allows a reliable, highly specific post-interventional evaluation of embolization response with good sensitivity without any further radiation exposure. It can detect residual viable tumor at early state, resulting in a close patient monitoring or re-therapy.
Research on fusion algorithm of polarization image in tetrolet domain

NASA Astrophysics Data System (ADS)

Zhang, Dexiang; Yuan, BaoHong; Zhang, Jingjing

2015-12-01

Tetrolets are Haar-type wavelets whose supports are tetrominoes which are shapes made by connecting four equal-sized squares. A fusion method for polarization images based on tetrolet transform is proposed. Firstly, the magnitude of polarization image and angle of polarization image can be decomposed into low-frequency coefficients and high-frequency coefficients with multi-scales and multi-directions using tetrolet transform. For the low-frequency coefficients, the average fusion method is used. According to edge distribution differences in high frequency sub-band images, for the directional high-frequency coefficients are used to select the better coefficients by region spectrum entropy algorithm for fusion. At last the fused image can be obtained by utilizing inverse transform for fused tetrolet coefficients. Experimental results show that the proposed method can detect image features more effectively and the fused image has better subjective visual effect
PET/CT image registration: preliminary tests for its application to clinical dosimetry in radiotherapy.

PubMed

Baños-Capilla, M C; García, M A; Bea, J; Pla, C; Larrea, L; López, E

2007-06-01

The quality of dosimetry in radiotherapy treatment requires the accurate delimitation of the gross tumor volume. This can be achieved by complementing the anatomical detail provided by CT images through fusion with other imaging modalities that provide additional metabolic and physiological information. Therefore, use of multiple imaging modalities for radiotherapy treatment planning requires an accurate image registration method. This work describes tests carried out on a Discovery LS positron emission/computed tomography (PET/CT) system by General Electric Medical Systems (GEMS), for its later use to obtain images to delimit the target in radiotherapy treatment. Several phantoms have been used to verify image correlation, in combination with fiducial markers, which were used as a system of external landmarks. We analyzed the geometrical accuracy of two different fusion methods with the images obtained with these phantoms. We first studied the fusion method used by the PET/CT system by GEMS (hardware fusion) on the basis that there is satisfactory coincidence between the reconstruction centers in CT and PET systems; and secondly the fiducial fusion, a registration method, by means of least-squares fitting algorithm of a landmark points system. The study concluded with the verification of the centroid position of some phantom components in both imaging modalities. Centroids were estimated through a calculation similar to center-of-mass, weighted by the value of the CT number and the uptake intensity in PET. The mean deviations found for the hardware fusion method were: deltax/ +/-sigma = 3.3 mm +/- 1.0 mm and /deltax/ +/-sigma = 3.6 mm +/- 1.0 mm. These values were substantially improved upon applying fiducial fusion based on external landmark points: /deltax/ +/-sigma = 0.7 mm +/- 0.8 mm and /deltax/ +/-sigma = 0.3 mm 1.7 mm. We also noted that differences found for each of the fusion methods were similar for both the axial and helical CT image acquisition protocols.
Infrared and visible image fusion based on total variation and augmented Lagrangian.

PubMed

Guo, Hanqi; Ma, Yong; Mei, Xiaoguang; Ma, Jiayi

2017-11-01

This paper proposes a new algorithm for infrared and visible image fusion based on gradient transfer that achieves fusion by preserving the intensity of the infrared image and then transferring gradients in the corresponding visible one to the result. The gradient transfer suffers from the problems of low dynamic range and detail loss because it ignores the intensity from the visible image. The new algorithm solves these problems by providing additive intensity from the visible image to balance the intensity between the infrared image and the visible one. It formulates the fusion task as an l 1 -l 1 -TV minimization problem and then employs variable splitting and augmented Lagrangian to convert the unconstrained problem to a constrained one that can be solved in the framework of alternating the multiplier direction method. Experiments demonstrate that the new algorithm achieves better fusion results with a high computation efficiency in both qualitative and quantitative tests than gradient transfer and most state-of-the-art methods.
Dim target detection method based on salient graph fusion

NASA Astrophysics Data System (ADS)

Hu, Ruo-lan; Shen, Yi-yan; Jiang, Jun

2018-02-01

Dim target detection is one key problem in digital image processing field. With development of multi-spectrum imaging sensor, it becomes a trend to improve the performance of dim target detection by fusing the information from different spectral images. In this paper, one dim target detection method based on salient graph fusion was proposed. In the method, Gabor filter with multi-direction and contrast filter with multi-scale were combined to construct salient graph from digital image. And then, the maximum salience fusion strategy was designed to fuse the salient graph from different spectral images. Top-hat filter was used to detect dim target from the fusion salient graph. Experimental results show that proposal method improved the probability of target detection and reduced the probability of false alarm on clutter background images.
Image fusion and navigation platforms for percutaneous image-guided interventions.

PubMed

Rajagopal, Manoj; Venkatesan, Aradhana M

2016-04-01

Image-guided interventional procedures, particularly image guided biopsy and ablation, serve an important role in the care of the oncology patient. The need for tumor genomic and proteomic profiling, early tumor response assessment and confirmation of early recurrence are common scenarios that may necessitate successful biopsies of targets, including those that are small, anatomically unfavorable or inconspicuous. As image-guided ablation is increasingly incorporated into interventional oncology practice, similar obstacles are posed for the ablation of technically challenging tumor targets. Navigation tools, including image fusion and device tracking, can enable abdominal interventionalists to more accurately target challenging biopsy and ablation targets. Image fusion technologies enable multimodality fusion and real-time co-displays of US, CT, MRI, and PET/CT data, with navigational technologies including electromagnetic tracking, robotic, cone beam CT, optical, and laser guidance of interventional devices. Image fusion and navigational platform technology is reviewed in this article, including the results of studies implementing their use for interventional procedures. Pre-clinical and clinical experiences to date suggest these technologies have the potential to reduce procedure risk, time, and radiation dose to both the patient and the operator, with a valuable role to play for complex image-guided interventions.
Compressive hyperspectral and multispectral imaging fusion

NASA Astrophysics Data System (ADS)

Espitia, Óscar; Castillo, Sergio; Arguello, Henry

2016-05-01

Image fusion is a valuable framework which combines two or more images of the same scene from one or multiple sensors, allowing to improve the resolution of the images and increase the interpretable content. In remote sensing a common fusion problem consists of merging hyperspectral (HS) and multispectral (MS) images that involve large amount of redundant data, which ignores the highly correlated structure of the datacube along the spatial and spectral dimensions. Compressive HS and MS systems compress the spectral data in the acquisition step allowing to reduce the data redundancy by using different sampling patterns. This work presents a compressed HS and MS image fusion approach, which uses a high dimensional joint sparse model. The joint sparse model is formulated by combining HS and MS compressive acquisition models. The high spectral and spatial resolution image is reconstructed by using sparse optimization algorithms. Different fusion spectral image scenarios are used to explore the performance of the proposed scheme. Several simulations with synthetic and real datacubes show promising results as the reliable reconstruction of a high spectral and spatial resolution image can be achieved by using as few as just the 50% of the datacube.
The addition of a sagittal image fusion improves the prostate cancer detection in a sensor-based MRI /ultrasound fusion guided targeted biopsy.

PubMed

Günzel, Karsten; Cash, Hannes; Buckendahl, John; Königbauer, Maximilian; Asbach, Patrick; Haas, Matthias; Neymeyer, Jörg; Hinz, Stefan; Miller, Kurt; Kempkensteffen, Carsten

2017-01-13

To explore the diagnostic benefit of an additional image fusion of the sagittal plane in addition to the standard axial image fusion, using a sensor-based MRI/US fusion platform. During July 2013 and September 2015, 251 patients with at least one suspicious lesion on mpMRI (rated by PI-RADS) were included into the analysis. All patients underwent MRI/US targeted biopsy (TB) in combination with a 10 core systematic prostate biopsy (SB). All biopsies were performed on a sensor-based fusion system. Group A included 162 men who received TB by an axial MRI/US image fusion. Group B comprised 89 men in whom the TB was performed with an additional sagittal image fusion. The median age in group A was 67 years (IQR 61-72) and in group B 68 years (IQR 60-71). The median PSA level in group A was 8.10 ng/ml (IQR 6.05-14) and in group B 8.59 ng/ml (IQR 5.65-12.32). In group A the proportion of patients with a suspicious digital rectal examination (DRE) (14 vs. 29%, p = 0.007) and the proportion of primary biopsies (33 vs 46%, p = 0.046) were significantly lower. The rate of PI-RADS 3 lesions were overrepresented in group A compared to group B (19 vs. 9%; p = 0.044). Classified according to PI-RADS 3, 4 and 5, the detection rates of TB were 42, 48, 75% in group A and 25, 74, 90% in group B. The rate of PCa with a Gleason score ≥7 missed by TB was 33% (18 cases) in group A and 9% (5 cases) in group B; p-value 0.072. An explorative multivariate binary logistic regression analysis revealed that PI-RADS, a suspicious DRE and performing an additional sagittal image fusion were significant predictors for PCa detection in TB. 9 PCa were only detected by TB with sagittal fusion (sTB) and sTB identified 10 additional clinically significant PCa (Gleason ≥7). Performing an additional sagittal image fusion besides the standard axial fusion appears to improve the accuracy of the sensor-based MRI/US fusion platform.
Assessment of Spatiotemporal Fusion Algorithms for Planet and Worldview Images

PubMed Central

Zhu, Xiaolin; Gao, Feng; Chou, Bryan; Li, Jiang; Shen, Yuzhong; Koperski, Krzysztof; Marchisio, Giovanni

2018-01-01

Although Worldview-2 (WV) images (non-pansharpened) have 2-m resolution, the re-visit times for the same areas may be seven days or more. In contrast, Planet images are collected using small satellites that can cover the whole Earth almost daily. However, the resolution of Planet images is 3.125 m. It would be ideal to fuse these two satellites images to generate high spatial resolution (2 m) and high temporal resolution (1 or 2 days) images for applications such as damage assessment, border monitoring, etc. that require quick decisions. In this paper, we evaluate three approaches to fusing Worldview (WV) and Planet images. These approaches are known as Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), Flexible Spatiotemporal Data Fusion (FSDAF), and Hybrid Color Mapping (HCM), which have been applied to the fusion of MODIS and Landsat images in recent years. Experimental results using actual Planet and Worldview images demonstrated that the three aforementioned approaches have comparable performance and can all generate high quality prediction images. PMID:29614745

Assessment of Spatiotemporal Fusion Algorithms for Planet and Worldview Images.

PubMed

Kwan, Chiman; Zhu, Xiaolin; Gao, Feng; Chou, Bryan; Perez, Daniel; Li, Jiang; Shen, Yuzhong; Koperski, Krzysztof; Marchisio, Giovanni

2018-03-31

Although Worldview-2 (WV) images (non-pansharpened) have 2-m resolution, the re-visit times for the same areas may be seven days or more. In contrast, Planet images are collected using small satellites that can cover the whole Earth almost daily. However, the resolution of Planet images is 3.125 m. It would be ideal to fuse these two satellites images to generate high spatial resolution (2 m) and high temporal resolution (1 or 2 days) images for applications such as damage assessment, border monitoring, etc. that require quick decisions. In this paper, we evaluate three approaches to fusing Worldview (WV) and Planet images. These approaches are known as Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), Flexible Spatiotemporal Data Fusion (FSDAF), and Hybrid Color Mapping (HCM), which have been applied to the fusion of MODIS and Landsat images in recent years. Experimental results using actual Planet and Worldview images demonstrated that the three aforementioned approaches have comparable performance and can all generate high quality prediction images.
Speckle noise reduction in ultrasound images using a discrete wavelet transform-based image fusion technique.

PubMed

Choi, Hyun Ho; Lee, Ju Hwan; Kim, Sung Min; Park, Sung Yun

2015-01-01

Here, the speckle noise in ultrasonic images is removed using an image fusion-based denoising method. To optimize the denoising performance, each discrete wavelet transform (DWT) and filtering technique was analyzed and compared. In addition, the performances were compared in order to derive the optimal input conditions. To evaluate the speckle noise removal performance, an image fusion algorithm was applied to the ultrasound images, and comparatively analyzed with the original image without the algorithm. As a result, applying DWT and filtering techniques caused information loss and noise characteristics, and did not represent the most significant noise reduction performance. Conversely, an image fusion method applying SRAD-original conditions preserved the key information in the original image, and the speckle noise was removed. Based on such characteristics, the input conditions of SRAD-original had the best denoising performance with the ultrasound images. From this study, the best denoising technique proposed based on the results was confirmed to have a high potential for clinical application.
Image Fusion Algorithms Using Human Visual System in Transform Domain

NASA Astrophysics Data System (ADS)

Vadhi, Radhika; Swamy Kilari, Veera; Samayamantula, Srinivas Kumar

2017-08-01

The endeavor of digital image fusion is to combine the important visual parts from various sources to advance the visibility eminence of the image. The fused image has a more visual quality than any source images. In this paper, the Human Visual System (HVS) weights are used in the transform domain to select appropriate information from various source images and then to attain a fused image. In this process, mainly two steps are involved. First, apply the DWT to the registered source images. Later, identify qualitative sub-bands using HVS weights. Hence, qualitative sub-bands are selected from different sources to form high quality HVS based fused image. The quality of the HVS based fused image is evaluated with general fusion metrics. The results show the superiority among the state-of-the art resolution Transforms (MRT) such as Discrete Wavelet Transform (DWT), Stationary Wavelet Transform (SWT), Contourlet Transform (CT), and Non Sub Sampled Contourlet Transform (NSCT) using maximum selection fusion rule.
Fusion of Geophysical Images in the Study of Archaeological Sites

NASA Astrophysics Data System (ADS)

Karamitrou, A. A.; Petrou, M.; Tsokas, G. N.

2011-12-01

This paper presents results from different fusion techniques between geophysical images from different modalities in order to combine them into one image with higher information content than the two original images independently. The resultant image will be useful for the detection and mapping of buried archaeological relics. The examined archaeological area is situated in Kampana site (NE Greece) near the ancient theater of Maronia city. Archaeological excavations revealed an ancient theater, an aristocratic house and the temple of the ancient Greek God Dionysus. Numerous ceramic objects found in the broader area indicated the probability of the existence of buried urban structure. In order to accurately locate and map the latter, geophysical measurements performed with the use of the magnetic method (vertical gradient of the magnetic field) and of the electrical method (apparent resistivity). We performed a semi-stochastic pixel based registration method between the geophysical images in order to fine register them by correcting their local spatial offsets produced by the use of hand held devices. After this procedure we applied to the registered images three different fusion approaches. Image fusion is a relatively new technique that not only allows integration of different information sources, but also takes advantage of the spatial and spectral resolution as well as the orientation characteristics of each image. We have used three different fusion techniques, fusion with mean values, with wavelets by enhancing selected frequency bands and curvelets giving emphasis at specific bands and angles (according the expecting orientation of the relics). In all three cases the fused images gave significantly better results than each of the original geophysical images separately. The comparison of the results of the three different approaches showed that the fusion with the use of curvelets, giving emphasis at the features' orientation, seems to give the best fused image. In the resultant image appear clear linear and ellipsoid features corresponding to potential archaeological relics.
Multispectral Image Enhancement Through Adaptive Wavelet Fusion

DTIC Science & Technology

2016-09-14

13. SUPPLEMENTARY NOTES 14. ABSTRACT This research developed a multiresolution image fusion scheme based on guided filtering . Guided filtering can...effectively reduce noise while preserving detail boundaries. When applied in an iterative mode, guided filtering selectively eliminates small scale...details while restoring larger scale edges. The proposed multi-scale image fusion scheme achieves spatial consistency by using guided filtering both at
Multidimensional Visualization of MHD and Turbulence in Fusion Plasmas [Multi-dimensional Visualization of Turbulence in Fusion Plasmas

DOE PAGES

Muscatello, Christopher M.; Domier, Calvin W.; Hu, Xing; ...

2014-08-13

Here, quasi-optical imaging at sub-THz frequencies has had a major impact on fusion plasma diagnostics. Mm-wave imaging reflectometry utilizes microwaves to actively probe fusion plasmas, inferring the local properties of electron density fluctuations. Electron cyclotron emission imaging is a multichannel radiometer that passively measures the spontaneous emission of microwaves from the plasma to infer local properties of electron temperature fluctuations. These imaging diagnostics work together to diagnose the characteristics of turbulence. Important quantities such as amplitude and wavenumber of coherent fluctuations, correlation lengths and decor relation times of turbulence, and poloidal flow velocity of the plasma are readily inferred.
Detail-enhanced multimodality medical image fusion based on gradient minimization smoothing filter and shearing filter.

PubMed

Liu, Xingbin; Mei, Wenbo; Du, Huiqian

2018-02-13

In this paper, a detail-enhanced multimodality medical image fusion algorithm is proposed by using proposed multi-scale joint decomposition framework (MJDF) and shearing filter (SF). The MJDF constructed with gradient minimization smoothing filter (GMSF) and Gaussian low-pass filter (GLF) is used to decompose source images into low-pass layers, edge layers, and detail layers at multiple scales. In order to highlight the detail information in the fused image, the edge layer and the detail layer in each scale are weighted combined into a detail-enhanced layer. As directional filter is effective in capturing salient information, so SF is applied to the detail-enhanced layer to extract geometrical features and obtain directional coefficients. Visual saliency map-based fusion rule is designed for fusing low-pass layers, and the sum of standard deviation is used as activity level measurement for directional coefficients fusion. The final fusion result is obtained by synthesizing the fused low-pass layers and directional coefficients. Experimental results show that the proposed method with shift-invariance, directional selectivity, and detail-enhanced property is efficient in preserving and enhancing detail information of multimodality medical images. Graphical abstract The detailed implementation of the proposed medical image fusion algorithm.
Adaptive structured dictionary learning for image fusion based on group-sparse-representation

NASA Astrophysics Data System (ADS)

Yang, Jiajie; Sun, Bin; Luo, Chengwei; Wu, Yuzhong; Xu, Limei

2018-04-01

Dictionary learning is the key process of sparse representation which is one of the most widely used image representation theories in image fusion. The existing dictionary learning method does not use the group structure information and the sparse coefficients well. In this paper, we propose a new adaptive structured dictionary learning algorithm and a l1-norm maximum fusion rule that innovatively utilizes grouped sparse coefficients to merge the images. In the dictionary learning algorithm, we do not need prior knowledge about any group structure of the dictionary. By using the characteristics of the dictionary in expressing the signal, our algorithm can automatically find the desired potential structure information that hidden in the dictionary. The fusion rule takes the physical meaning of the group structure dictionary, and makes activity-level judgement on the structure information when the images are being merged. Therefore, the fused image can retain more significant information. Comparisons have been made with several state-of-the-art dictionary learning methods and fusion rules. The experimental results demonstrate that, the dictionary learning algorithm and the fusion rule both outperform others in terms of several objective evaluation metrics.
Assessment of SPOT-6 optical remote sensing data against GF-1 using NNDiffuse image fusion algorithm

NASA Astrophysics Data System (ADS)

Zhao, Jinling; Guo, Junjie; Cheng, Wenjie; Xu, Chao; Huang, Linsheng

2017-07-01

A cross-comparison method was used to assess the SPOT-6 optical satellite imagery against Chinese GF-1 imagery using three types of indicators: spectral and color quality, fusion effect and identification potential. More specifically, spectral response function (SRF) curves were used to compare the two imagery, showing that the SRF curve shape of SPOT-6 is more like a rectangle compared to GF-1 in blue, green, red and near-infrared bands. NNDiffuse image fusion algorithm was used to evaluate the capability of information conservation in comparison with wavelet transform (WT) and principal component (PC) algorithms. The results show that NNDiffuse fused image has extremely similar entropy vales than original image (1.849 versus 1.852) and better color quality. In addition, the object-oriented classification toolset (ENVI EX) was used to identify greenlands for comparing the effect of self-fusion image of SPOT-6 and inter-fusion image between SPOT-6 and GF-1 based on the NNDiffuse algorithm. The overall accuracy is 97.27% and 76.88%, respectively, showing that self-fused image of SPOT-6 has better identification capability.
Some new classification methods for hyperspectral remote sensing

NASA Astrophysics Data System (ADS)

Du, Pei-jun; Chen, Yun-hao; Jones, Simon; Ferwerda, Jelle G.; Chen, Zhi-jun; Zhang, Hua-peng; Tan, Kun; Yin, Zuo-xia

2006-10-01

Hyperspectral Remote Sensing (HRS) is one of the most significant recent achievements of Earth Observation Technology. Classification is the most commonly employed processing methodology. In this paper three new hyperspectral RS image classification methods are analyzed. These methods are: Object-oriented FIRS image classification, HRS image classification based on information fusion and HSRS image classification by Back Propagation Neural Network (BPNN). OMIS FIRS image is used as the example data. Object-oriented techniques have gained popularity for RS image classification in recent years. In such method, image segmentation is used to extract the regions from the pixel information based on homogeneity criteria at first, and spectral parameters like mean vector, texture, NDVI and spatial/shape parameters like aspect ratio, convexity, solidity, roundness and orientation for each region are calculated, finally classification of the image using the region feature vectors and also using suitable classifiers such as artificial neural network (ANN). It proves that object-oriented methods can improve classification accuracy since they utilize information and features both from the point and the neighborhood, and the processing unit is a polygon (in which all pixels are homogeneous and belong to the class). HRS image classification based on information fusion, divides all bands of the image into different groups initially, and extracts features from every group according to the properties of each group. Three levels of information fusion: data level fusion, feature level fusion and decision level fusion are used to HRS image classification. Artificial Neural Network (ANN) can perform well in RS image classification. In order to promote the advances of ANN used for HIRS image classification, Back Propagation Neural Network (BPNN), the most commonly used neural network, is used to HRS image classification.
The effect of multispectral image fusion enhancement on human efficiency.

PubMed

Bittner, Jennifer L; Schill, M Trent; Mohd-Zaid, Fairul; Blaha, Leslie M

2017-01-01

The visual system can be highly influenced by changes to visual presentation. Thus, numerous techniques have been developed to augment imagery in an attempt to improve human perception. The current paper examines the potential impact of one such enhancement, multispectral image fusion, where imagery captured in varying spectral bands (e.g., visible, thermal, night vision) is algorithmically combined to produce an output to strengthen visual perception. We employ ideal observer analysis over a series of experimental conditions to (1) establish a framework for testing the impact of image fusion over the varying aspects surrounding its implementation (e.g., stimulus content, task) and (2) examine the effectiveness of fusion on human information processing efficiency in a basic application. We used a set of rotated Landolt C images captured with a number of individual sensor cameras and combined across seven traditional fusion algorithms (e.g., Laplacian pyramid, principal component analysis, averaging) in a 1-of-8 orientation task. We found that, contrary to the idea of fused imagery always producing a greater impact on perception, single-band imagery can be just as influential. Additionally, efficiency data were shown to fluctuate based on sensor combination instead of fusion algorithm, suggesting the need for examining multiple factors to determine the success of image fusion. Our use of ideal observer analysis, a popular technique from the vision sciences, provides not only a standard for testing fusion in direct relation to the visual system but also allows for comparable examination of fusion across its associated problem space of application.
Benchmarking image fusion system design parameters

NASA Astrophysics Data System (ADS)

Howell, Christopher L.

2013-06-01

A clear and absolute method for discriminating between image fusion algorithm performances is presented. This method can effectively be used to assist in the design and modeling of image fusion systems. Specifically, it is postulated that quantifying human task performance using image fusion should be benchmarked to whether the fusion algorithm, at a minimum, retained the performance benefit achievable by each independent spectral band being fused. The established benchmark would then clearly represent the threshold that a fusion system should surpass to be considered beneficial to a particular task. A genetic algorithm is employed to characterize the fused system parameters using a Matlab® implementation of NVThermIP as the objective function. By setting the problem up as a mixed-integer constraint optimization problem, one can effectively look backwards through the image acquisition process: optimizing fused system parameters by minimizing the difference between modeled task difficulty measure and the benchmark task difficulty measure. The results of an identification perception experiment are presented, where human observers were asked to identify a standard set of military targets, and used to demonstrate the effectiveness of the benchmarking process.
Pixel-based image fusion with false color mapping

NASA Astrophysics Data System (ADS)

Zhao, Wei; Mao, Shiyi

2003-06-01

In this paper, we propose a pixel-based image fusion algorithm that combines the gray-level image fusion method with the false color mapping. This algorithm integrates two gray-level images presenting different sensor modalities or at different frequencies and produces a fused false-color image. The resulting image has higher information content than each of the original images. The objects in the fused color image are easy to be recognized. This algorithm has three steps: first, obtaining the fused gray-level image of two original images; second, giving the generalized high-boost filtering images between fused gray-level image and two source images respectively; third, generating the fused false-color image. We use the hybrid averaging and selection fusion method to obtain the fused gray-level image. The fused gray-level image will provide better details than two original images and reduce noise at the same time. But the fused gray-level image can't contain all detail information in two source images. At the same time, the details in gray-level image cannot be discerned as easy as in a color image. So a color fused image is necessary. In order to create color variation and enhance details in the final fusion image, we produce three generalized high-boost filtering images. These three images are displayed through red, green and blue channel respectively. A fused color image is produced finally. This method is used to fuse two SAR images acquired on the San Francisco area (California, USA). The result shows that fused false-color image enhances the visibility of certain details. The resolution of the final false-color image is the same as the resolution of the input images.
Multispectral multisensor image fusion using wavelet transforms

USGS Publications Warehouse

Lemeshewsky, George P.

1999-01-01

Fusion techniques can be applied to multispectral and higher spatial resolution panchromatic images to create a composite image that is easier to interpret than the individual images. Wavelet transform-based multisensor, multiresolution fusion (a type of band sharpening) was applied to Landsat thematic mapper (TM) multispectral and coregistered higher resolution SPOT panchromatic images. The objective was to obtain increased spatial resolution, false color composite products to support the interpretation of land cover types wherein the spectral characteristics of the imagery are preserved to provide the spectral clues needed for interpretation. Since the fusion process should not introduce artifacts, a shift invariant implementation of the discrete wavelet transform (SIDWT) was used. These results were compared with those using the shift variant, discrete wavelet transform (DWT). Overall, the process includes a hue, saturation, and value color space transform to minimize color changes, and a reported point-wise maximum selection rule to combine transform coefficients. The performance of fusion based on the SIDWT and DWT was evaluated with a simulated TM 30-m spatial resolution test image and a higher resolution reference. Simulated imagery was made by blurring higher resolution color-infrared photography with the TM sensors' point spread function. The SIDWT based technique produced imagery with fewer artifacts and lower error between fused images and the full resolution reference. Image examples with TM and SPOT 10-m panchromatic illustrate the reduction in artifacts due to the SIDWT based fusion.
Image fusion in craniofacial virtual reality modeling based on CT and 3dMD photogrammetry.

PubMed

Xin, Pengfei; Yu, Hongbo; Cheng, Huanchong; Shen, Shunyao; Shen, Steve G F

2013-09-01

The aim of this study was to demonstrate the feasibility of building a craniofacial virtual reality model by image fusion of 3-dimensional (3D) CT models and 3 dMD stereophotogrammetric facial surface. A CT scan and stereophotography were performed. The 3D CT models were reconstructed by Materialise Mimics software, and the stereophotogrammetric facial surface was reconstructed by 3 dMD patient software. All 3D CT models were exported as Stereo Lithography file format, and the 3 dMD model was exported as Virtual Reality Modeling Language file format. Image registration and fusion were performed in Mimics software. Genetic algorithm was used for precise image fusion alignment with minimum error. The 3D CT models and the 3 dMD stereophotogrammetric facial surface were finally merged into a single file and displayed using Deep Exploration software. Errors between the CT soft tissue model and 3 dMD facial surface were also analyzed. Virtual model based on CT-3 dMD image fusion clearly showed the photorealistic face and bone structures. Image registration errors in virtual face are mainly located in bilateral cheeks and eyeballs, and the errors are more than 1.5 mm. However, the image fusion of whole point cloud sets of CT and 3 dMD is acceptable with a minimum error that is less than 1 mm. The ease of use and high reliability of CT-3 dMD image fusion allows the 3D virtual head to be an accurate, realistic, and widespread tool, and has a great benefit to virtual face model.
PI(4,5)P2 regulates myoblast fusion through Arp2/3 regulator localization at the fusion site

PubMed Central

Bothe, Ingo; Deng, Su; Baylies, Mary

2014-01-01

Cell-cell fusion is a regulated process that requires merging of the opposing membranes and underlying cytoskeletons. However, the integration between membrane and cytoskeleton signaling during fusion is not known. Using Drosophila, we demonstrate that the membrane phosphoinositide PI(4,5)P2 is a crucial regulator of F-actin dynamics during myoblast fusion. PI(4,5)P2 is locally enriched and colocalizes spatially and temporally with the F-actin focus that defines the fusion site. PI(4,5)P2 enrichment depends on receptor engagement but is upstream or parallel to actin remodeling. Regulators of actin branching via Arp2/3 colocalize with PI(4,5)P2 in vivo and bind PI(4,5)P2 in vitro. Manipulation of PI(4,5)P2 availability leads to impaired fusion, with a reduction in the F-actin focus size and altered focus morphology. Mechanistically, the changes in the actin focus are due to a failure in the enrichment of actin regulators at the fusion site. Moreover, improper localization of these regulators hinders expansion of the fusion interface. Thus, PI(4,5)P2 enrichment at the fusion site encodes spatial and temporal information that regulates fusion progression through the localization of activators of actin polymerization. PMID:24821989
A new hyperspectral image compression paradigm based on fusion

NASA Astrophysics Data System (ADS)

Guerra, Raúl; Melián, José; López, Sebastián.; Sarmiento, Roberto

2016-10-01

The on-board compression of remote sensed hyperspectral images is an important task nowadays. One of the main difficulties is that the compression of these images must be performed in the satellite which carries the hyperspectral sensor. Hence, this process must be performed by space qualified hardware, having area, power and speed limitations. Moreover, it is important to achieve high compression ratios without compromising the quality of the decompress image. In this manuscript we proposed a new methodology for compressing hyperspectral images based on hyperspectral image fusion concepts. The proposed compression process has two independent steps. The first one is to spatially degrade the remote sensed hyperspectral image to obtain a low resolution hyperspectral image. The second step is to spectrally degrade the remote sensed hyperspectral image to obtain a high resolution multispectral image. These two degraded images are then send to the earth surface, where they must be fused using a fusion algorithm for hyperspectral and multispectral image, in order to recover the remote sensed hyperspectral image. The main advantage of the proposed methodology for compressing remote sensed hyperspectral images is that the compression process, which must be performed on-board, becomes very simple, being the fusion process used to reconstruct image the more complex one. An extra advantage is that the compression ratio can be fixed in advanced. Many simulations have been performed using different fusion algorithms and different methodologies for degrading the hyperspectral image. The results obtained in the simulations performed corroborate the benefits of the proposed methodology.
Biometric image enhancement using decision rule based image fusion techniques

NASA Astrophysics Data System (ADS)

Sagayee, G. Mary Amirtha; Arumugam, S.

2010-02-01

Introducing biometrics into information systems may result in considerable benefits. Most of the researchers confirmed that the finger print is widely used than the iris or face and more over it is the primary choice for most privacy concerned applications. For finger prints applications, choosing proper sensor is at risk. The proposed work deals about, how the image quality can be improved by introducing image fusion technique at sensor levels. The results of the images after introducing the decision rule based image fusion technique are evaluated and analyzed with its entropy levels and root mean square error.
An infrared-visible image fusion scheme based on NSCT and compressed sensing

NASA Astrophysics Data System (ADS)

Zhang, Qiong; Maldague, Xavier

2015-05-01

Image fusion, as a research hot point nowadays in the field of infrared computer vision, has been developed utilizing different varieties of methods. Traditional image fusion algorithms are inclined to bring problems, such as data storage shortage and computational complexity increase, etc. Compressed sensing (CS) uses sparse sampling without knowing the priori knowledge and greatly reconstructs the image, which reduces the cost and complexity of image processing. In this paper, an advanced compressed sensing image fusion algorithm based on non-subsampled contourlet transform (NSCT) is proposed. NSCT provides better sparsity than the wavelet transform in image representation. Throughout the NSCT decomposition, the low-frequency and high-frequency coefficients can be obtained respectively. For the fusion processing of low-frequency coefficients of infrared and visible images , the adaptive regional energy weighting rule is utilized. Thus only the high-frequency coefficients are specially measured. Here we use sparse representation and random projection to obtain the required values of high-frequency coefficients, afterwards, the coefficients of each image block can be fused via the absolute maximum selection rule and/or the regional standard deviation rule. In the reconstruction of the compressive sampling results, a gradient-based iterative algorithm and the total variation (TV) method are employed to recover the high-frequency coefficients. Eventually, the fused image is recovered by inverse NSCT. Both the visual effects and the numerical computation results after experiments indicate that the presented approach achieves much higher quality of image fusion, accelerates the calculations, enhances various targets and extracts more useful information.
Integrative Multi-Spectral Sensor Device for Far-Infrared and Visible Light Fusion

NASA Astrophysics Data System (ADS)

Qiao, Tiezhu; Chen, Lulu; Pang, Yusong; Yan, Gaowei

2018-06-01

Infrared and visible light image fusion technology is a hot spot in the research of multi-sensor fusion technology in recent years. Existing infrared and visible light fusion technologies need to register before fusion because of using two cameras. However, the application effect of the registration technology has yet to be improved. Hence, a novel integrative multi-spectral sensor device is proposed for infrared and visible light fusion, and by using the beam splitter prism, the coaxial light incident from the same lens is projected to the infrared charge coupled device (CCD) and visible light CCD, respectively. In this paper, the imaging mechanism of the proposed sensor device is studied with the process of the signals acquisition and fusion. The simulation experiment, which involves the entire process of the optic system, signal acquisition, and signal fusion, is constructed based on imaging effect model. Additionally, the quality evaluation index is adopted to analyze the simulation result. The experimental results demonstrate that the proposed sensor device is effective and feasible.

Added Value of Contrast-Enhanced Ultrasound on Biopsies of Focal Hepatic Lesions Invisible on Fusion Imaging Guidance

PubMed Central

Kang, Tae Wook; Song, Kyoung Doo; Kim, Mimi; Kim, Seung Soo; Kim, Seong Hyun; Ha, Sang Yun

2017-01-01

Objective To assess whether contrast-enhanced ultrasonography (CEUS) with Sonazoid can improve the lesion conspicuity and feasibility of percutaneous biopsies for focal hepatic lesions invisible on fusion imaging of real-time ultrasonography (US) with computed tomography/magnetic resonance images, and evaluate its impact on clinical decision making. Materials and Methods The Institutional Review Board approved this retrospective study. Between June 2013 and January 2015, 711 US-guided percutaneous biopsies were performed for focal hepatic lesions. Biopsies were performed using CEUS for guidance if lesions were invisible on fusion imaging. We retrospectively evaluated the number of target lesions initially invisible on fusion imaging that became visible after applying CEUS, using a 4-point scale. Technical success rates of biopsies were evaluated based on histopathological results. In addition, the occurrence of changes in clinical decision making was assessed. Results Among 711 patients, 16 patients (2.3%) were included in the study. The median size of target lesions was 1.1 cm (range, 0.5–1.9 cm) in pre-procedural imaging. After CEUS, 15 of 16 (93.8%) focal hepatic lesions were visualized. The conspicuity score was significantly increased after adding CEUS, as compared to that on fusion imaging (p < 0.001). The technical success rate of biopsy was 87.6% (14/16). After biopsy, there were changes in clinical decision making for 11 of 16 patients (68.8%). Conclusion The addition of CEUS could improve the conspicuity of focal hepatic lesions invisible on fusion imaging. This dual guidance using CEUS and fusion imaging may affect patient management via changes in clinical decision-making. PMID:28096725
A transversal approach for patch-based label fusion via matrix completion

PubMed Central

Sanroma, Gerard; Wu, Guorong; Gao, Yaozong; Thung, Kim-Han; Guo, Yanrong; Shen, Dinggang

2015-01-01

Recently, multi-atlas patch-based label fusion has received an increasing interest in the medical image segmentation field. After warping the anatomical labels from the atlas images to the target image by registration, label fusion is the key step to determine the latent label for each target image point. Two popular types of patch-based label fusion approaches are (1) reconstruction-based approaches that compute the target labels as a weighted average of atlas labels, where the weights are derived by reconstructing the target image patch using the atlas image patches; and (2) classification-based approaches that determine the target label as a mapping of the target image patch, where the mapping function is often learned using the atlas image patches and their corresponding labels. Both approaches have their advantages and limitations. In this paper, we propose a novel patch-based label fusion method to combine the above two types of approaches via matrix completion (and hence, we call it transversal). As we will show, our method overcomes the individual limitations of both reconstruction-based and classification-based approaches. Since the labeling confidences may vary across the target image points, we further propose a sequential labeling framework that first labels the highly confident points and then gradually labels more challenging points in an iterative manner, guided by the label information determined in the previous iterations. We demonstrate the performance of our novel label fusion method in segmenting the hippocampus in the ADNI dataset, subcortical and limbic structures in the LONI dataset, and mid-brain structures in the SATA dataset. We achieve more accurate segmentation results than both reconstruction-based and classification-based approaches. Our label fusion method is also ranked 1st in the online SATA Multi-Atlas Segmentation Challenge. PMID:26160394
Human visual system consistent quality assessment for remote sensing image fusion

NASA Astrophysics Data System (ADS)

Liu, Jun; Huang, Junyi; Liu, Shuguang; Li, Huali; Zhou, Qiming; Liu, Junchen

2015-07-01

Quality assessment for image fusion is essential for remote sensing application. Generally used indices require a high spatial resolution multispectral (MS) image for reference, which is not always readily available. Meanwhile, the fusion quality assessments using these indices may not be consistent with the Human Visual System (HVS). As an attempt to overcome this requirement and inconsistency, this paper proposes an HVS-consistent image fusion quality assessment index at the highest resolution without a reference MS image using Gaussian Scale Space (GSS) technology that could simulate the HVS. The spatial details and spectral information of original and fused images are first separated in GSS, and the qualities are evaluated using the proposed spatial and spectral quality index respectively. The overall quality is determined without a reference MS image by a combination of the proposed two indices. Experimental results on various remote sensing images indicate that the proposed index is more consistent with HVS evaluation compared with other widely used indices that may or may not require reference images.
A Remote Sensing Image Fusion Method based on adaptive dictionary learning

NASA Astrophysics Data System (ADS)

He, Tongdi; Che, Zongxi

2018-01-01

This paper discusses using a remote sensing fusion method, based on' adaptive sparse representation (ASP)', to provide improved spectral information, reduce data redundancy and decrease system complexity. First, the training sample set is formed by taking random blocks from the images to be fused, the dictionary is then constructed using the training samples, and the remaining terms are clustered to obtain the complete dictionary by iterated processing at each step. Second, the self-adaptive weighted coefficient rule of regional energy is used to select the feature fusion coefficients and complete the reconstruction of the image blocks. Finally, the reconstructed image blocks are rearranged and an average is taken to obtain the final fused images. Experimental results show that the proposed method is superior to other traditional remote sensing image fusion methods in both spectral information preservation and spatial resolution.
Assessment of Cropping System Diversity in the Fergana Valley Through Image Fusion of Landsat 8 and SENTINEL-1

NASA Astrophysics Data System (ADS)

Dimov, D.; Kuhn, J.; Conrad, C.

2016-06-01

In the transitioning agricultural societies of the world, food security is an essential element of livelihood and economic development with the agricultural sector very often being the major employment factor and income source. Rapid population growth, urbanization, pollution, desertification, soil degradation and climate change pose a variety of threats to a sustainable agricultural development and can be expressed as agricultural vulnerability components. Diverse cropping patterns may help to adapt the agricultural systems to those hazards in terms of increasing the potential yield and resilience to water scarcity. Thus, the quantification of crop diversity using indices like the Simpson Index of Diversity (SID) e.g. through freely available remote sensing data becomes a very important issue. This however requires accurate land use classifications. In this study, the focus is set on the cropping system diversity of garden plots, summer crop fields and orchard plots which are the prevalent agricultural systems in the test area of the Fergana Valley in Uzbekistan. In order to improve the accuracy of land use classification algorithms with low or medium resolution data, a novel processing chain through the hitherto unique fusion of optical and SAR data from the Landsat 8 and Sentinel-1 platforms is proposed. The combination of both sensors is intended to enhance the object's textural and spectral signature rather than just to enhance the spatial context through pansharpening. It could be concluded that the Ehlers fusion algorithm gave the most suitable results. Based on the derived image fusion different object-based image classification algorithms such as SVM, Naïve Bayesian and Random Forest were evaluated whereby the latter one achieved the highest classification accuracy. Subsequently, the SID was applied to measure the diversification of the three main cropping systems.
Image fusion of contrast enhanced ultrasound (CEUS) with computed tomography (CT) or magnetic resonance imaging (MRI) using volume navigation for detection, characterization and planning of therapeutic interventions of liver tumors.

PubMed

Rennert, J; Georgieva, M; Schreyer, A G; Jung, W; Ross, C; Stroszczynski, C; Jung, E M

2011-01-01

To evaluate, whether image fusion of contrast enhanced ultrasound (CEUS) with CT or MRI affects the diagnosis and characterization of liver lesions or the therapeutic strategy of surgical or interventional procedures compared to the preliminary diagnosis. In a retrospective study the image fusion scans of CEUS with contrast enhanced CT or MRI of 100 patients (71 male, mean age 59 years, 0.3-85 years) with benign or malignant liver lesions were evaluated. Fundamental B-scan, color Doppler imaging and CEUS were performed in all patients by an experienced examiner using a multifrequency convex transducer (1-5 MHz, LOGIQ 9/GE) and volume navigation (Vnav). After a bolus injections of up to 2.4 ml SonoVue® (BRACCO, Italy) digital raw data was stored as cine-loops up to 5 min. In 74 patients, CEUS was fused with a pre-existing ceCT, in 26 patients a ceMRI was used. In all 100 patients (100%) the image quality in all modalities (ceCT, ceMRI and CEUS) was excellent or with only minor diagnostic limitations. Regarding the number of lesions revealed in image fusion of CEUS/ceCT/ceMRI and the preceding diagnostic method, concordant results were found in 84 patients. In 12 patients, additional lesions were found using fusion imaging causing subsequently a change of the therapeutical strategy. In 15 out of 21 patients with either concordant or discordant results regarding the number of lesions, image fusion allowed a definite diagnosis due to a continuous documentation of the microcirculation of the tumor and its contrast enhancement. A significant coherency (p < 0.05) among image fusion with either ceCT or ceMRI and CEUS and a subsequent change of therapeutic strategy was found. Image fusion with volume navigation (VNav) of CEUS with ceCT or ceMRI frequently allows a definite localization and diagnosis of hepatic lesions in patients with primary hepatic carcinoma or metastatic diseases. This might cause a change of the therapeutic strategy in many patients with hepatic lesions.
The applicability of holography in forensic identification: a fusion of the traditional optical technique and digital technique.

PubMed

Biwasaka, Hitoshi; Saigusa, Kiyoshi; Aoki, Yasuhiro

2005-03-01

In this study, the applicability of holography in the 3-dimensional recording of forensic objects such as skulls and mandibulae, and the accuracy of the reconstructed 3-D images, were examined. The virtual holographic image, which records the 3-dimensional data of the original object, is visually observed on the other side of the holographic plate, and reproduces the 3-dimensional shape of the object well. Another type of holographic image, the real image, is focused on a frosted glass screen, and cross-sectional images of the object can be observed. When measuring the distances between anatomical reference points using an image-processing software, the average deviations in the holographic images as compared to the actual objects were less than 0.1 mm. Therefore, holography could be useful as a 3-dimensional recording method of forensic objects. Two superimposition systems using holographic images were examined. In the 2D-3D system, the transparent virtual holographic image of an object is directly superimposed onto the digitized photograph of the same object on the LCD monitor. On the other hand, in the video system, the holographic image captured by the CCD camera is superimposed onto the digitized photographic image using a personal computer. We found that the discrepancy between the outlines of the superimposed holographic and photographic dental images using the video system was smaller than that using the 2D-3D system. Holography seemed to perform comparably to the computer graphic system; however, a fusion with the digital technique would expand the utility of holography in superimposition.
A Multi-Objective Decision Making Approach for Solving the Image Segmentation Fusion Problem.

PubMed

Khelifi, Lazhar; Mignotte, Max

2017-08-01

Image segmentation fusion is defined as the set of methods which aim at merging several image segmentations, in a manner that takes full advantage of the complementarity of each one. Previous relevant researches in this field have been impeded by the difficulty in identifying an appropriate single segmentation fusion criterion, providing the best possible, i.e., the more informative, result of fusion. In this paper, we propose a new model of image segmentation fusion based on multi-objective optimization which can mitigate this problem, to obtain a final improved result of segmentation. Our fusion framework incorporates the dominance concept in order to efficiently combine and optimize two complementary segmentation criteria, namely, the global consistency error and the F-measure (precision-recall) criterion. To this end, we present a hierarchical and efficient way to optimize the multi-objective consensus energy function related to this fusion model, which exploits a simple and deterministic iterative relaxation strategy combining the different image segments. This step is followed by a decision making task based on the so-called "technique for order performance by similarity to ideal solution". Results obtained on two publicly available databases with manual ground truth segmentations clearly show that our multi-objective energy-based model gives better results than the classical mono-objective one.
Infrared and visible image fusion using discrete cosine transform and swarm intelligence for surveillance applications

NASA Astrophysics Data System (ADS)

Paramanandham, Nirmala; Rajendiran, Kishore

2018-01-01

A novel image fusion technique is presented for integrating infrared and visible images. Integration of images from the same or various sensing modalities can deliver the required information that cannot be delivered by viewing the sensor outputs individually and consecutively. In this paper, a swarm intelligence based image fusion technique using discrete cosine transform (DCT) domain is proposed for surveillance application which integrates the infrared image with the visible image for generating a single informative fused image. Particle swarm optimization (PSO) is used in the fusion process for obtaining the optimized weighting factor. These optimized weighting factors are used for fusing the DCT coefficients of visible and infrared images. Inverse DCT is applied for obtaining the initial fused image. An enhanced fused image is obtained through adaptive histogram equalization for a better visual understanding and target detection. The proposed framework is evaluated using quantitative metrics such as standard deviation, spatial frequency, entropy and mean gradient. The experimental results demonstrate the outperformance of the proposed algorithm over many other state- of- the- art techniques reported in literature.
Infrared and visible image fusion based on robust principal component analysis and compressed sensing

NASA Astrophysics Data System (ADS)

Li, Jun; Song, Minghui; Peng, Yuanxi

2018-03-01

Current infrared and visible image fusion methods do not achieve adequate information extraction, i.e., they cannot extract the target information from infrared images while retaining the background information from visible images. Moreover, most of them have high complexity and are time-consuming. This paper proposes an efficient image fusion framework for infrared and visible images on the basis of robust principal component analysis (RPCA) and compressed sensing (CS). The novel framework consists of three phases. First, RPCA decomposition is applied to the infrared and visible images to obtain their sparse and low-rank components, which represent the salient features and background information of the images, respectively. Second, the sparse and low-rank coefficients are fused by different strategies. On the one hand, the measurements of the sparse coefficients are obtained by the random Gaussian matrix, and they are then fused by the standard deviation (SD) based fusion rule. Next, the fused sparse component is obtained by reconstructing the result of the fused measurement using the fast continuous linearized augmented Lagrangian algorithm (FCLALM). On the other hand, the low-rank coefficients are fused using the max-absolute rule. Subsequently, the fused image is superposed by the fused sparse and low-rank components. For comparison, several popular fusion algorithms are tested experimentally. By comparing the fused results subjectively and objectively, we find that the proposed framework can extract the infrared targets while retaining the background information in the visible images. Thus, it exhibits state-of-the-art performance in terms of both fusion effects and timeliness.
Segmentation Fusion Techniques with Application to Plenoptic Images: A Survey.

NASA Astrophysics Data System (ADS)

Evin, D.; Hadad, A.; Solano, A.; Drozdowicz, B.

2016-04-01

The segmentation of anatomical and pathological structures plays a key role in the characterization of clinically relevant evidence from digital images. Recently, plenoptic imaging has emerged as a new promise to enrich the diagnostic potential of conventional photography. Since the plenoptic images comprises a set of slightly different versions of the target scene, we propose to make use of those images to improve the segmentation quality in relation to the scenario of a single image segmentation. The problem of finding a segmentation solution from multiple images of a single scene, is called segmentation fusion. This paper reviews the issue of segmentation fusion in order to find solutions that can be applied to plenoptic images, particularly images from the ophthalmological domain.
[An improved low spectral distortion PCA fusion method].

PubMed

Peng, Shi; Zhang, Ai-Wu; Li, Han-Lun; Hu, Shao-Xing; Meng, Xian-Gang; Sun, Wei-Dong

2013-10-01

Aiming at the spectral distortion produced in PCA fusion process, the present paper proposes an improved low spectral distortion PCA fusion method. This method uses NCUT (normalized cut) image segmentation algorithm to make a complex hyperspectral remote sensing image into multiple sub-images for increasing the separability of samples, which can weaken the spectral distortions of traditional PCA fusion; Pixels similarity weighting matrix and masks were produced by using graph theory and clustering theory. These masks are used to cut the hyperspectral image and high-resolution image into some sub-region objects. All corresponding sub-region objects between the hyperspectral image and high-resolution image are fused by using PCA method, and all sub-regional integration results are spliced together to produce a new image. In the experiment, Hyperion hyperspectral data and Rapid Eye data were used. And the experiment result shows that the proposed method has the same ability to enhance spatial resolution and greater ability to improve spectral fidelity performance.
Fusion of magnetic resonance angiography and magnetic resonance imaging for surgical planning for meningioma--technical note.

PubMed

Kashimura, Hiroshi; Ogasawara, Kuniaki; Arai, Hiroshi; Beppu, Takaaki; Inoue, Takashi; Takahashi, Tsutomu; Matsuda, Koichi; Takahashi, Yujiro; Fujiwara, Shunrou; Ogawa, Akira

2008-09-01

A fusion technique for magnetic resonance (MR) angiography and MR imaging was developed to help assess the peritumoral angioarchitecture during surgical planning for meningioma. Three-dimensional time-of-flight (3D-TOF) and 3D-spoiled gradient recalled (SPGR) datasets were obtained from 10 patients with intracranial meningioma, and fused using newly developed volume registration and visualization software. Maximum intensity projection (MIP) images from 3D-TOF MR angiography and axial SPGR MR imaging were displayed at the same time on the monitor. Selecting a vessel on the real-time MIP image indicated the corresponding points on the axial image automatically. Fusion images showed displacement of the anterior cerebral or middle cerebral artery in 7 patients and encasement of the anterior cerebral arteries in 1 patient, with no relationship between the main arterial trunk and tumor in 2 patients. Fusion of MR angiography and MR imaging can clarify relationships between the intracranial vasculature and meningioma, and may be helpful for surgical planning for meningioma.
Multitask saliency detection model for synthetic aperture radar (SAR) image and its application in SAR and optical image fusion

NASA Astrophysics Data System (ADS)

Liu, Chunhui; Zhang, Duona; Zhao, Xintao

2018-03-01

Saliency detection in synthetic aperture radar (SAR) images is a difficult problem. This paper proposed a multitask saliency detection (MSD) model for the saliency detection task of SAR images. We extract four features of the SAR image, which include the intensity, orientation, uniqueness, and global contrast, as the input of the MSD model. The saliency map is generated by the multitask sparsity pursuit, which integrates the multiple features collaboratively. Detection of different scale features is also taken into consideration. Subjective and objective evaluation of the MSD model verifies its effectiveness. Based on the saliency maps obtained by the MSD model, we apply the saliency map of the SAR image to the SAR and color optical image fusion. The experimental results of real data show that the saliency map obtained by the MSD model helps to improve the fusion effect, and the salient areas in the SAR image can be highlighted in the fusion results.
A GIHS-based spectral preservation fusion method for remote sensing images using edge restored spectral modulation

NASA Astrophysics Data System (ADS)

Zhou, Xiran; Liu, Jun; Liu, Shuguang; Cao, Lei; Zhou, Qiming; Huang, Huawen

2014-02-01

High spatial resolution and spectral fidelity are basic standards for evaluating an image fusion algorithm. Numerous fusion methods for remote sensing images have been developed. Some of these methods are based on the intensity-hue-saturation (IHS) transform and the generalized IHS (GIHS), which may cause serious spectral distortion. Spectral distortion in the GIHS is proven to result from changes in saturation during fusion. Therefore, reducing such changes can achieve high spectral fidelity. A GIHS-based spectral preservation fusion method that can theoretically reduce spectral distortion is proposed in this study. The proposed algorithm consists of two steps. The first step is spectral modulation (SM), which uses the Gaussian function to extract spatial details and conduct SM of multispectral (MS) images. This method yields a desirable visual effect without requiring histogram matching between the panchromatic image and the intensity of the MS image. The second step uses the Gaussian convolution function to restore lost edge details during SM. The proposed method is proven effective and shown to provide better results compared with other GIHS-based methods.
Fusion of laser and image sensory data for 3-D modeling of the free navigation space

NASA Technical Reports Server (NTRS)

Mass, M.; Moghaddamzadeh, A.; Bourbakis, N.

1994-01-01

A fusion technique which combines two different types of sensory data for 3-D modeling of a navigation space is presented. The sensory data is generated by a vision camera and a laser scanner. The problem of different resolutions for these sensory data was solved by reduced image resolution, fusion of different data, and use of a fuzzy image segmentation technique.
Diagnostic Value of Software-Based Image Fusion of Computed Tomography and F18-FDG PET Scans in Patients with Malignant Lymphoma

PubMed Central

Henninger, B.; Putzer, D.; Kendler, D.; Uprimny, C.; Virgolini, I.; Gunsilius, E.; Bale, R.

2012-01-01

Aim. The purpose of this study was to evaluate the accuracy of 2-deoxy-2-[fluorine-18]fluoro-D-glucose (FDG) positron emission tomography (PET), computed tomography (CT), and software-based image fusion of both modalities in the imaging of non-Hodgkin's lymphoma (NHL) and Hodgkin's disease (HD). Methods. 77 patients with NHL (n = 58) or HD (n = 19) underwent a FDG PET scan, a contrast-enhanced CT, and a subsequent digital image fusion during initial staging or followup. 109 examinations of each modality were evaluated and compared to each other. Conventional staging procedures, other imaging techniques, laboratory screening, and follow-up data constituted the reference standard for comparison with image fusion. Sensitivity and specificity were calculated for CT and PET separately. Results. Sensitivity and specificity for detecting malignant lymphoma were 90% and 76% for CT and 94% and 91% for PET, respectively. A lymph node region-based analysis (comprising 14 defined anatomical regions) revealed a sensitivity of 81% and a specificity of 97% for CT and 96% and 99% for FDG PET, respectively. Only three of 109 image fusion findings needed further evaluation (false positive). Conclusion. Digital fusion of PET and CT improves the accuracy of staging, restaging, and therapy monitoring in patients with malignant lymphoma and may reduce the need for invasive diagnostic procedures. PMID:22654631
Molecular imaging of malignant tumor metabolism: whole-body image fusion of DWI/CT vs. PET/CT.

PubMed

Reiner, Caecilia S; Fischer, Michael A; Hany, Thomas; Stolzmann, Paul; Nanz, Daniel; Donati, Olivio F; Weishaupt, Dominik; von Schulthess, Gustav K; Scheffel, Hans

2011-08-01

To prospectively investigate the technical feasibility and performance of image fusion for whole-body diffusion-weighted imaging (wbDWI) and computed tomography (CT) to detect metastases using hybrid positron emission tomography/computed tomography (PET/CT) as reference standard. Fifty-two patients (60 ± 14 years; 18 women) with different malignant tumor disease examined by PET/CT for clinical reasons consented to undergo additional wbDWI at 1.5 Tesla. WbDWI was performed using a diffusion-weighted single-shot echo-planar imaging during free breathing. Images at b = 0 s/mm(2) and b = 700 s/mm(2) were acquired and apparent diffusion coefficient (ADC) maps were generated. Image fusion of wbDWI and CT (from PET/CT scan) was performed yielding for wbDWI/CT fused image data. One radiologist rated the success of image fusion and diagnostic image quality. The presence or absence of metastases on wbDWI/CT fused images was evaluated together with the separate wbDWI and CT images by two different, independent radiologists blinded to results from PET/CT. Detection rate and positive predictive values for diagnosing metastases was calculated. PET/CT examinations were used as reference standard. PET/CT identified 305 malignant lesions in 39 of 52 (75%) patients. WbDWI/CT image fusion was technically successful and yielded diagnostic image quality in 73% and 92% of patients, respectively. Interobserver agreement for the evaluation of wbDWI/CT images was κ = 0.78. WbDWI/CT identified 270 metastases in 43 of 52 (83%) patients. Overall detection rate and positive predictive value of wbDWI/CT was 89% (95% CI, 0.85-0.92) and 94% (95% CI, 0.92-0.97), respectively. WbDWI/CT image fusion is technically feasible in a clinical setting and allows the diagnostic assessment of metastatic tumor disease detecting nine of 10 lesions as compared with PET/CT. Copyright © 2011 AUR. Published by Elsevier Inc. All rights reserved.
Improving Echo-Guided Procedures Using an Ultrasound-CT Image Fusion System.

PubMed

Diana, Michele; Halvax, Peter; Mertz, Damien; Legner, Andras; Brulé, Jean-Marcel; Robinet, Eric; Mutter, Didier; Pessaux, Patrick; Marescaux, Jacques

2015-06-01

Image fusion between ultrasound (US) and computed tomography (CT) scan or magnetic resonance can increase operator accuracy in targeting liver lesions, particularly when those are undetectable with US alone. We have developed a modular gel to simulate hepatic solid lesions for educational purposes in imaging and minimally invasive ablation techniques. We aimed to assess the impact of image fusion in targeting artificial hepatic lesions during the hands-on part of 2 courses (basic and advanced) in hepatobiliary surgery. Under US guidance, 10 fake tumors of various sizes were created in the livers of 2 pigs, by percutaneous injection of a biocompatible gel engineered to be hyperdense on CT scanning and barely detectable on US. A CT scan was obtained and a CT-US image fusion was performed using the ACUSON S3000 US system (Siemens Healthcare, Germany). A total of 12 blinded course attendants, were asked in turn to perform a 10-minute liver scan with US alone followed by a 10-minute scan using image fusion. Using US alone, the expert managed to identify all lesions successfully. The true positive rate for course attendants with US alone was 14/36 and 2/24 in the advanced and basic courses, respectively. The total number of false positives identified was 26. With image fusion, the rate of true positives significantly increased to 31/36 (P < .001) in the advanced group and 16/24 in the basic group (P < .001). The total number of false positives, considering all participants, decreased to 4 (P < .001). Image fusion significantly increases accuracy in targeting hepatic lesions and might improve echo-guided procedures. © The Author(s) 2015.
Multi-atlas segmentation with joint label fusion and corrective learning—an open source implementation

PubMed Central

Wang, Hongzhi; Yushkevich, Paul A.

2013-01-01

Label fusion based multi-atlas segmentation has proven to be one of the most competitive techniques for medical image segmentation. This technique transfers segmentations from expert-labeled images, called atlases, to a novel image using deformable image registration. Errors produced by label transfer are further reduced by label fusion that combines the results produced by all atlases into a consensus solution. Among the proposed label fusion strategies, weighted voting with spatially varying weight distributions derived from atlas-target intensity similarity is a simple and highly effective label fusion technique. However, one limitation of most weighted voting methods is that the weights are computed independently for each atlas, without taking into account the fact that different atlases may produce similar label errors. To address this problem, we recently developed the joint label fusion technique and the corrective learning technique, which won the first place of the 2012 MICCAI Multi-Atlas Labeling Challenge and was one of the top performers in 2013 MICCAI Segmentation: Algorithms, Theory and Applications (SATA) challenge. To make our techniques more accessible to the scientific research community, we describe an Insight-Toolkit based open source implementation of our label fusion methods. Our implementation extends our methods to work with multi-modality imaging data and is more suitable for segmentation problems with multiple labels. We demonstrate the usage of our tools through applying them to the 2012 MICCAI Multi-Atlas Labeling Challenge brain image dataset and the 2013 SATA challenge canine leg image dataset. We report the best results on these two datasets so far. PMID:24319427

Image fusion method based on regional feature and improved bidimensional empirical mode decomposition

NASA Astrophysics Data System (ADS)

Qin, Xinqiang; Hu, Gang; Hu, Kai

2018-01-01

The decomposition of multiple source images using bidimensional empirical mode decomposition (BEMD) often produces mismatched bidimensional intrinsic mode functions, either by their number or their frequency, making image fusion difficult. A solution to this problem is proposed using a fixed number of iterations and a union operation in the sifting process. By combining the local regional features of the images, an image fusion method has been developed. First, the source images are decomposed using the proposed BEMD to produce the first intrinsic mode function (IMF) and residue component. Second, for the IMF component, a selection and weighted average strategy based on local area energy is used to obtain a high-frequency fusion component. Third, for the residue component, a selection and weighted average strategy based on local average gray difference is used to obtain a low-frequency fusion component. Finally, the fused image is obtained by applying the inverse BEMD transform. Experimental results show that the proposed algorithm provides superior performance over methods based on wavelet transform, line and column-based EMD, and complex empirical mode decomposition, both in terms of visual quality and objective evaluation criteria.
Diagnostic performance of fluorodeoxyglucose positron emission tomography/magnetic resonance imaging fusion images of gynecological malignant tumors: comparison with positron emission tomography/computed tomography.

PubMed

Nakajo, Kazuya; Tatsumi, Mitsuaki; Inoue, Atsuo; Isohashi, Kayako; Higuchi, Ichiro; Kato, Hiroki; Imaizumi, Masao; Enomoto, Takayuki; Shimosegawa, Eku; Kimura, Tadashi; Hatazawa, Jun

2010-02-01

We compared the diagnostic accuracy of fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) and PET/magnetic resonance imaging (MRI) fusion images for gynecological malignancies. A total of 31 patients with gynecological malignancies were enrolled. FDG-PET images were fused to CT, T1- and T2-weighted images (T1WI, T2WI). PET-MRI fusion was performed semiautomatically. We performed three types of evaluation to demonstrate the usefulness of PET/MRI fusion images in comparison with that of inline PET/CT as follows: depiction of the uterus and the ovarian lesions on CT or MRI mapping images (first evaluation); additional information for lesion localization with PET and mapping images (second evaluation); and the image quality of fusion on interpretation (third evaluation). For the first evaluation, the score for T2WI (4.68 +/- 0.65) was significantly higher than that for CT (3.54 +/- 1.02) or T1WI (3.71 +/- 0.97) (P < 0.01). For the second evaluation, the scores for the localization of FDG accumulation showing that T2WI (2.74 +/- 0.57) provided significantly more additional information for the identification of anatomical sites of FDG accumulation than did CT (2.06 +/- 0.68) or T1WI (2.23 +/- 0.61) (P < 0.01). For the third evaluation, the three-point rating scale for the patient group as a whole demonstrated that PET/T2WI (2.72 +/- 0.54) localized the lesion significantly more convincingly than PET/CT (2.23 +/- 0.50) or PET/T1WI (2.29 +/- 0.53) (P < 0.01). PET/T2WI fusion images are superior for the detection and localization of gynecological malignancies.
The use of 3D image fusion for percutaneous transluminal angioplasty and stenting of iliac artery obstructions: validation of the technique and systematic review of literature.

PubMed

Goudeketting, Seline R; Heinen, Stefan G; van den Heuvel, Daniel A; van Strijen, Marco J; de Haan, Michiel W; Slump, Cornelis H; de Vries, Jean-Paul P

2018-02-01

The effect of the insertion of guidewires and catheters on fusion accuracy of the three-dimensional (3D) image fusion technique during iliac percutaneous transluminal angioplasty (PTA) procedures has not yet been investigated. Technical validation of the 3D fusion technique was evaluated in 11 patients with common and/or external iliac artery lesions. A preprocedural contrast-enhanced magnetic resonance angiogram (CE-MRA) was segmented and manually registered to a cone-beam computed tomography image created at the beginning of the procedure for each patient. The treating physician visually scored the fusion accuracy (i.e., accurate [<2 mm], mismatch [2-5 mm], or inaccurate [>5 mm]) of the entire vasculature of the overlay with respect to the digital subtraction angiography (DSA) directly after the first obtained DSA. Contours of the vasculature of the fusion images and DSAs were drawn after the procedure. The cranial-caudal, lateral-medial, and absolute displacement were calculated between the vessel centerlines. To determine the influence of the catheters, displacement of the catheterized iliac trajectories were compared with the noncatheterized trajectories. Electronic databases were systematically searched for available literature published between January 2010 till August 2017. The mean registration error for all iliac trajectories (N.=20) was small (4.0±2.5 mm). No significant difference in fusion displacement was observed between catheterized (N.=11) and noncatheterized (N.=9) iliac arteries. The systematic literature search yielded 2 manuscripts with a total of 22 patients. The methodological quality of these studies was poor (≤11 MINORS Score), mainly due to a lack of a control group. Accurate image fusion based on preprocedural CE-MRA is possible and could potentially be of help in iliac PTA procedures. The flexible guidewires and angiographic catheters, routinely used during endovascular procedures of iliac arteries, did not cause significant displacement that influenced the image fusion. Current literature on 3D image fusion in iliac PTA procedures is of limited methodological quality.
Mosaicing of single plane illumination microscopy images using groupwise registration and fast content-based image fusion

NASA Astrophysics Data System (ADS)

Preibisch, Stephan; Rohlfing, Torsten; Hasak, Michael P.; Tomancak, Pavel

2008-03-01

Single Plane Illumination Microscopy (SPIM; Huisken et al., Nature 305(5686):1007-1009, 2004) is an emerging microscopic technique that enables live imaging of large biological specimens in their entirety. By imaging the living biological sample from multiple angles SPIM has the potential to achieve isotropic resolution throughout even relatively large biological specimens. For every angle, however, only a relatively shallow section of the specimen is imaged with high resolution, whereas deeper regions appear increasingly blurred. In order to produce a single, uniformly high resolution image, we propose here an image mosaicing algorithm that combines state of the art groupwise image registration for alignment with content-based image fusion to prevent degrading of the fused image due to regional blurring of the input images. For the registration stage, we introduce an application-specific groupwise transformation model that incorporates per-image as well as groupwise transformation parameters. We also propose a new fusion algorithm based on Gaussian filters, which is substantially faster than fusion based on local image entropy. We demonstrate the performance of our mosaicing method on data acquired from living embryos of the fruit fly, Drosophila, using four and eight angle acquisitions.
Operational data fusion framework for building frequent Landsat-like imagery in a cloudy region

USDA-ARS?s Scientific Manuscript database

An operational data fusion framework is built to generate dense time-series Landsat-like images for a cloudy region by fusing Moderate Resolution Imaging Spectroradiometer (MODIS) data products and Landsat imagery. The Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) is integrated in ...
Aperture tolerances for neutron-imaging systems in inertial confinement fusion.

PubMed

Ghilea, M C; Sangster, T C; Meyerhofer, D D; Lerche, R A; Disdier, L

2008-02-01

Neutron-imaging systems are being considered as an ignition diagnostic for the National Ignition Facility (NIF) [Hogan et al., Nucl. Fusion 41, 567 (2001)]. Given the importance of these systems, a neutron-imaging design tool is being used to quantify the effects of aperture fabrication and alignment tolerances on reconstructed neutron images for inertial confinement fusion. The simulations indicate that alignment tolerances of more than 1 mrad would introduce measurable features in a reconstructed image for both pinholes and penumbral aperture systems. These simulations further show that penumbral apertures are several times less sensitive to fabrication errors than pinhole apertures.
An object-oriented framework for medical image registration, fusion, and visualization.

PubMed

Zhu, Yang-Ming; Cochoff, Steven M

2006-06-01

An object-oriented framework for image registration, fusion, and visualization was developed based on the classic model-view-controller paradigm. The framework employs many design patterns to facilitate legacy code reuse, manage software complexity, and enhance the maintainability and portability of the framework. Three sample applications built a-top of this framework are illustrated to show the effectiveness of this framework: the first one is for volume image grouping and re-sampling, the second one is for 2D registration and fusion, and the last one is for visualization of single images as well as registered volume images.
Diagnostic Accuracy of Multiparametric Magnetic Resonance Imaging and Fusion Guided Targeted Biopsy Evaluated by Transperineal Template Saturation Prostate Biopsy for the Detection and Characterization of Prostate Cancer.

PubMed

Mortezavi, Ashkan; Märzendorfer, Olivia; Donati, Olivio F; Rizzi, Gianluca; Rupp, Niels J; Wettstein, Marian S; Gross, Oliver; Sulser, Tullio; Hermanns, Thomas; Eberli, Daniel

2018-02-21

We evaluated the diagnostic accuracy of multiparametric magnetic resonance imaging and multiparametric magnetic resonance imaging/transrectal ultrasound fusion guided targeted biopsy against that of transperineal template saturation prostate biopsy to detect prostate cancer. We retrospectively analyzed the records of 415 men who consecutively presented for prostate biopsy between November 2014 and September 2016 at our tertiary care center. Multiparametric magnetic resonance imaging was performed using a 3 Tesla device without an endorectal coil, followed by transperineal template saturation prostate biopsy with the BiopSee® fusion system. Additional fusion guided targeted biopsy was done in men with a suspicious lesion on multiparametric magnetic resonance imaging, defined as Likert score 3 to 5. Any Gleason pattern 4 or greater was defined as clinically significant prostate cancer. The detection rates of multiparametric magnetic resonance imaging and fusion guided targeted biopsy were compared with the detection rate of transperineal template saturation prostate biopsy using the McNemar test. We obtained a median of 40 (range 30 to 55) and 3 (range 2 to 4) transperineal template saturation prostate biopsy and fusion guided targeted biopsy cores, respectively. Of the 124 patients (29.9%) without a suspicious lesion on multiparametric magnetic resonance imaging 32 (25.8%) were found to have clinically significant prostate cancer on transperineal template saturation prostate biopsy. Of the 291 patients (70.1%) with a Likert score of 3 to 5 clinically significant prostate cancer was detected in 129 (44.3%) by multiparametric magnetic resonance imaging fusion guided targeted biopsy, in 176 (60.5%) by transperineal template saturation prostate biopsy and in 187 (64.3%) by the combined approach. Overall 58 cases (19.9%) of clinically significant prostate cancer would have been missed if fusion guided targeted biopsy had been performed exclusively. The sensitivity of multiparametric magnetic resonance imaging and fusion guided targeted biopsy for clinically significant prostate cancer was 84.6% and 56.7% with a negative likelihood ratio of 0.35 and 0.46, respectively. Multiparametric magnetic resonance imaging alone should not be performed as a triage test due to a substantial number of false-negative cases with clinically significant prostate cancer. Systematic biopsy outperformed fusion guided targeted biopsy. Therefore, it will remain crucial in the diagnostic pathway of prostate cancer. Copyright © 2018 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.
Magnetic resonance and computed tomography image fusion technology in patients with Parkinson's disease after deep brain stimulation.

PubMed

Xia, Jun; He, Pin; Cai, Xiaodong; Zhang, Doudou; Xie, Ni

2017-10-15

Electrode position after deep brain stimulation (DBS) for Parkinson's disease (PD) needs to be confirmed, but there are concerns about the risk of postoperative magnetic resonance imaging (MRI) after DBS. These issues could be avoided by fusion images obtained from preoperative MRI and postoperative computed tomography (CT). This study aimed to investigate image fusion technology for displaying the position of the electrodes compared with postoperative MRI. This was a retrospective study of 32 patients with PD treated with bilateral subthalamic nucleus (STN) DBS between April 2015 and March 2016. The postoperative (same day) CT and preoperative MRI were fused using the Elekta Leksell 10.1 planning workstation (Elekta Instruments, Stockholm, Sweden). The position of the electrodes was compared between the fusion images and postoperative 1-2-week MRI. The position of the electrodes was highly correlated between the fusion and postoperative MRI (all r between 0.865 and 0.996; all P<0.001). The differences of the left electrode position in the lateral and vertical planes was significantly different between the two methods (0.30 and 0.24mm, respectively, both P<0.05), but there were no significant differences for the other electrode and planes (all P>0.05). The position of the electrodes was highly correlated between the fusion and postoperative MRI. The CT-MRI fusion images could be used to avoid the potential risks of MRI after DBS in patients with PD. Copyright © 2017. Published by Elsevier B.V.
Progressive Label Fusion Framework for Multi-atlas Segmentation by Dictionary Evolution

PubMed Central

Song, Yantao; Wu, Guorong; Sun, Quansen; Bahrami, Khosro; Li, Chunming; Shen, Dinggang

2015-01-01

Accurate segmentation of anatomical structures in medical images is very important in neuroscience studies. Recently, multi-atlas patch-based label fusion methods have achieved many successes, which generally represent each target patch from an atlas patch dictionary in the image domain and then predict the latent label by directly applying the estimated representation coefficients in the label domain. However, due to the large gap between these two domains, the estimated representation coefficients in the image domain may not stay optimal for the label fusion. To overcome this dilemma, we propose a novel label fusion framework to make the weighting coefficients eventually to be optimal for the label fusion by progressively constructing a dynamic dictionary in a layer-by-layer manner, where a sequence of intermediate patch dictionaries gradually encode the transition from the patch representation coefficients in image domain to the optimal weights for label fusion. Our proposed framework is general to augment the label fusion performance of the current state-of-the-art methods. In our experiments, we apply our proposed method to hippocampus segmentation on ADNI dataset and achieve more accurate labeling results, compared to the counterpart methods with single-layer dictionary. PMID:26942233
Progressive Label Fusion Framework for Multi-atlas Segmentation by Dictionary Evolution.

PubMed

Song, Yantao; Wu, Guorong; Sun, Quansen; Bahrami, Khosro; Li, Chunming; Shen, Dinggang

2015-10-01

Accurate segmentation of anatomical structures in medical images is very important in neuroscience studies. Recently, multi-atlas patch-based label fusion methods have achieved many successes, which generally represent each target patch from an atlas patch dictionary in the image domain and then predict the latent label by directly applying the estimated representation coefficients in the label domain. However, due to the large gap between these two domains, the estimated representation coefficients in the image domain may not stay optimal for the label fusion. To overcome this dilemma, we propose a novel label fusion framework to make the weighting coefficients eventually to be optimal for the label fusion by progressively constructing a dynamic dictionary in a layer-by-layer manner, where a sequence of intermediate patch dictionaries gradually encode the transition from the patch representation coefficients in image domain to the optimal weights for label fusion. Our proposed framework is general to augment the label fusion performance of the current state-of-the-art methods. In our experiments, we apply our proposed method to hippocampus segmentation on ADNI dataset and achieve more accurate labeling results, compared to the counterpart methods with single-layer dictionary.
An investigation of density measurement method for yarn-dyed woven fabrics based on dual-side fusion technique

NASA Astrophysics Data System (ADS)

Zhang, Rui; Xin, Binjie

2016-08-01

Yarn density is always considered as the fundamental structural parameter used for the quality evaluation of woven fabrics. The conventional yarn density measurement method is based on one-side analysis. In this paper, a novel density measurement method is developed for yarn-dyed woven fabrics based on a dual-side fusion technique. Firstly, a lab-used dual-side imaging system is established to acquire both face-side and back-side images of woven fabric and the affine transform is used for the alignment and fusion of the dual-side images. Then, the color images of the woven fabrics are transferred from the RGB to the CIE-Lab color space, and the intensity information of the image extracted from the L component is used for texture fusion and analysis. Subsequently, three image fusion methods are developed and utilized to merge the dual-side images: the weighted average method, wavelet transform method and Laplacian pyramid blending method. The fusion efficacy of each method is evaluated by three evaluation indicators and the best of them is selected to do the reconstruction of the complete fabric texture. Finally, the yarn density of the fused image is measured based on the fast Fourier transform, and the yarn alignment image could be reconstructed using the inverse fast Fourier transform. Our experimental results show that the accuracy of density measurement by using the proposed method is close to 99.44% compared with the traditional method and the robustness of this new proposed method is better than that of conventional analysis methods.
Introduction to clinical and laboratory (small-animal) image registration and fusion.

PubMed

Zanzonico, Pat B; Nehmeh, Sadek A

2006-01-01

Imaging has long been a vital component of clinical medicine and, increasingly, of biomedical research in small-animals. Clinical and laboratory imaging modalities can be divided into two general categories, structural (or anatomical) and functional (or physiological). The latter, in particular, has spawned what has come to be known as "molecular imaging". Image registration and fusion have rapidly emerged as invaluable components of both clinical and small-animal imaging and has lead to the development and marketing of a variety of multi-modality, e.g. PET-CT, devices which provide registered and fused three-dimensional image sets. This paper briefly reviews the basics of image registration and fusion and available clinical and small-animal multi-modality instrumentation.
Evaluation techniques and metrics for assessment of pan+MSI fusion (pansharpening)

NASA Astrophysics Data System (ADS)

Mercovich, Ryan A.

2015-05-01

Fusion of broadband panchromatic data with narrow band multispectral data - pansharpening - is a common and often studied problem in remote sensing. Many methods exist to produce data fusion results with the best possible spatial and spectral characteristics, and a number have been commercially implemented. This study examines the output products of 4 commercial implementations with regard to their relative strengths and weaknesses for a set of defined image characteristics and analyst use-cases. Image characteristics used are spatial detail, spatial quality, spectral integrity, and composite color quality (hue and saturation), and analyst use-cases included a variety of object detection and identification tasks. The imagery comes courtesy of the RIT SHARE 2012 collect. Two approaches are used to evaluate the pansharpening methods, analyst evaluation or qualitative measure and image quality metrics or quantitative measures. Visual analyst evaluation results are compared with metric results to determine which metrics best measure the defined image characteristics and product use-cases and to support future rigorous characterization the metrics' correlation with the analyst results. Because pansharpening represents a trade between adding spatial information from the panchromatic image, and retaining spectral information from the MSI channels, the metrics examined are grouped into spatial improvement metrics and spectral preservation metrics. A single metric to quantify the quality of a pansharpening method would necessarily be a combination of weighted spatial and spectral metrics based on the importance of various spatial and spectral characteristics for the primary task of interest. Appropriate metrics and weights for such a combined metric are proposed here, based on the conducted analyst evaluation. Additionally, during this work, a metric was developed specifically focused on assessment of spatial structure improvement relative to a reference image and independent of scene content. Using analysis of Fourier transform images, a measure of high-frequency content is computed in small sub-segments of the image. The average increase in high-frequency content across the image is used as the metric, where averaging across sub-segments combats the scene dependent nature of typical image sharpness techniques. This metric had an improved range of scores, better representing difference in the test set than other common spatial structure metrics.
Standardized 2D ultrasound versus 3D/4D ultrasound and image fusion for measurement of aortic aneurysm diameter in follow-up after EVAR.

PubMed

Pfister, Karin; Schierling, Wilma; Jung, Ernst Michael; Apfelbeck, Hanna; Hennersperger, Christoph; Kasprzak, Piotr M

2016-01-01

To compare standardised 2D ultrasound (US) to the novel ultrasonographic imaging techniques 3D/4D US and image fusion (combined real-time display of B mode and CT scan) for routine measurement of aortic diameter in follow-up after endovascular aortic aneurysm repair (EVAR). 300 measurements were performed on 20 patients after EVAR by one experienced sonographer (3rd degree of the German society of ultrasound (DEGUM)) with a high-end ultrasound machine and a convex probe (1-5 MHz). An internally standardized scanning protocol of the aortic aneurysm diameter in B mode used a so called leading-edge method. In summary, five different US methods (2D, 3D free-hand, magnetic field tracked 3D - Curefab™, 4D volume sweep, image fusion), each including contrast-enhanced ultrasound (CEUS), were used for measurement of the maximum aortic aneurysm diameter. Standardized 2D sonography was the defined reference standard for statistical analysis. CEUS was used for endoleak detection. Technical success was 100%. In augmented transverse imaging the mean aortic anteroposterior (AP) diameter was 4.0±1.3 cm for 2D US, 4.0±1.2 cm for 3D Curefab™, and 3.9±1.3 cm for 4D US and 4.0±1.2 for image fusion. The mean differences were below 1 mm (0.2-0.9 mm). Concerning estimation of aneurysm growth, agreement was found between 2D, 3D and 4D US in 19 of the 20 patients (95%). Definitive decision could always be made by image fusion. CEUS was combined with all methods and detected two out of the 20 patients (10%) with an endoleak type II. In one case, endoleak feeding arteries remained unclear with 2D CEUS but could be clearly localized by 3D CEUS and image fusion. Standardized 2D US allows adequate routine follow-up of maximum aortic aneurysm diameter after EVAR. Image Fusion enables a definitive statement about aneurysm growth without the need for new CT imaging by combining the postoperative CT scan with real-time B mode in a dual image display. 3D/4D CEUS and image fusion can improve endoleak characterization in selected cases but are not mandatory for routine practice.
Fusion of PAN and multispectral remote sensing images in shearlet domain by considering regional metrics

NASA Astrophysics Data System (ADS)

Poobalasubramanian, Mangalraj; Agrawal, Anupam

2016-10-01

The presented work proposes fusion of panchromatic and multispectral images in a shearlet domain. The proposed fusion rules rely on the regional considerations which makes the system efficient in terms of spatial enhancement. The luminance hue saturation-based color conversion system is utilized to avoid spectral distortions. The proposed fusion method is tested on Worldview2 and Ikonos datasets, and the proposed method is compared against other methodologies. The proposed fusion method performs well against the other compared methods in terms of subjective and objective evaluations.
Enhancement of low light level images using color-plus-mono dual camera.

PubMed

Jung, Yong Ju

2017-05-15

In digital photography, the improvement of imaging quality in low light shooting is one of the users' needs. Unfortunately, conventional smartphone cameras that use a single, small image sensor cannot provide satisfactory quality in low light level images. A color-plus-mono dual camera that consists of two horizontally separate image sensors, which simultaneously captures both a color and mono image pair of the same scene, could be useful for improving the quality of low light level images. However, an incorrect image fusion between the color and mono image pair could also have negative effects, such as the introduction of severe visual artifacts in the fused images. This paper proposes a selective image fusion technique that applies an adaptive guided filter-based denoising and selective detail transfer to only those pixels deemed reliable with respect to binocular image fusion. We employ a dissimilarity measure and binocular just-noticeable-difference (BJND) analysis to identify unreliable pixels that are likely to cause visual artifacts during image fusion via joint color image denoising and detail transfer from the mono image. By constructing an experimental system of color-plus-mono camera, we demonstrate that the BJND-aware denoising and selective detail transfer is helpful in improving the image quality during low light shooting.
Evaluation of multimodality imaging using image fusion with ultrasound tissue elasticity imaging in an experimental animal model.

PubMed

Paprottka, P M; Zengel, P; Cyran, C C; Ingrisch, M; Nikolaou, K; Reiser, M F; Clevert, D A

2014-01-01

To evaluate the ultrasound tissue elasticity imaging by comparison to multimodality imaging using image fusion with Magnetic Resonance Imaging (MRI) and conventional grey scale imaging with additional elasticity-ultrasound in an experimental small-animal-squamous-cell carcinoma-model for the assessment of tissue morphology. Human hypopharynx carcinoma cells were subcutaneously injected into the left flank of 12 female athymic nude rats. After 10 days (SD ± 2) of subcutaneous tumor growth, sonographic grey scale including elasticity imaging and MRI measurements were performed using a high-end ultrasound system and a 3T MR. For image fusion the contrast-enhanced MRI DICOM data set was uploaded in the ultrasonic device which has a magnetic field generator, a linear array transducer (6-15 MHz) and a dedicated software package (GE Logic E9), that can detect transducers by means of a positioning system. Conventional grey scale and elasticity imaging were integrated in the image fusion examination. After successful registration and image fusion the registered MR-images were simultaneously shown with the respective ultrasound sectional plane. Data evaluation was performed using the digitally stored video sequence data sets by two experienced radiologist using a modified Tsukuba Elasticity score. The colors "red and green" are assigned for an area of soft tissue, "blue" indicates hard tissue. In all cases a successful image fusion and plan registration with MRI and ultrasound imaging including grey scale and elasticity imaging was possible. The mean tumor volume based on caliper measurements in 3 dimensions was ~323 mm3. 4/12 rats were evaluated with Score I, 5/12 rates were evaluated with Score II, 3/12 rates were evaluated with Score III. There was a close correlation in the fused MRI with existing small necrosis in the tumor. None of the scored II or III lesions was visible by conventional grey scale. The comparison of ultrasound tissue elasticity imaging enables a secure differentiation between different tumor tissue areas in comparison to image fusion with MRI in our small study group. Therefore ultrasound tissue elasticity imaging might be used for fast detection of tumor response in the future whereas conventional grey scale imaging alone could not provide the additional information. By using standard, contrast-enhanced MRI images for reliable and reproducible slice positioning, the strongly user-dependent limitation of ultrasound tissue elasticity imaging may be overcome, especially for a comparison between baseline and follow-up measurements.
Developing an Automated Science Analysis System for Mars Surface Exploration for MSL and Beyond

NASA Technical Reports Server (NTRS)

Gulick, V. C.; Hart, S. D.; Shi, X.; Siegel, V. L.

2004-01-01

We are developing an automated science analysis system that could be utilized by robotic or human explorers on Mars (or even in remote locations on Earth) to improve the quality and quantity of science data returned. Three components of this system (our rock, layer, and horizon detectors) [1] have been incorporated into the JPL CLARITY system for possible use by MSL and future Mars robotic missions. Two other components include a multi-spectral image compression (SPEC) algorithm for pancam-type images with multiple filters and image fusion algorithms that identify the in focus regions of individual images in an image focal series [2]. Recently, we have been working to combine image and spectral data, and other knowledge to identify both rocks and minerals. Here we present our progress on developing an igneous rock detection system.
A Hierarchical Convolutional Neural Network for vesicle fusion event classification.

PubMed

Li, Haohan; Mao, Yunxiang; Yin, Zhaozheng; Xu, Yingke

2017-09-01

Quantitative analysis of vesicle exocytosis and classification of different modes of vesicle fusion from the fluorescence microscopy are of primary importance for biomedical researches. In this paper, we propose a novel Hierarchical Convolutional Neural Network (HCNN) method to automatically identify vesicle fusion events in time-lapse Total Internal Reflection Fluorescence Microscopy (TIRFM) image sequences. Firstly, a detection and tracking method is developed to extract image patch sequences containing potential fusion events. Then, a Gaussian Mixture Model (GMM) is applied on each image patch of the patch sequence with outliers rejected for robust Gaussian fitting. By utilizing the high-level time-series intensity change features introduced by GMM and the visual appearance features embedded in some key moments of the fusion process, the proposed HCNN architecture is able to classify each candidate patch sequence into three classes: full fusion event, partial fusion event and non-fusion event. Finally, we validate the performance of our method on 9 challenging datasets that have been annotated by cell biologists, and our method achieves better performances when comparing with three previous methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

Intensity-hue-saturation-based image fusion using iterative linear regression

NASA Astrophysics Data System (ADS)

Cetin, Mufit; Tepecik, Abdulkadir

2016-10-01

The image fusion process basically produces a high-resolution image by combining the superior features of a low-resolution spatial image and a high-resolution panchromatic image. Despite its common usage due to its fast computing capability and high sharpening ability, the intensity-hue-saturation (IHS) fusion method may cause some color distortions, especially when a large number of gray value differences exist among the images to be combined. This paper proposes a spatially adaptive IHS (SA-IHS) technique to avoid these distortions by automatically adjusting the exact spatial information to be injected into the multispectral image during the fusion process. The SA-IHS method essentially suppresses the effects of those pixels that cause the spectral distortions by assigning weaker weights to them and avoiding a large number of redundancies on the fused image. The experimental database consists of IKONOS images, and the experimental results both visually and statistically prove the enhancement of the proposed algorithm when compared with the several other IHS-like methods such as IHS, generalized IHS, fast IHS, and generalized adaptive IHS.
Implementing and validating of pan-sharpening algorithms in open-source software

NASA Astrophysics Data System (ADS)

Pesántez-Cobos, Paúl; Cánovas-García, Fulgencio; Alonso-Sarría, Francisco

2017-10-01

Several approaches have been used in remote sensing to integrate images with different spectral and spatial resolutions in order to obtain fused enhanced images. The objective of this research is three-fold. To implement in R three image fusion techniques (High Pass Filter, Principal Component Analysis and Gram-Schmidt); to apply these techniques to merging multispectral and panchromatic images from five different images with different spatial resolutions; finally, to evaluate the results using the universal image quality index (Q index) and the ERGAS index. As regards qualitative analysis, Landsat-7 and Landsat-8 show greater colour distortion with the three pansharpening methods, although the results for the other images were better. Q index revealed that HPF fusion performs better for the QuickBird, IKONOS and Landsat-7 images, followed by GS fusion; whereas in the case of Landsat-8 and Natmur-08 images, the results were more even. Regarding the ERGAS spatial index, the ACP algorithm performed better for the QuickBird, IKONOS, Landsat-7 and Natmur-08 images, followed closely by the GS algorithm. Only for the Landsat-8 image did, the GS fusion present the best result. In the evaluation of spectral components, HPF results tended to be better and ACP results worse, the opposite was the case with the spatial components. Better quantitative results are obtained in Landsat-7 and Landsat-8 images with the three fusion methods than with the QuickBird, IKONOS and Natmur-08 images. This contrasts with the qualitative evaluation reflecting the importance of splitting the two evaluation approaches (qualitative and quantitative). Significant disagreement may arise when different methodologies are used to asses the quality of an image fusion. Moreover, it is not possible to designate, a priori, a given algorithm as the best, not only because of the different characteristics of the sensors, but also because of the different atmospherics conditions or peculiarities of the different study areas, among other reasons.
Perception-oriented fusion of multi-sensor imagery: visible, IR, and SAR

NASA Astrophysics Data System (ADS)

Sidorchuk, D.; Volkov, V.; Gladilin, S.

2018-04-01

This paper addresses the problem of image fusion of optical (visible and thermal domain) data and radar data for the purpose of visualization. These types of images typically contain a lot of complimentary information, and their joint visualization can be useful and more convenient for human user than a set of individual images. To solve the image fusion problem we propose a novel algorithm that utilizes some peculiarities of human color perception and based on the grey-scale structural visualization. Benefits of presented algorithm are exemplified by satellite imagery.
Image Fusion for Radiosurgery, Neurosurgery and Hypofractionated Radiotherapy.

PubMed

Inoue, Hiroshi K; Nakajima, Atsushi; Sato, Hiro; Noda, Shin-Ei; Saitoh, Jun-Ichi; Suzuki, Yoshiyuki

2015-03-01

Precise target detection is essential for radiosurgery, neurosurgery and hypofractionated radiotherapy because treatment results and complication rates are related to accuracy of the target definition. In skull base tumors and tumors around the optic pathways, exact anatomical evaluation of cranial nerves are important to avoid adverse effects on these structures close to lesions. Three-dimensional analyses of structures obtained with MR heavy T2-images and image fusion with CT thin-sliced sections are desirable to evaluate fine structures during radiosurgery and microsurgery. In vascular lesions, angiography is most important for evaluations of whole structures from feeder to drainer, shunt, blood flow and risk factors of bleeding. However, exact sites and surrounding structures in the brain are not shown on angiography. True image fusions of angiography, MR images and CT on axial planes are ideal for precise target definition. In malignant tumors, especially recurrent head and neck tumors, biologically active areas of recurrent tumors are main targets of radiosurgery. PET scan is useful for quantitative evaluation of recurrences. However, the examination is not always available at the time of radiosurgery. Image fusion of MR diffusion images with CT is always available during radiosurgery and useful for the detection of recurrent lesions. All images are fused and registered on thin sliced CT sections and exactly demarcated targets are planned for treatment. Follow-up images are also able to register on this CT. Exact target changes, including volume, are possible in this fusion system. The purpose of this review is to describe the usefulness of image fusion for 1) skull base, 2) vascular, 3) recurrent target detection, and 4) follow-up analyses in radiosurgery, neurosurgery and hypofractionated radiotherapy.
Image Fusion for Radiosurgery, Neurosurgery and Hypofractionated Radiotherapy

PubMed Central

Nakajima, Atsushi; Sato, Hiro; Noda, Shin-ei; Saitoh, Jun-ichi; Suzuki, Yoshiyuki

2015-01-01

Precise target detection is essential for radiosurgery, neurosurgery and hypofractionated radiotherapy because treatment results and complication rates are related to accuracy of the target definition. In skull base tumors and tumors around the optic pathways, exact anatomical evaluation of cranial nerves are important to avoid adverse effects on these structures close to lesions. Three-dimensional analyses of structures obtained with MR heavy T2-images and image fusion with CT thin-sliced sections are desirable to evaluate fine structures during radiosurgery and microsurgery. In vascular lesions, angiography is most important for evaluations of whole structures from feeder to drainer, shunt, blood flow and risk factors of bleeding. However, exact sites and surrounding structures in the brain are not shown on angiography. True image fusions of angiography, MR images and CT on axial planes are ideal for precise target definition. In malignant tumors, especially recurrent head and neck tumors, biologically active areas of recurrent tumors are main targets of radiosurgery. PET scan is useful for quantitative evaluation of recurrences. However, the examination is not always available at the time of radiosurgery. Image fusion of MR diffusion images with CT is always available during radiosurgery and useful for the detection of recurrent lesions. All images are fused and registered on thin sliced CT sections and exactly demarcated targets are planned for treatment. Follow-up images are also able to register on this CT. Exact target changes, including volume, are possible in this fusion system. The purpose of this review is to describe the usefulness of image fusion for 1) skull base, 2) vascular, 3) recurrent target detection, and 4) follow-up analyses in radiosurgery, neurosurgery and hypofractionated radiotherapy. PMID:26180676
A new method for fusion, denoising and enhancement of x-ray images retrieved from Talbot-Lau grating interferometry.

PubMed

Scholkmann, Felix; Revol, Vincent; Kaufmann, Rolf; Baronowski, Heidrun; Kottler, Christian

2014-03-21

This paper introduces a new image denoising, fusion and enhancement framework for combining and optimal visualization of x-ray attenuation contrast (AC), differential phase contrast (DPC) and dark-field contrast (DFC) images retrieved from x-ray Talbot-Lau grating interferometry. The new image fusion framework comprises three steps: (i) denoising each input image (AC, DPC and DFC) through adaptive Wiener filtering, (ii) performing a two-step image fusion process based on the shift-invariant wavelet transform, i.e. first fusing the AC with the DPC image and then fusing the resulting image with the DFC image, and finally (iii) enhancing the fused image to obtain a final image using adaptive histogram equalization, adaptive sharpening and contrast optimization. Application examples are presented for two biological objects (a human tooth and a cherry) and the proposed method is compared to two recently published AC/DPC/DFC image processing techniques. In conclusion, the new framework for the processing of AC, DPC and DFC allows the most relevant features of all three images to be combined in one image while reducing the noise and enhancing adaptively the relevant image features. The newly developed framework may be used in technical and medical applications.
System integration and DICOM image creation for PET-MR fusion.

PubMed

Hsiao, Chia-Hung; Kao, Tsair; Fang, Yu-Hua; Wang, Jiunn-Kuen; Guo, Wan-Yuo; Chao, Liang-Hsiao; Yen, Sang-Hue

2005-03-01

This article demonstrates a gateway system for converting image fusion results to digital imaging and communication in medicine (DICOM) objects. For the purpose of standardization and integration, we have followed the guidelines of the Integrated Healthcare Enterprise technical framework and developed a DICOM gateway. The gateway system combines data from hospital information system, image fusion results, and the information generated itself to constitute new DICOM objects. All the mandatory tags defined in standard DICOM object were generated in the gateway system. The gateway system will generate two series of SOP instances of each PET-MR fusion result; SOP (Service Object Pair) one for the reconstructed magnetic resonance (MR) images and the other for position emission tomography (PET) images. The size, resolution, spatial coordinates, and number of frames are the same in both series of SOP instances. Every new generated MR image exactly fits with one of the reconstructed PET images. Those DICOM images are stored to the picture archiving and communication system (PACS) server by means of standard DICOM protocols. When those images are retrieved and viewed by standard DICOM viewing systems, both images can be viewed at the same anatomy location. This system is useful for precise diagnosis and therapy.
Computed tomography angiography-fluoroscopy image fusion allows visceral vessel cannulation without angiography during fenestrated endovascular aneurysm repair.

PubMed

Schwein, Adeline; Chinnadurai, Ponraj; Behler, Greg; Lumsden, Alan B; Bismuth, Jean; Bechara, Carlos F

2018-07-01

Fenestrated endovascular aneurysm repair (FEVAR) is an evolving technique to treat juxtarenal abdominal aortic aneurysms (AAAs). Catheterization of visceral and renal vessels after the deployment of the fenestrated main body device is often challenging, usually requiring additional fluoroscopy and multiple digital subtraction angiograms. The aim of this study was to assess the clinical utility and accuracy of a computed tomography angiography (CTA)-fluoroscopy image fusion technique in guiding visceral vessel cannulation during FEVAR. Between August 2014 and September 2016, all consecutive patients who underwent FEVAR at our institution using image fusion guidance were included. Preoperative CTA images were fused with intraoperative fluoroscopy after coregistering with non-contrast-enhanced cone beam computed tomography (syngo 3D3D image fusion; Siemens Healthcare, Forchheim, Germany). The ostia of the visceral vessels were electronically marked on CTA images (syngo iGuide Toolbox) and overlaid on live fluoroscopy to guide vessel cannulation after fenestrated device deployment. Clinical utility of image fusion was evaluated by assessing the number of dedicated angiograms required for each visceral or renal vessel cannulation and the use of optimized C-arm angulation. Accuracy of image fusion was evaluated from video recordings by three raters using a binary qualitative assessment scale. A total of 26 patients (17 men; mean age, 73.8 years) underwent FEVAR during the study period for juxtarenal AAA (17), pararenal AAA (6), and thoracoabdominal aortic aneurysm (3). Video recordings of fluoroscopy from 19 cases were available for review and assessment. A total of 46 vessels were cannulated; 38 of 46 (83%) of these vessels were cannulated without angiography but based only on image fusion guidance: 9 of 11 superior mesenteric artery cannulations and 29 of 35 renal artery cannulations. Binary qualitative assessment showed that 90% (36/40) of the virtual ostia overlaid on live fluoroscopy were accurate. Optimized C-arm angulations were achieved in 35% of vessel cannulations (0/9 for superior mesenteric artery cannulation, 12/25 for renal arteries). Preoperative CTA-fluoroscopy image fusion guidance during FEVAR is a valuable and accurate tool that allows visceral and renal vessel cannulation without the need of dedicated angiograms, thus avoiding additional injection of contrast material and radiation exposure. Further refinements, such as accounting for device-induced aortic deformation and automating the image fusion workflow, will bolster this technology toward optimal routine clinical use. Copyright © 2017 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.
Improved colour matching technique for fused nighttime imagery with daytime colours

NASA Astrophysics Data System (ADS)

Hogervorst, Maarten A.; Toet, Alexander

2016-10-01

Previously, we presented a method for applying daytime colours to fused nighttime (e.g., intensified and LWIR) imagery (Toet and Hogervorst, Opt.Eng. 51(1), 2012). Our colour mapping not only imparts a natural daylight appearance to multiband nighttime images but also enhances the contrast and visibility of otherwise obscured details. As a result, this colourizing method leads to increased ease of interpretation, better discrimination and identification of materials, faster reaction times and ultimately improved situational awareness (Toet e.a., Opt.Eng.53(4), 2014). A crucial step in this colouring process is the choice of a suitable colour mapping scheme. When daytime colour images and multiband sensor images of the same scene are available the colour mapping can be derived from matching image samples (i.e., by relating colour values to sensor signal intensities). When no exact matching reference images are available the colour transformation can be derived from the first-order statistical properties of the reference image and the multiband sensor image (Toet, Info. Fus. 4(3), 2003). In the current study we investigated new colour fusion schemes that combine the advantages of the both methods, using the correspondence between multiband sensor values and daytime colours (1st method) in a smooth transformation (2nd method). We designed and evaluated three new fusion schemes that focus on: i) a closer match with the daytime luminances, ii) improved saliency of hot targets and iii) improved discriminability of materials
Multispectral image fusion based on fractal features

NASA Astrophysics Data System (ADS)

Tian, Jie; Chen, Jie; Zhang, Chunhua

2004-01-01

Imagery sensors have been one indispensable part of the detection and recognition systems. They are widely used to the field of surveillance, navigation, control and guide, et. However, different imagery sensors depend on diverse imaging mechanisms, and work within diverse range of spectrum. They also perform diverse functions and have diverse circumstance requires. So it is unpractical to accomplish the task of detection or recognition with a single imagery sensor under the conditions of different circumstances, different backgrounds and different targets. Fortunately, the multi-sensor image fusion technique emerged as important route to solve this problem. So image fusion has been one of the main technical routines used to detect and recognize objects from images. While, loss of information is unavoidable during fusion process, so it is always a very important content of image fusion how to preserve the useful information to the utmost. That is to say, it should be taken into account before designing the fusion schemes how to avoid the loss of useful information or how to preserve the features helpful to the detection. In consideration of these issues and the fact that most detection problems are actually to distinguish man-made objects from natural background, a fractal-based multi-spectral fusion algorithm has been proposed in this paper aiming at the recognition of battlefield targets in the complicated backgrounds. According to this algorithm, source images are firstly orthogonally decomposed according to wavelet transform theories, and then fractal-based detection is held to each decomposed image. At this step, natural background and man-made targets are distinguished by use of fractal models that can well imitate natural objects. Special fusion operators are employed during the fusion of area that contains man-made targets so that useful information could be preserved and features of targets could be extruded. The final fused image is reconstructed from the composition of source pyramid images. So this fusion scheme is a multi-resolution analysis. The wavelet decomposition of image can be actually considered as special pyramid decomposition. According to wavelet decomposition theories, the approximation of image (formula available in paper) at resolution 2j+1 equal to its orthogonal projection in space , that is, where Ajf is the low-frequency approximation of image f(x, y) at resolution 2j and , , represent the vertical, horizontal and diagonal wavelet coefficients respectively at resolution 2j. These coefficients describe the high-frequency information of image at direction of vertical, horizontal and diagonal respectively. Ajf, , and are independent and can be considered as images. In this paper J is set to be 1, so the source image is decomposed to produce the son-images Af, D1f, D2f and D3f. To solve the problem of detecting artifacts, the concepts of vertical fractal dimension FD1, horizontal fractal dimension FD2 and diagonal fractal dimension FD3 are proposed in this paper. The vertical fractal dimension FD1 corresponds to the vertical wavelet coefficients image after the wavelet decomposition of source image, the horizontal fractal dimension FD2 corresponds to the horizontal wavelet coefficients and the diagonal fractal dimension FD3 the diagonal one. These definitions enrich the illustration of source images. Therefore they are helpful to classify the targets. Then the detection of artifacts in the decomposed images is a problem of pattern recognition in 4-D space. The combination of FD0, FD1, FD2 and FD3 make a vector of (FD0, FD1, FD2, FD3), which can be considered as a united feature vector of the studied image. All the parts of the images are classified in the 4-D pattern space created by the vector of (FD0, FD1, FD2, FD3) so that the area that contains man-made objects could be detected. This detection can be considered as a coarse recognition, and then the significant areas in each son-images are signed so that they can be dealt with special rules. There has been various fusion rules developed with each one aiming at a special problem. These rules have different performance, so it is very important to select an appropriate rule during the design of an image fusion system. Recent research denotes that the rule should be adjustable so that it is always suitable to extrude the features of targets and to preserve the pixels of useful information. In this paper, owing to the consideration that fractal dimension is one of the main features to distinguish man-made targets from natural objects, the fusion rule was defined that if the studied region of image contains man-made target, the pixels of the source image whose fractal dimension is minimal are saved to be the pixels of the fused image, otherwise, a weighted average operator is adopted to avoid loss of information. The main idea of this rule is to store the pixels with low fractal dimensions, so it can be named Minimal Fractal dimensions (MFD) fusion rule. This fractal-based algorithm is compared with a common weighted average fusion algorithm. An objective assessment is taken to the two fusion results. The criteria of Entropy, Cross-Entropy, Peak Signal-to-Noise Ratio (PSNR) and Standard Gray Scale Difference are defined in this paper. Reversely to the idea of constructing an ideal image as the assessing reference, the source images are selected to be the reference in this paper. It can be deemed that this assessment is to calculate how much the image quality has been enhanced and the quantity of information has been increased when the fused image is compared with the source images. The experimental results imply that the fractal-based multi-spectral fusion algorithm can effectively preserve the information of man-made objects with a high contrast. It is proved that this algorithm could well preserve features of military targets because that battlefield targets are most man-made objects and in common their images differ from fractal models obviously. Furthermore, the fractal features are not sensitive to the imaging conditions and the movement of targets, so this fractal-based algorithm may be very practical.
Live imaging of mouse secondary palate fusion

PubMed Central

Kim, Seungil; Prochazka, Jan; Bush, Jeffrey O.

2017-01-01

LONG ABSTRACT The fusion of the secondary palatal shelves to form the intact secondary palate is a key process in mammalian development and its disruption can lead to cleft secondary palate, a common congenital anomaly in humans. Secondary palate fusion has been extensively studied leading to several proposed cellular mechanisms that may mediate this process. However, these studies have been mostly performed on fixed embryonic tissues at progressive timepoints during development or in fixed explant cultures analyzed at static timepoints. Static analysis is limited for the analysis of dynamic morphogenetic processes such a palate fusion and what types of dynamic cellular behaviors mediate palatal fusion is incompletely understood. Here we describe a protocol for live imaging of ex vivo secondary palate fusion in mouse embryos. To examine cellular behaviors of palate fusion, epithelial-specific Keratin14-cre was used to label palate epithelial cells in ROSA26-mTmGflox reporter embryos. To visualize filamentous actin, Lifeact-mRFPruby reporter mice were used. Live imaging of secondary palate fusion was performed by dissecting recently-adhered secondary palatal shelves of embryonic day (E) 14.5 stage embryos and culturing in agarose-containing media on a glass bottom dish to enable imaging with an inverted confocal microscope. Using this method, we have detected a variety of novel cellular behaviors during secondary palate fusion. An appreciation of how distinct cell behaviors are coordinated in space and time greatly contributes to our understanding of this dynamic morphogenetic process. This protocol can be applied to mutant mouse lines, or cultures treated with pharmacological inhibitors to further advance understanding of how secondary palate fusion is controlled. PMID:28784960
Active contour configuration model for estimating the posterior ablative margin in image fusion of real-time ultrasound and 3D ultrasound or magnetic resonance images for radiofrequency ablation: an experimental study.

PubMed

Lee, Junkyo; Lee, Min Woo; Choi, Dongil; Cha, Dong Ik; Lee, Sunyoung; Kang, Tae Wook; Yang, Jehoon; Jo, Jaemoon; Bang, Won-Chul; Kim, Jongsik; Shin, Dongkuk

2017-12-21

The purpose of this study was to evaluate the accuracy of an active contour model for estimating the posterior ablative margin in images obtained by the fusion of real-time ultrasonography (US) and 3-dimensional (3D) US or magnetic resonance (MR) images of an experimental tumor model for radiofrequency ablation. Chickpeas (n=12) and bovine rump meat (n=12) were used as an experimental tumor model. Grayscale 3D US and T1-weighted MR images were pre-acquired for use as reference datasets. US and MR/3D US fusion was performed for one group (n=4), and US and 3D US fusion only (n=8) was performed for the other group. Half of the models in each group were completely ablated, while the other half were incompletely ablated. Hyperechoic ablation areas were extracted using an active contour model from real-time US images, and the posterior margin of the ablation zone was estimated from the anterior margin. After the experiments, the ablated pieces of bovine rump meat were cut along the electrode path and the cut planes were photographed. The US images with the estimated posterior margin were compared with the photographs and post-ablation MR images. The extracted contours of the ablation zones from 12 US fusion videos and post-ablation MR images were also matched. In the four models fused under real-time US with MR/3D US, compression from the transducer and the insertion of an electrode resulted in misregistration between the real-time US and MR images, making the estimation of the ablation zones less accurate than was achieved through fusion between real-time US and 3D US. Eight of the 12 post-ablation 3D US images were graded as good when compared with the sectioned specimens, and 10 of the 12 were graded as good in a comparison with nicotinamide adenine dinucleotide staining and histopathologic results. Estimating the posterior ablative margin using an active contour model is a feasible way of predicting the ablation area, and US/3D US fusion was more accurate than US/MR fusion.
Neutron imaging with bubble chambers for inertial confinement fusion

NASA Astrophysics Data System (ADS)

Ghilea, Marian C.

One of the main methods to obtain energy from controlled thermonuclear fusion is inertial confinement fusion (ICF), a process where nuclear fusion reactions are initiated by heating and compressing a fuel target, typically in the form of a pellet that contains deuterium and tritium, relying on the inertia of the fuel mass to provide confinement. In inertial confinement fusion experiments, it is important to distinguish failure mechanisms of the imploding capsule and unambiguously diagnose compression and hot spot formation in the fuel. Neutron imaging provides such a technique and bubble chambers are capable of generating higher resolution images than other types of neutron detectors. This thesis explores the use of a liquid bubble chamber to record high yield 14.1 MeV neutrons resulting from deuterium-tritium fusion reactions on ICF experiments. A design tool to deconvolve and reconstruct penumbral and pinhole neutron images was created, using an original ray tracing concept to simulate the neutron images. The design tool proved that misalignment and aperture fabrication errors can significantly decrease the resolution of the reconstructed neutron image. A theoretical model to describe the mechanism of bubble formation was developed. A bubble chamber for neutron imaging with Freon 115 as active medium was designed and implemented for the OMEGA laser system. High neutron yields resulting from deuterium-tritium capsule implosions were recorded. The bubble density was too low for neutron imaging on OMEGA but agreed with the model of bubble formation. The research done in here shows that bubble detectors are a promising technology for the higher neutron yields expected at National Ignition Facility (NIF).
Multispectral image fusion for illumination-invariant palmprint recognition

PubMed Central

Zhang, Xinman; Xu, Xuebin; Shang, Dongpeng

2017-01-01

Multispectral palmprint recognition has shown broad prospects for personal identification due to its high accuracy and great stability. In this paper, we develop a novel illumination-invariant multispectral palmprint recognition method. To combine the information from multiple spectral bands, an image-level fusion framework is completed based on a fast and adaptive bidimensional empirical mode decomposition (FABEMD) and a weighted Fisher criterion. The FABEMD technique decomposes the multispectral images into their bidimensional intrinsic mode functions (BIMFs), on which an illumination compensation operation is performed. The weighted Fisher criterion is to construct the fusion coefficients at the decomposition level, making the images be separated correctly in the fusion space. The image fusion framework has shown strong robustness against illumination variation. In addition, a tensor-based extreme learning machine (TELM) mechanism is presented for feature extraction and classification of two-dimensional (2D) images. In general, this method has fast learning speed and satisfying recognition accuracy. Comprehensive experiments conducted on the PolyU multispectral palmprint database illustrate that the proposed method can achieve favorable results. For the testing under ideal illumination, the recognition accuracy is as high as 99.93%, and the result is 99.50% when the lighting condition is unsatisfied. PMID:28558064
Multispectral image fusion for illumination-invariant palmprint recognition.

PubMed

Lu, Longbin; Zhang, Xinman; Xu, Xuebin; Shang, Dongpeng

2017-01-01

Multispectral palmprint recognition has shown broad prospects for personal identification due to its high accuracy and great stability. In this paper, we develop a novel illumination-invariant multispectral palmprint recognition method. To combine the information from multiple spectral bands, an image-level fusion framework is completed based on a fast and adaptive bidimensional empirical mode decomposition (FABEMD) and a weighted Fisher criterion. The FABEMD technique decomposes the multispectral images into their bidimensional intrinsic mode functions (BIMFs), on which an illumination compensation operation is performed. The weighted Fisher criterion is to construct the fusion coefficients at the decomposition level, making the images be separated correctly in the fusion space. The image fusion framework has shown strong robustness against illumination variation. In addition, a tensor-based extreme learning machine (TELM) mechanism is presented for feature extraction and classification of two-dimensional (2D) images. In general, this method has fast learning speed and satisfying recognition accuracy. Comprehensive experiments conducted on the PolyU multispectral palmprint database illustrate that the proposed method can achieve favorable results. For the testing under ideal illumination, the recognition accuracy is as high as 99.93%, and the result is 99.50% when the lighting condition is unsatisfied.
Echocardiographic and Fluoroscopic Fusion Imaging for Procedural Guidance: An Overview and Early Clinical Experience.

PubMed

Thaden, Jeremy J; Sanon, Saurabh; Geske, Jeffrey B; Eleid, Mackram F; Nijhof, Niels; Malouf, Joseph F; Rihal, Charanjit S; Bruce, Charles J

2016-06-01

There has been significant growth in the volume and complexity of percutaneous structural heart procedures in the past decade. Increasing procedural complexity and accompanying reliance on multimodality imaging have fueled the development of fusion imaging to facilitate procedural guidance. The first clinically available system capable of echocardiographic and fluoroscopic fusion for real-time guidance of structural heart procedures was approved by the US Food and Drug Administration in 2012. Echocardiographic-fluoroscopic fusion imaging combines the precise catheter and device visualization of fluoroscopy with the soft tissue anatomy and color flow Doppler information afforded by echocardiography in a single image. This allows the interventionalist to perform precise catheter manipulations under fluoroscopy guidance while visualizing critical tissue anatomy provided by echocardiography. However, there are few data available addressing this technology's strengths and limitations in routine clinical practice. The authors provide a critical review of currently available echocardiographic-fluoroscopic fusion imaging for guidance of structural heart interventions to highlight its strengths, limitations, and potential clinical applications and to guide further research into value of this emerging technology. Copyright © 2016 American Society of Echocardiography. Published by Elsevier Inc. All rights reserved.
Knowledge guided information fusion for segmentation of multiple sclerosis lesions in MRI images

NASA Astrophysics Data System (ADS)

Zhu, Chaozhe; Jiang, Tianzi

2003-05-01

In this work, T1-, T2- and PD-weighted MR images of multiple sclerosis (MS) patients, providing information on the properties of tissues from different aspects, are treated as three independent information sources for the detection and segmentation of MS lesions. Based on information fusion theory, a knowledge guided information fusion framework is proposed to accomplish 3-D segmentation of MS lesions. This framework consists of three parts: (1) information extraction, (2) information fusion, and (3) decision. Information provided by different spectral images is extracted and modeled separately in each spectrum using fuzzy sets, aiming at managing the uncertainty and ambiguity in the images due to noise and partial volume effect. In the second part, the possible fuzzy map of MS lesions in each spectral image is constructed from the extracted information under the guidance of experts' knowledge, and then the final fuzzy map of MS lesions is constructed through the fusion of the fuzzy maps obtained from different spectrum. Finally, 3-D segmentation of MS lesions is derived from the final fuzzy map. Experimental results show that this method is fast and accurate.
Live cell imaging of in vitro human trophoblast syncytialization.

PubMed

Wang, Rui; Dang, Yan-Li; Zheng, Ru; Li, Yue; Li, Weiwei; Lu, Xiaoyin; Wang, Li-Juan; Zhu, Cheng; Lin, Hai-Yan; Wang, Hongmei

2014-06-01

Human trophoblast syncytialization, a process of cell-cell fusion, is one of the most important yet least understood events during placental development. Investigating the fusion process in a placenta in vivo is very challenging given the complexity of this process. Application of primary cultured cytotrophoblast cells isolated from term placentas and BeWo cells derived from human choriocarcinoma formulates a biphasic strategy to achieve the mechanism of trophoblast cell fusion, as the former can spontaneously fuse to form the multinucleated syncytium and the latter is capable of fusing under the treatment of forskolin (FSK). Live-cell imaging is a powerful tool that is widely used to investigate many physiological or pathological processes in various animal models or humans; however, to our knowledge, the mechanism of trophoblast cell fusion has not been reported using a live- cell imaging manner. In this study, a live-cell imaging system was used to delineate the fusion process of primary term cytotrophoblast cells and BeWo cells. By using live staining with Hoechst 33342 or cytoplasmic dyes or by stably transfecting enhanced green fluorescent protein (EGFP) and DsRed2-Nuc reporter plasmids, we observed finger-like protrusions on the cell membranes of fusion partners before fusion and the exchange of cytoplasmic contents during fusion. In summary, this study provides the first video recording of the process of trophoblast syncytialization. Furthermore, the various live-cell imaging systems used in this study will help to yield molecular insights into the syncytialization process during placental development. © 2014 by the Society for the Study of Reproduction, Inc.
SIRF: Simultaneous Satellite Image Registration and Fusion in a Unified Framework.

PubMed

Chen, Chen; Li, Yeqing; Liu, Wei; Huang, Junzhou

2015-11-01

In this paper, we propose a novel method for image fusion with a high-resolution panchromatic image and a low-resolution multispectral (Ms) image at the same geographical location. The fusion is formulated as a convex optimization problem which minimizes a linear combination of a least-squares fitting term and a dynamic gradient sparsity regularizer. The former is to preserve accurate spectral information of the Ms image, while the latter is to keep sharp edges of the high-resolution panchromatic image. We further propose to simultaneously register the two images during the fusing process, which is naturally achieved by virtue of the dynamic gradient sparsity property. An efficient algorithm is then devised to solve the optimization problem, accomplishing a linear computational complexity in the size of the output image in each iteration. We compare our method against six state-of-the-art image fusion methods on Ms image data sets from four satellites. Extensive experimental results demonstrate that the proposed method substantially outperforms the others in terms of both spatial and spectral qualities. We also show that our method can provide high-quality products from coarsely registered real-world IKONOS data sets. Finally, a MATLAB implementation is provided to facilitate future research.
Advanced image fusion algorithms for Gamma Knife treatment planning. Evaluation and proposal for clinical use.

PubMed

Apostolou, N; Papazoglou, Th; Koutsouris, D

2006-01-01

Image fusion is a process of combining information from multiple sensors. It is a useful tool implemented in the treatment planning programme of Gamma Knife Radiosurgery. In this paper we evaluate advanced image fusion algorithms for Matlab platform and head images. We develop nine level grayscale image fusion methods: average, principal component analysis (PCA), discrete wavelet transform (DWT) and Laplacian, filter - subtract - decimate (FSD), contrast, gradient, morphological pyramid and a shift invariant discrete wavelet transform (SIDWT) method in Matlab platform. We test these methods qualitatively and quantitatively. The quantitative criteria we use are the Root Mean Square Error (RMSE), the Mutual Information (MI), the Standard Deviation (STD), the Entropy (H), the Difference Entropy (DH) and the Cross Entropy (CEN). The qualitative are: natural appearance, brilliance contrast, presence of complementary features and enhancement of common features. Finally we make clinically useful suggestions.

A fusion algorithm for infrared and visible based on guided filtering and phase congruency in NSST domain

NASA Astrophysics Data System (ADS)

Liu, Zhanwen; Feng, Yan; Chen, Hang; Jiao, Licheng

2017-10-01

A novel and effective image fusion method is proposed for creating a highly informative and smooth surface of fused image through merging visible and infrared images. Firstly, a two-scale non-subsampled shearlet transform (NSST) is employed to decompose the visible and infrared images into detail layers and one base layer. Then, phase congruency is adopted to extract the saliency maps from the detail layers and a guided filtering is proposed to compute the filtering output of base layer and saliency maps. Next, a novel weighted average technique is used to make full use of scene consistency for fusion and obtaining coefficients map. Finally the fusion image was acquired by taking inverse NSST of the fused coefficients map. Experiments show that the proposed approach can achieve better performance than other methods in terms of subjective visual effect and objective assessment.
Angiogram, fundus, and oxygen saturation optic nerve head image fusion

NASA Astrophysics Data System (ADS)

Cao, Hua; Khoobehi, Bahram

2009-02-01

A novel multi-modality optic nerve head image fusion approach has been successfully designed. The new approach has been applied on three ophthalmologic modalities: angiogram, fundus, and oxygen saturation retinal optic nerve head images. It has achieved an excellent result by giving the visualization of fundus or oxygen saturation images with a complete angiogram overlay. During this study, two contributions have been made in terms of novelty, efficiency, and accuracy. The first contribution is the automated control point detection algorithm for multi-sensor images. The new method employs retina vasculature and bifurcation features by identifying the initial good-guess of control points using the Adaptive Exploratory Algorithm. The second contribution is the heuristic optimization fusion algorithm. In order to maximize the objective function (Mutual-Pixel-Count), the iteration algorithm adjusts the initial guess of the control points at the sub-pixel level. A refinement of the parameter set is obtained at the end of each loop, and finally an optimal fused image is generated at the end of the iteration. It is the first time that Mutual-Pixel-Count concept has been introduced into biomedical image fusion area. By locking the images in one place, the fused image allows ophthalmologists to match the same eye over time and get a sense of disease progress and pinpoint surgical tools. The new algorithm can be easily expanded to human or animals' 3D eye, brain, or body image registration and fusion.
Use of image registration and fusion algorithms and techniques in radiotherapy: Report of the AAPM Radiation Therapy Committee Task Group No. 132.

PubMed

Brock, Kristy K; Mutic, Sasa; McNutt, Todd R; Li, Hua; Kessler, Marc L

2017-07-01

Image registration and fusion algorithms exist in almost every software system that creates or uses images in radiotherapy. Most treatment planning systems support some form of image registration and fusion to allow the use of multimodality and time-series image data and even anatomical atlases to assist in target volume and normal tissue delineation. Treatment delivery systems perform registration and fusion between the planning images and the in-room images acquired during the treatment to assist patient positioning. Advanced applications are beginning to support daily dose assessment and enable adaptive radiotherapy using image registration and fusion to propagate contours and accumulate dose between image data taken over the course of therapy to provide up-to-date estimates of anatomical changes and delivered dose. This information aids in the detection of anatomical and functional changes that might elicit changes in the treatment plan or prescription. As the output of the image registration process is always used as the input of another process for planning or delivery, it is important to understand and communicate the uncertainty associated with the software in general and the result of a specific registration. Unfortunately, there is no standard mathematical formalism to perform this for real-world situations where noise, distortion, and complex anatomical variations can occur. Validation of the software systems performance is also complicated by the lack of documentation available from commercial systems leading to use of these systems in undesirable 'black-box' fashion. In view of this situation and the central role that image registration and fusion play in treatment planning and delivery, the Therapy Physics Committee of the American Association of Physicists in Medicine commissioned Task Group 132 to review current approaches and solutions for image registration (both rigid and deformable) in radiotherapy and to provide recommendations for quality assurance and quality control of these clinical processes. © 2017 American Association of Physicists in Medicine.
Approach to interpret images produced by new generations of multidetector CT scanners in post-operative spine.

PubMed

Zeitoun, Rania; Hussein, Manar

2017-11-01

To reach a practical approach to interpret MDCT findings in post-operative spine cases and to change the false belief of CT failure in the setting of instruments secondary to related artefacts. We performed observational retrospective analysis of premier, early and late MDCT scans in 68 post-operative spine patients, with emphasis on instruments related complications and osseous fusion status. We used a grading system for assessment of osseous fusion in 35 patients and we further analysed the findings in failure of fusion, grade (D). We observed a variety of instruments related complications (mostly screws medially penetrating the pedicle) and osseous fusion status in late scans. We graded 11 interbody and 14 posterolateral levels as osseous fusion failure, showing additional instruments related complications, end plates erosive changes, adjacent segments spondylosis and malalignment. Modern MDCT scanners provide high quality images and are strongly recommended in assessment of the instruments and status of osseous fusion. In post-operative imaging of the spine, it is essential to be aware for what you are looking for, in relevance to the date of surgery. Advances in knowledge: Modern MDCT scanners allow assessment of instruments position and integrity and osseous fusion status in post-operative spine. We propose a helpful algorithm to simplify interpreting post-operative spine imaging.
Improved disparity map analysis through the fusion of monocular image segmentations

NASA Technical Reports Server (NTRS)

Perlant, Frederic P.; Mckeown, David M.

1991-01-01

The focus is to examine how estimates of three dimensional scene structure, as encoded in a scene disparity map, can be improved by the analysis of the original monocular imagery. The utilization of surface illumination information is provided by the segmentation of the monocular image into fine surface patches of nearly homogeneous intensity to remove mismatches generated during stereo matching. These patches are used to guide a statistical analysis of the disparity map based on the assumption that such patches correspond closely with physical surfaces in the scene. Such a technique is quite independent of whether the initial disparity map was generated by automated area-based or feature-based stereo matching. Stereo analysis results are presented on a complex urban scene containing various man-made and natural features. This scene contains a variety of problems including low building height with respect to the stereo baseline, buildings and roads in complex terrain, and highly textured buildings and terrain. The improvements are demonstrated due to monocular fusion with a set of different region-based image segmentations. The generality of this approach to stereo analysis and its utility in the development of general three dimensional scene interpretation systems are also discussed.
A Study of Feature Combination for Vehicle Detection Based on Image Processing

PubMed Central

2014-01-01

Video analytics play a critical role in most recent traffic monitoring and driver assistance systems. In this context, the correct detection and classification of surrounding vehicles through image analysis has been the focus of extensive research in the last years. Most of the pieces of work reported for image-based vehicle verification make use of supervised classification approaches and resort to techniques, such as histograms of oriented gradients (HOG), principal component analysis (PCA), and Gabor filters, among others. Unfortunately, existing approaches are lacking in two respects: first, comparison between methods using a common body of work has not been addressed; second, no study of the combination potentiality of popular features for vehicle classification has been reported. In this study the performance of the different techniques is first reviewed and compared using a common public database. Then, the combination capabilities of these techniques are explored and a methodology is presented for the fusion of classifiers built upon them, taking into account also the vehicle pose. The study unveils the limitations of single-feature based classification and makes clear that fusion of classifiers is highly beneficial for vehicle verification. PMID:24672299
Research on segmentation based on multi-atlas in brain MR image

NASA Astrophysics Data System (ADS)

Qian, Yuejing

2018-03-01

Accurate segmentation of specific tissues in brain MR image can be effectively achieved with the multi-atlas-based segmentation method, and the accuracy mainly depends on the image registration accuracy and fusion scheme. This paper proposes an automatic segmentation method based on the multi-atlas for brain MR image. Firstly, to improve the registration accuracy in the area to be segmented, we employ a target-oriented image registration method for the refinement. Then In the label fusion, we proposed a new algorithm to detect the abnormal sparse patch and simultaneously abandon the corresponding abnormal sparse coefficients, this method is made based on the remaining sparse coefficients combined with the multipoint label estimator strategy. The performance of the proposed method was compared with those of the nonlocal patch-based label fusion method (Nonlocal-PBM), the sparse patch-based label fusion method (Sparse-PBM) and majority voting method (MV). Based on our experimental results, the proposed method is efficient in the brain MR images segmentation compared with MV, Nonlocal-PBM, and Sparse-PBM methods.
Joint image registration and fusion method with a gradient strength regularization

NASA Astrophysics Data System (ADS)

Lidong, Huang; Wei, Zhao; Jun, Wang

2015-05-01

Image registration is an essential process for image fusion, and fusion performance can be used to evaluate registration accuracy. We propose a maximum likelihood (ML) approach to joint image registration and fusion instead of treating them as two independent processes in the conventional way. To improve the visual quality of a fused image, a gradient strength (GS) regularization is introduced in the cost function of ML. The GS of the fused image is controllable by setting the target GS value in the regularization term. This is useful because a larger target GS brings a clearer fused image and a smaller target GS makes the fused image smoother and thus restrains noise. Hence, the subjective quality of the fused image can be improved whether the source images are polluted by noise or not. We can obtain the fused image and registration parameters successively by minimizing the cost function using an iterative optimization method. Experimental results show that our method is effective with transformation, rotation, and scale parameters in the range of [-2.0, 2.0] pixel, [-1.1 deg, 1.1 deg], and [0.95, 1.05], respectively, and variances of noise smaller than 300. It also demonstrated that our method yields a more visual pleasing fused image and higher registration accuracy compared with a state-of-the-art algorithm.
Layer-Based Approach for Image Pair Fusion.

PubMed

Son, Chang-Hwan; Zhang, Xiao-Ping

2016-04-20

Recently, image pairs, such as noisy and blurred images or infrared and noisy images, have been considered as a solution to provide high-quality photographs under low lighting conditions. In this paper, a new method for decomposing the image pairs into two layers, i.e., the base layer and the detail layer, is proposed for image pair fusion. In the case of infrared and noisy images, simple naive fusion leads to unsatisfactory results due to the discrepancies in brightness and image structures between the image pair. To address this problem, a local contrast-preserving conversion method is first proposed to create a new base layer of the infrared image, which can have visual appearance similar to another base layer such as the denoised noisy image. Then, a new way of designing three types of detail layers from the given noisy and infrared images is presented. To estimate the noise-free and unknown detail layer from the three designed detail layers, the optimization framework is modeled with residual-based sparsity and patch redundancy priors. To better suppress the noise, an iterative approach that updates the detail layer of the noisy image is adopted via a feedback loop. This proposed layer-based method can also be applied to fuse another noisy and blurred image pair. The experimental results show that the proposed method is effective for solving the image pair fusion problem.
Color image fusion for concealed weapon detection

NASA Astrophysics Data System (ADS)

Toet, Alexander

2003-09-01

Recent advances in passive and active imaging sensor technology offer the potential to detect weapons that are concealed underneath a person's clothing or carried along in bags. Although the concealed weapons can sometimes easily be detected, it can be difficult to perceive their context, due to the non-literal nature of these images. Especially for dynamic crowd surveillance purposes it may be impossible to rapidly asses with certainty which individual in the crowd is the one carrying the observed weapon. Sensor fusion is an enabling technology that may be used to solve this problem. Through fusion the signal of the sensor that depicts the weapon can be displayed in the context provided by a sensor of a different modality. We propose an image fusion scheme in which non-literal imagery can be fused with standard color images such that the result clearly displays the observed weapons in the context of the original color image. The procedure is such that the relevant contrast details from the non-literal image are transferred to the color image without altering the original color distribution of this image. The result is a natural looking color image that fluently combines all details from both input sources. When an observer who performs a dynamic crowd surveillance task, detects a weapon in the scene, he will also be able to quickly determine which person in the crowd is actually carrying the observed weapon (e.g. "the man with the red T-shirt and blue jeans"). The method is illustrated by the fusion of thermal 8-12 μm imagery with standard RGB color images.
Standardizing Quality Assessment of Fused Remotely Sensed Images

NASA Astrophysics Data System (ADS)

Pohl, C.; Moellmann, J.; Fries, K.

2017-09-01

The multitude of available operational remote sensing satellites led to the development of many image fusion techniques to provide high spatial, spectral and temporal resolution images. The comparison of different techniques is necessary to obtain an optimized image for the different applications of remote sensing. There are two approaches in assessing image quality: 1. Quantitatively by visual interpretation and 2. Quantitatively using image quality indices. However an objective comparison is difficult due to the fact that a visual assessment is always subject and a quantitative assessment is done by different criteria. Depending on the criteria and indices the result varies. Therefore it is necessary to standardize both processes (qualitative and quantitative assessment) in order to allow an objective image fusion quality evaluation. Various studies have been conducted at the University of Osnabrueck (UOS) to establish a standardized process to objectively compare fused image quality. First established image fusion quality assessment protocols, i.e. Quality with No Reference (QNR) and Khan's protocol, were compared on varies fusion experiments. Second the process of visual quality assessment was structured and standardized with the aim to provide an evaluation protocol. This manuscript reports on the results of the comparison and provides recommendations for future research.
Nonsubsampled rotated complex wavelet transform (NSRCxWT) for medical image fusion related to clinical aspects in neurocysticercosis.

PubMed

Chavan, Satishkumar S; Mahajan, Abhishek; Talbar, Sanjay N; Desai, Subhash; Thakur, Meenakshi; D'cruz, Anil

2017-02-01

Neurocysticercosis (NCC) is a parasite infection caused by the tapeworm Taenia solium in its larvae stage which affects the central nervous system of the human body (a definite host). It results in the formation of multiple lesions in the brain at different locations during its various stages. During diagnosis of such symptomatic patients, these lesions can be better visualized using a feature based fusion of Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). This paper presents a novel approach to Multimodality Medical Image Fusion (MMIF) used for the analysis of the lesions for the diagnostic purpose and post treatment review of NCC. The MMIF presented here is a technique of combining CT and MRI data of the same patient into a new slice using a Nonsubsampled Rotated Complex Wavelet Transform (NSRCxWT). The forward NSRCxWT is applied on both the source modalities separately to extract the complementary and the edge related features. These features are then combined to form a composite spectral plane using average and maximum value selection fusion rules. The inverse transformation on this composite plane results into a new, visually better, and enriched fused image. The proposed technique is tested on the pilot study data sets of patients infected with NCC. The quality of these fused images is measured using objective and subjective evaluation metrics. Objective evaluation is performed by estimating the fusion parameters like entropy, fusion factor, image quality index, edge quality measure, mean structural similarity index measure, etc. The fused images are also evaluated for their visual quality using subjective analysis with the help of three expert radiologists. The experimental results on 43 image data sets of 17 patients are promising and superior when compared with the state of the art wavelet based fusion algorithms. The proposed algorithm can be a part of computer-aided detection and diagnosis (CADD) system which assists the radiologists in clinical practices. Copyright © 2016 Elsevier Ltd. All rights reserved.
Live-cell imaging of conidial anastomosis tube fusion during colony initiation in Fusarium oxysporum

PubMed Central

Kurian, Smija M.; Di Pietro, Antonio

2018-01-01

Fusarium oxysporum exhibits conidial anastomosis tube (CAT) fusion during colony initiation to form networks of conidial germlings. Here we determined the optimal culture conditions for this fungus to undergo CAT fusion between microconidia in liquid medium. Extensive high resolution, confocal live-cell imaging was performed to characterise the different stages of CAT fusion, using genetically encoded fluorescent labelling and vital fluorescent organelle stains. CAT homing and fusion were found to be dependent on adhesion to the surface, in contrast to germ tube development which occurs in the absence of adhesion. Staining with fluorescently labelled concanavalin A indicated that the cell wall composition of CATs differs from that of microconidia and germ tubes. The movement of nuclei, mitochondria, vacuoles and lipid droplets through fused germlings was observed by live-cell imaging. PMID:29734342
Live-cell imaging of conidial anastomosis tube fusion during colony initiation in Fusarium oxysporum.

PubMed

Kurian, Smija M; Di Pietro, Antonio; Read, Nick D

2018-01-01

Fusarium oxysporum exhibits conidial anastomosis tube (CAT) fusion during colony initiation to form networks of conidial germlings. Here we determined the optimal culture conditions for this fungus to undergo CAT fusion between microconidia in liquid medium. Extensive high resolution, confocal live-cell imaging was performed to characterise the different stages of CAT fusion, using genetically encoded fluorescent labelling and vital fluorescent organelle stains. CAT homing and fusion were found to be dependent on adhesion to the surface, in contrast to germ tube development which occurs in the absence of adhesion. Staining with fluorescently labelled concanavalin A indicated that the cell wall composition of CATs differs from that of microconidia and germ tubes. The movement of nuclei, mitochondria, vacuoles and lipid droplets through fused germlings was observed by live-cell imaging.
Information Fusion and Visualisation in Anti Asymmetric Warfare

DTIC Science & Technology

2006-12-01

thermal detectors (e.g. bolometers). They used the MWIR and LWIR part of the IR spectrum. Quantum detectors realize an image rate of over 100Hz while... panorama image by image fusion of several sensors components. EO designators are distinguished through their agility and increased resolution
Joint interpretation of geophysical data using Image Fusion techniques

NASA Astrophysics Data System (ADS)

Karamitrou, A.; Tsokas, G.; Petrou, M.

2013-12-01

Joint interpretation of geophysical data produced from different methods is a challenging area of research in a wide range of applications. In this work we apply several image fusion approaches to combine maps of electrical resistivity, electromagnetic conductivity, vertical gradient of the magnetic field, magnetic susceptibility, and ground penetrating radar reflections, in order to detect archaeological relics. We utilize data gathered from Arkansas University, with the support of the U.S. Department of Defense, through the Strategic Environmental Research and Development Program (SERDP-CS1263). The area of investigation is the Army City, situated in Riley Country of Kansas, USA. The depth of the relics is estimated about 30 cm from the surface, yet the surface indications of its existence are limited. We initially register the images from the different methods to correct from random offsets due to the use of hand-held devices during the measurement procedure. Next, we apply four different image fusion approaches to create combined images, using fusion with mean values, wavelet decomposition, curvelet transform, and curvelet transform enhancing the images along specific angles. We create seven combinations of pairs between the available geophysical datasets. The combinations are such that for every pair at least one high-resolution method (resistivity or magnetic gradiometry) is included. Our results indicate that in almost every case the method of mean values produces satisfactory fused images that corporate the majority of the features of the initial images. However, the contrast of the final image is reduced, and in some cases the averaging process nearly eliminated features that are fade in the original images. Wavelet based fusion outputs also good results, providing additional control in selecting the feature wavelength. Curvelet based fusion is proved the most effective method in most of the cases. The ability of curvelet domain to unfold the image in terms of space, wavenumber, and orientation, provides important advantages compared with the rest of the methods by allowing the incorporation of a-priori information about the orientation of the potential targets.
Multi-sensor fusion of Landsat 8 thermal infrared (TIR) and panchromatic (PAN) images.

PubMed

Jung, Hyung-Sup; Park, Sung-Whan

2014-12-18

Data fusion is defined as the combination of data from multiple sensors such that the resulting information is better than would be possible when the sensors are used individually. The multi-sensor fusion of panchromatic (PAN) and thermal infrared (TIR) images is a good example of this data fusion. While a PAN image has higher spatial resolution, a TIR one has lower spatial resolution. In this study, we have proposed an efficient method to fuse Landsat 8 PAN and TIR images using an optimal scaling factor in order to control the trade-off between the spatial details and the thermal information. We have compared the fused images created from different scaling factors and then tested the performance of the proposed method at urban and rural test areas. The test results show that the proposed method merges the spatial resolution of PAN image and the temperature information of TIR image efficiently. The proposed method may be applied to detect lava flows of volcanic activity, radioactive exposure of nuclear power plants, and surface temperature change with respect to land-use change.
A Study for Texture Feature Extraction of High-Resolution Satellite Images Based on a Direction Measure and Gray Level Co-Occurrence Matrix Fusion Algorithm

PubMed Central

Zhang, Xin; Cui, Jintian; Wang, Weisheng; Lin, Chao

2017-01-01

To address the problem of image texture feature extraction, a direction measure statistic that is based on the directionality of image texture is constructed, and a new method of texture feature extraction, which is based on the direction measure and a gray level co-occurrence matrix (GLCM) fusion algorithm, is proposed in this paper. This method applies the GLCM to extract the texture feature value of an image and integrates the weight factor that is introduced by the direction measure to obtain the final texture feature of an image. A set of classification experiments for the high-resolution remote sensing images were performed by using support vector machine (SVM) classifier with the direction measure and gray level co-occurrence matrix fusion algorithm. Both qualitative and quantitative approaches were applied to assess the classification results. The experimental results demonstrated that texture feature extraction based on the fusion algorithm achieved a better image recognition, and the accuracy of classification based on this method has been significantly improved. PMID:28640181
Optics design for J-TEXT ECE imaging with field curvature adjustment lens.

PubMed

Zhu, Y; Zhao, Z; Liu, W D; Xie, J; Hu, X; Muscatello, C M; Domier, C W; Luhmann, N C; Chen, M; Ren, X; Tobias, B J; Zhuang, G; Yang, Z

2014-11-01

Significant progress has been made in the imaging and visualization of magnetohydrodynamic and microturbulence phenomena in magnetic fusion plasmas. Of particular importance has been microwave electron cyclotron emission imaging (ECEI) for imaging Te fluctuations. Key to the success of ECEI is a large Gaussian optics system constituting a major portion of the focusing of the microwave radiation from the plasma to the detector array. Both the spatial resolution and observation range are dependent upon the imaging optics system performance. In particular, it is critical that the field curvature on the image plane is reduced to decrease crosstalk between vertical channels. The receiver optics systems for two ECEI on the J-TEXT device have been designed to ameliorate these problems and provide good performance with additional field curvature adjustment lenses with a meniscus shape to correct the aberrations from several spherical surfaces.
A fast and automatic fusion algorithm for unregistered multi-exposure image sequence

NASA Astrophysics Data System (ADS)

Liu, Yan; Yu, Feihong

2014-09-01

Human visual system (HVS) can visualize all the brightness levels of the scene through visual adaptation. However, the dynamic range of most commercial digital cameras and display devices are smaller than the dynamic range of human eye. This implies low dynamic range (LDR) images captured by normal digital camera may lose image details. We propose an efficient approach to high dynamic (HDR) image fusion that copes with image displacement and image blur degradation in a computationally efficient manner, which is suitable for implementation on mobile devices. The various image registration algorithms proposed in the previous literatures are unable to meet the efficiency and performance requirements in the application of mobile devices. In this paper, we selected Oriented Brief (ORB) detector to extract local image structures. The descriptor selected in multi-exposure image fusion algorithm has to be fast and robust to illumination variations and geometric deformations. ORB descriptor is the best candidate in our algorithm. Further, we perform an improved RANdom Sample Consensus (RANSAC) algorithm to reject incorrect matches. For the fusion of images, a new approach based on Stationary Wavelet Transform (SWT) is used. The experimental results demonstrate that the proposed algorithm generates high quality images at low computational cost. Comparisons with a number of other feature matching methods show that our method gets better performance.

The Formin Diaphanous Regulates Myoblast Fusion through Actin Polymerization and Arp2/3 Regulation

PubMed Central

Deng, Su; Bothe, Ingo; Baylies, Mary K.

2015-01-01

The formation of multinucleated muscle cells through cell-cell fusion is a conserved process from fruit flies to humans. Numerous studies have shown the importance of Arp2/3, its regulators, and branched actin for the formation of an actin structure, the F-actin focus, at the fusion site. This F-actin focus forms the core of an invasive podosome-like structure that is required for myoblast fusion. In this study, we find that the formin Diaphanous (Dia), which nucleates and facilitates the elongation of actin filaments, is essential for Drosophila myoblast fusion. Following cell recognition and adhesion, Dia is enriched at the myoblast fusion site, concomitant with, and having the same dynamics as, the F-actin focus. Through analysis of Dia loss-of-function conditions using mutant alleles but particularly a dominant negative Dia transgene, we demonstrate that reduction in Dia activity in myoblasts leads to a fusion block. Significantly, no actin focus is detected, and neither branched actin regulators, SCAR or WASp, accumulate at the fusion site when Dia levels are reduced. Expression of constitutively active Dia also causes a fusion block that is associated with an increase in highly dynamic filopodia, altered actin turnover rates and F-actin distribution, and mislocalization of SCAR and WASp at the fusion site. Together our data indicate that Dia plays two roles during invasive podosome formation at the fusion site: it dictates the level of linear F-actin polymerization, and it is required for appropriate branched actin polymerization via localization of SCAR and WASp. These studies provide new insight to the mechanisms of cell-cell fusion, the relationship between different regulators of actin polymerization, and invasive podosome formation that occurs in normal development and in disease. PMID:26295716
Value of Image Fusion in Coronary Angiography for the Detection of Coronary Artery Bypass Grafts.

PubMed

Plessis, Julien; Warin Fresse, Karine; Cahouch, Zachary; Manigold, Thibaut; Letocart, Vincent; Le Gloan, Laurianne; Guyomarch, Béatrice; Guerin, Patrice

2016-06-10

Coronary angiography is more complex in patients with coronary artery bypass grafts (CABG). Image fusion is a new technology that allows the overlay of a computed tomography (CT) three-dimension (3D) model with fluoroscopic images in real time. This single-center prospective study included 66 previous CABG patients undergoing coronary and bypass graft angiography. Image fusion coronary angiographies (fusion group, 20 patients) were compared to conventional coronary angiographies (control group, 46 patients). The fusion group included patients for whom a previous chest CT scan with contrast was available. For patients in this group, aorta and CABG were reconstructed in 3D from CT acquisitions and merged in real time with fluoroscopic images. The following parameters were compared: time needed to localize the CABG; procedure duration; air kerma (AK); dose area product (DAP); and volume of contrast media injected. Results are expressed as median. There were no significant differences between the 2 groups in patient demographics and procedure characteristics (access site, number of bypass to be found, and interventional cardiologist's experience). The time to localize CABG was significantly shorter in the fusion group (7.3 versus 12.4 minutes; P=0.002), as well as the procedure duration (20.6 versus 25.6 minutes; P=0.002), AK (610 versus 814 mGy; P=0.02), DAP (4390 versus 5922.5 cGy·cm(2); P=0.02), and volume of iodinated contrast media (85 versus 116 cc; P=0.002). 3D image fusion improves the CABG detection in coronary angiography and reduces the time necessary to localize CABG, total procedure time duration, radiation exposure, and volume of contrast media. © 2016 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.
Multisensor fusion for 3D target tracking using track-before-detect particle filter

NASA Astrophysics Data System (ADS)

Moshtagh, Nima; Romberg, Paul M.; Chan, Moses W.

2015-05-01

This work presents a novel fusion mechanism for estimating the three-dimensional trajectory of a moving target using images collected by multiple imaging sensors. The proposed projective particle filter avoids the explicit target detection prior to fusion. In projective particle filter, particles that represent the posterior density (of target state in a high-dimensional space) are projected onto the lower-dimensional observation space. Measurements are generated directly in the observation space (image plane) and a marginal (sensor) likelihood is computed. The particles states and their weights are updated using the joint likelihood computed from all the sensors. The 3D state estimate of target (system track) is then generated from the states of the particles. This approach is similar to track-before-detect particle filters that are known to perform well in tracking dim and stealthy targets in image collections. Our approach extends the track-before-detect approach to 3D tracking using the projective particle filter. The performance of this measurement-level fusion method is compared with that of a track-level fusion algorithm using the projective particle filter. In the track-level fusion algorithm, the 2D sensor tracks are generated separately and transmitted to a fusion center, where they are treated as measurements to the state estimator. The 2D sensor tracks are then fused to reconstruct the system track. A realistic synthetic scenario with a boosting target was generated, and used to study the performance of the fusion mechanisms.
Millimeter-wave imaging of magnetic fusion plasmas: technology innovations advancing physics understanding

NASA Astrophysics Data System (ADS)

Wang, Y.; Tobias, B.; Chang, Y.-T.; Yu, J.-H.; Li, M.; Hu, F.; Chen, M.; Mamidanna, M.; Phan, T.; Pham, A.-V.; Gu, J.; Liu, X.; Zhu, Y.; Domier, C. W.; Shi, L.; Valeo, E.; Kramer, G. J.; Kuwahara, D.; Nagayama, Y.; Mase, A.; Luhmann, N. C., Jr.

2017-07-01

Electron cyclotron emission (ECE) imaging is a passive radiometric technique that measures electron temperature fluctuations; and microwave imaging reflectometry (MIR) is an active radar imaging technique that measures electron density fluctuations. Microwave imaging diagnostic instruments employing these techniques have made important contributions to fusion science and have been adopted at major fusion facilities worldwide including DIII-D, EAST, ASDEX Upgrade, HL-2A, KSTAR, LHD, and J-TEXT. In this paper, we describe the development status of three major technological advancements: custom mm-wave integrated circuits (ICs), digital beamforming (DBF), and synthetic diagnostic modeling (SDM). These have the potential to greatly advance microwave fusion plasma imaging, enabling compact and low-noise transceiver systems with real-time, fast tracking ability to address critical fusion physics issues, including ELM suppression and disruptions in the ITER baseline scenario, naturally ELM-free states such as QH-mode, and energetic particle confinement (i.e. Alfvén eigenmode stability) in high-performance regimes that include steady-state and advanced tokamak scenarios. Furthermore, these systems are fully compatible with today’s most challenging non-inductive heating and current drive systems and capable of operating in harsh environments, making them the ideal approach for diagnosing long-pulse and steady-state tokamaks.
Millimeter-wave imaging of magnetic fusion plasmas: technology innovations advancing physics understanding

DOE PAGES

Wang, Y.; Tobias, B.; Chang, Y. -T.; ...

2017-03-14

Electron cyclotron emission (ECE) imaging is a passive radiometric technique that measures electron temperature fluctuations; and microwave imaging reflectometry (MIR) is an active radar imaging technique that measures electron density fluctuations. The microwave imaging diagnostic instruments employing these techniques have made important contributions to fusion science and have been adopted at major fusion facilities worldwide including DIII-D, EAST, ASDEX Upgrade, HL-2A, KSTAR, LHD, and J-TEXT. In this paper, we describe the development status of three major technological advancements: custom mm-wave integrated circuits (ICs), digital beamforming (DBF), and synthetic diagnostic modeling (SDM). These also have the potential to greatly advance microwavemore » fusion plasma imaging, enabling compact and low-noise transceiver systems with real-time, fast tracking ability to address critical fusion physics issues, including ELM suppression and disruptions in the ITER baseline scenario, naturally ELM-free states such as QH-mode, and energetic particle confinement (i.e. Alfven eigenmode stability) in high-performance regimes that include steady-state and advanced tokamak scenarios. Furthermore, these systems are fully compatible with today's most challenging non-inductive heating and current drive systems and capable of operating in harsh environments, making them the ideal approach for diagnosing long-pulse and steady-state tokamaks.« less
A novel false color mapping model-based fusion method of visual and infrared images

NASA Astrophysics Data System (ADS)

Qi, Bin; Kun, Gao; Tian, Yue-xin; Zhu, Zhen-yu

2013-12-01

A fast and efficient image fusion method is presented to generate near-natural colors from panchromatic visual and thermal imaging sensors. Firstly, a set of daytime color reference images are analyzed and the false color mapping principle is proposed according to human's visual and emotional habits. That is, object colors should remain invariant after color mapping operations, differences between infrared and visual images should be enhanced and the background color should be consistent with the main scene content. Then a novel nonlinear color mapping model is given by introducing the geometric average value of the input visual and infrared image gray and the weighted average algorithm. To determine the control parameters in the mapping model, the boundary conditions are listed according to the mapping principle above. Fusion experiments show that the new fusion method can achieve the near-natural appearance of the fused image, and has the features of enhancing color contrasts and highlighting the infrared brilliant objects when comparing with the traditional TNO algorithm. Moreover, it owns the low complexity and is easy to realize real-time processing. So it is quite suitable for the nighttime imaging apparatus.
A tri-modality image fusion method for target delineation of brain tumors in radiotherapy.

PubMed

Guo, Lu; Shen, Shuming; Harris, Eleanor; Wang, Zheng; Jiang, Wei; Guo, Yu; Feng, Yuanming

2014-01-01

To develop a tri-modality image fusion method for better target delineation in image-guided radiotherapy for patients with brain tumors. A new method of tri-modality image fusion was developed, which can fuse and display all image sets in one panel and one operation. And a feasibility study in gross tumor volume (GTV) delineation using data from three patients with brain tumors was conducted, which included images of simulation CT, MRI, and 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) examinations before radiotherapy. Tri-modality image fusion was implemented after image registrations of CT+PET and CT+MRI, and the transparency weight of each modality could be adjusted and set by users. Three radiation oncologists delineated GTVs for all patients using dual-modality (MRI/CT) and tri-modality (MRI/CT/PET) image fusion respectively. Inter-observer variation was assessed by the coefficient of variation (COV), the average distance between surface and centroid (ADSC), and the local standard deviation (SDlocal). Analysis of COV was also performed to evaluate intra-observer volume variation. The inter-observer variation analysis showed that, the mean COV was 0.14(± 0.09) and 0.07(± 0.01) for dual-modality and tri-modality respectively; the standard deviation of ADSC was significantly reduced (p<0.05) with tri-modality; SDlocal averaged over median GTV surface was reduced in patient 2 (from 0.57 cm to 0.39 cm) and patient 3 (from 0.42 cm to 0.36 cm) with the new method. The intra-observer volume variation was also significantly reduced (p = 0.00) with the tri-modality method as compared with using the dual-modality method. With the new tri-modality image fusion method smaller inter- and intra-observer variation in GTV definition for the brain tumors can be achieved, which improves the consistency and accuracy for target delineation in individualized radiotherapy.
Magnetic resonance venography and three-dimensional image fusion guidance provide a novel paradigm for endovascular recanalization of chronic central venous occlusion.

PubMed

Schwein, Adeline; Lu, Tony; Chinnadurai, Ponraj; Kitkungvan, Danai; Shah, Dipan J; Chakfe, Nabil; Lumsden, Alan B; Bismuth, Jean

2017-01-01

Endovascular recanalization is considered first-line therapy for chronic central venous occlusion (CVO). Unlike arteries, in which landmarks such as wall calcifications provide indirect guidance for endovascular navigation, sclerotic veins without known vascular branching patterns impose significant challenges. Therefore, safe wire access through such chronic lesions mostly relies on intuition and experience. Studies have shown that magnetic resonance venography (MRV) can be performed safely in these patients, and the boundaries of occluded veins may be visualized on specific MRV sequences. Intraoperative image fusion techniques have become more common to guide complex arterial endovascular procedures. The aim of this study was to assess the feasibility and utility of MRV and intraoperative cone-beam computed tomography (CBCT) image fusion technique during endovascular CVO recanalization. During the study period, patients with symptomatic CVO and failed standard endovascular recanalization underwent further recanalization attempts with use of intraoperative MRV image fusion guidance. After preoperative MRV and intraoperative CBCT image coregistration, a virtual centerline path of the occluded segment was electronically marked in MRV and overlaid on real-time two-dimensional fluoroscopy images. Technical success, fluoroscopy times, radiation doses, number of venograms before recanalization, and accuracy of the virtual centerline overlay were evaluated. Four patients underwent endovascular CVO recanalization with use of intraoperative MRV image fusion guidance. Mean (± standard deviation) time for image fusion was 6:36 ± 00:51 mm:ss. The lesion was successfully crossed in all patients without complications. Mean fluoroscopy time for lesion crossing was 12.5 ± 3.4 minutes. Mean total fluoroscopy time was 28.8 ± 6.5 minutes. Mean total radiation dose was 15,185 ± 7747 μGy/m 2 , and mean radiation dose from CBCT acquisition was 2788 ± 458 μGy/m 2 (18% of mean total radiation dose). Mean number of venograms before recanalization was 1.6 ± 0.9, whereas two lesions were crossed without any prior venography. On qualitative analysis, virtual centerlines from MRV were aligned with actual guidewire trajectory on fluoroscopy in all four cases. MRV image fusion is feasible and may improve success, safety, and the surgeon's confidence during CVO recanalization. Similar to arterial interventions, three-dimensional MRV imaging and image fusion techniques could foster innovative solutions for such complex venous interventions and have the potential to affect a great number of patients. Copyright © 2016 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.
Design of an Image Fusion Phantom for a Small Animal microPET/CT Scanner Prototype

NASA Astrophysics Data System (ADS)

Nava-García, Dante; Alva-Sánchez, Héctor; Murrieta-Rodríguez, Tirso; Martínez-Dávalos, Arnulfo; Rodríguez-Villafuerte, Mercedes

2010-12-01

Two separate microtomography systems recently developed at Instituto de Física, UNAM, produce anatomical (microCT) and physiological images (microPET) of small animals. In this work, the development and initial tests of an image fusion method based on fiducial markers for image registration between the two modalities are presented. A modular Helix/Line-Sources phantom was designed and constructed; this phantom contains fiducial markers that can be visualized in both imaging systems. The registration was carried out by solving the rigid body alignment problem of Procrustes to obtain rotation and translation matrices required to align the two sets of images. The microCT/microPET image fusion of the Helix/Line-Sources phantom shows excellent visual coincidence between different structures, showing a calculated target-registration-error of 0.32 mm.
Artificial intelligence (AI)-based relational matching and multimodal medical image fusion: generalized 3D approaches

NASA Astrophysics Data System (ADS)

Vajdic, Stevan M.; Katz, Henry E.; Downing, Andrew R.; Brooks, Michael J.

1994-09-01

A 3D relational image matching/fusion algorithm is introduced. It is implemented in the domain of medical imaging and is based on Artificial Intelligence paradigms--in particular, knowledge base representation and tree search. The 2D reference and target images are selected from 3D sets and segmented into non-touching and non-overlapping regions, using iterative thresholding and/or knowledge about the anatomical shapes of human organs. Selected image region attributes are calculated. Region matches are obtained using a tree search, and the error is minimized by evaluating a `goodness' of matching function based on similarities of region attributes. Once the matched regions are found and the spline geometric transform is applied to regional centers of gravity, images are ready for fusion and visualization into a single 3D image of higher clarity.
Three-Dimensional Image Fusion of 18F-Fluorodeoxyglucose-Positron Emission Tomography/Computed Tomography and Contrast-Enhanced Computed Tomography for Computer-Assisted Planning of Maxillectomy of Recurrent Maxillary Squamous Cell Carcinoma and Defect Reconstruction.

PubMed

Yu, Yao; Zhang, Wen-Bo; Liu, Xiao-Jing; Guo, Chuan-Bin; Yu, Guang-Yan; Peng, Xin

2017-06-01

The purpose of this study was to describe new technology assisted by 3-dimensional (3D) image fusion of 18 F-fluorodeoxyglucose (FDG)-positron emission tomography (PET)/computed tomography (CT) and contrast-enhanced CT (CECT) for computer planning of a maxillectomy of recurrent maxillary squamous cell carcinoma and defect reconstruction. Treatment of recurrent maxillary squamous cell carcinoma usually includes tumor resection and free flap reconstruction. FDG-PET/CT provided images of regions of abnormal glucose uptake and thus showed metabolic tumor volume to guide tumor resection. CECT data were used to create 3D reconstructed images of vessels to show the vascular diameters and locations, so that the most suitable vein and artery could be selected during anastomosis of the free flap. The data from preoperative maxillofacial CECT scans and FDG-PET/CT imaging were imported into the navigation system (iPlan 3.0; Brainlab, Feldkirchen, Germany). Three-dimensional image fusion between FDG-PET/CT and CECT was accomplished using Brainlab software according to the position of the 2 skulls simulated in the CECT image and PET/CT image, respectively. After verification of the image fusion accuracy, the 3D reconstruction images of the metabolic tumor, vessels, and other critical structures could be visualized within the same coordinate system. These sagittal, coronal, axial, and 3D reconstruction images were used to determine the virtual osteotomy sites and reconstruction plan, which was provided to the surgeon and used for surgical navigation. The average shift of the 3D image fusion between FDG-PET/CT and CECT was less than 1 mm. This technique, by clearly showing the metabolic tumor volume and the most suitable vessels for anastomosis, facilitated resection and reconstruction of recurrent maxillary squamous cell carcinoma. We used 3D image fusion of FDG-PET/CT and CECT to successfully accomplish resection and reconstruction of recurrent maxillary squamous cell carcinoma. This method has the potential to improve the clinical outcomes of these challenging procedures. Copyright © 2017 American Association of Oral and Maxillofacial Surgeons. Published by Elsevier Inc. All rights reserved.
Radar E-O image fusion

NASA Technical Reports Server (NTRS)

Oneil, William F.

1993-01-01

The fusion of radar and electro-optic (E-O) sensor images presents unique challenges. The two sensors measure different properties of the real three-dimensional (3-D) world. Forming the sensor outputs into a common format does not mask these differences. In this paper, the conditions under which fusion of the two sensor signals is possible are explored. The program currently planned to investigate this problem is briefly discussed.
[The poster as a communication medium].

PubMed

Tovar Samanez, C

1987-01-01

The poster as a medium of communication serves to transmit a message by means of a graphical synthesis. It elicits attention by its originality, contrast, and focus on the center of interest. The poster is effective if the images and slogans can be identified easily. Its visual attractiveness is also essential. The understanding of the message is the function of the cultural characteristics of the public with symbols, metaphors, gestures, and detailed description. The appeal of the message allows the public to accept it on sensorial, emotional, social, intellectual, and economical levels. Adverse motivations should not be confused with the positive appeal (prejudice, preconceived ideas, and bias). Confusion and ambiguity can carry conflicting messages, therefore negative examples should be avoided. The force of the message targets the memory carrying conviction and calling to action. The target group and objective must be defined as to age, occupation, location, and sex. The message also has to be defined precisely for the target audience. It is in the analysis of the context whereby the poster is received as to notions of the target topic, alternative attitudes relative to the promotion of the message, obstacles that are encountered in the mentality of the target, and cultural characteristics of the target audience. The text of the slogan must be given before drawing the poster. The designing of the poster should be creative with association of ideas, metaphors and symbols, descriptive images, fusion of symbolic and descriptive forms, humor, the fusion of graphics with letters, and the fusion of letters with images. Completed forms of the poster use illustration, photography, typography, calligraphy, and photo montage.
Multi exposure image fusion algorithm based on YCbCr space

NASA Astrophysics Data System (ADS)

Yang, T. T.; Fang, P. Y.

2018-05-01

To solve the problem that scene details and visual effects are difficult to be optimized in high dynamic image synthesis, we proposes a multi exposure image fusion algorithm for processing low dynamic range images in YCbCr space, and weighted blending of luminance and chromatic aberration components respectively. The experimental results show that the method can retain color effect of the fused image while balancing details of the bright and dark regions of the high dynamic image.
Infrared and Visible Image Fusion Based on Different Constraints in the Non-Subsampled Shearlet Transform Domain.

PubMed

Huang, Yan; Bi, Duyan; Wu, Dongpeng

2018-04-11

There are many artificial parameters when fuse infrared and visible images, to overcome the lack of detail in the fusion image because of the artifacts, a novel fusion algorithm for infrared and visible images that is based on different constraints in non-subsampled shearlet transform (NSST) domain is proposed. There are high bands and low bands of images that are decomposed by the NSST. After analyzing the characters of the bands, fusing the high level bands by the gradient constraint, the fused image can obtain more details; fusing the low bands by the constraint of saliency in the images, the targets are more salient. Before the inverse NSST, the Nash equilibrium is used to update the coefficient. The fused images and the quantitative results demonstrate that our method is more effective in reserving details and highlighting the targets when compared with other state-of-the-art methods.
Image retrieval by information fusion based on scalable vocabulary tree and robust Hausdorff distance

NASA Astrophysics Data System (ADS)

Che, Chang; Yu, Xiaoyang; Sun, Xiaoming; Yu, Boyang

2017-12-01

In recent years, Scalable Vocabulary Tree (SVT) has been shown to be effective in image retrieval. However, for general images where the foreground is the object to be recognized while the background is cluttered, the performance of the current SVT framework is restricted. In this paper, a new image retrieval framework that incorporates a robust distance metric and information fusion is proposed, which improves the retrieval performance relative to the baseline SVT approach. First, the visual words that represent the background are diminished by using a robust Hausdorff distance between different images. Second, image matching results based on three image signature representations are fused, which enhances the retrieval precision. We conducted intensive experiments on small-scale to large-scale image datasets: Corel-9, Corel-48, and PKU-198, where the proposed Hausdorff metric and information fusion outperforms the state-of-the-art methods by about 13, 15, and 15%, respectively.
Infrared and Visible Image Fusion Based on Different Constraints in the Non-Subsampled Shearlet Transform Domain

PubMed Central

Huang, Yan; Bi, Duyan; Wu, Dongpeng

2018-01-01

There are many artificial parameters when fuse infrared and visible images, to overcome the lack of detail in the fusion image because of the artifacts, a novel fusion algorithm for infrared and visible images that is based on different constraints in non-subsampled shearlet transform (NSST) domain is proposed. There are high bands and low bands of images that are decomposed by the NSST. After analyzing the characters of the bands, fusing the high level bands by the gradient constraint, the fused image can obtain more details; fusing the low bands by the constraint of saliency in the images, the targets are more salient. Before the inverse NSST, the Nash equilibrium is used to update the coefficient. The fused images and the quantitative results demonstrate that our method is more effective in reserving details and highlighting the targets when compared with other state-of-the-art methods. PMID:29641505
Fourier domain image fusion for differential X-ray phase-contrast breast imaging.

PubMed

Coello, Eduardo; Sperl, Jonathan I; Bequé, Dirk; Benz, Tobias; Scherer, Kai; Herzen, Julia; Sztrókay-Gaul, Anikó; Hellerhoff, Karin; Pfeiffer, Franz; Cozzini, Cristina; Grandl, Susanne

2017-04-01

X-Ray Phase-Contrast (XPC) imaging is a novel technology with a great potential for applications in clinical practice, with breast imaging being of special interest. This work introduces an intuitive methodology to combine and visualize relevant diagnostic features, present in the X-ray attenuation, phase shift and scattering information retrieved in XPC imaging, using a Fourier domain fusion algorithm. The method allows to present complementary information from the three acquired signals in one single image, minimizing the noise component and maintaining visual similarity to a conventional X-ray image, but with noticeable enhancement in diagnostic features, details and resolution. Radiologists experienced in mammography applied the image fusion method to XPC measurements of mastectomy samples and evaluated the feature content of each input and the fused image. This assessment validated that the combination of all the relevant diagnostic features, contained in the XPC images, was present in the fused image as well. Copyright © 2017 Elsevier B.V. All rights reserved.
Spatial Statistical Data Fusion for Remote Sensing Applications

NASA Technical Reports Server (NTRS)

Nguyen, Hai

2010-01-01

Data fusion is the process of combining information from heterogeneous sources into a single composite picture of the relevant process, such that the composite picture is generally more accurate and complete than that derived from any single source alone. Data collection is often incomplete, sparse, and yields incompatible information. Fusion techniques can make optimal use of such data. When investment in data collection is high, fusion gives the best return. Our study uses data from two satellites: (1) Multiangle Imaging SpectroRadiometer (MISR), (2) Moderate Resolution Imaging Spectroradiometer (MODIS).
An imaging method of wavefront coding system based on phase plate rotation

NASA Astrophysics Data System (ADS)

Yi, Rigui; Chen, Xi; Dong, Liquan; Liu, Ming; Zhao, Yuejin; Liu, Xiaohua

2018-01-01

Wave-front coding has a great prospect in extending the depth of the optical imaging system and reducing optical aberrations, but the image quality and noise performance are inevitably reduced. According to the theoretical analysis of the wave-front coding system and the phase function expression of the cubic phase plate, this paper analyzed and utilized the feature that the phase function expression would be invariant in the new coordinate system when the phase plate rotates at different angles around the z-axis, and we proposed a method based on the rotation of the phase plate and image fusion. First, let the phase plate rotated at a certain angle around the z-axis, the shape and distribution of the PSF obtained on the image surface remain unchanged, the rotation angle and direction are consistent with the rotation angle of the phase plate. Then, the middle blurred image is filtered by the point spread function of the rotation adjustment. Finally, the reconstruction images were fused by the method of the Laplacian pyramid image fusion and the Fourier transform spectrum fusion method, and the results were evaluated subjectively and objectively. In this paper, we used Matlab to simulate the images. By using the Laplacian pyramid image fusion method, the signal-to-noise ratio of the image is increased by 19% 27%, the clarity is increased by 11% 15% , and the average gradient is increased by 4% 9% . By using the Fourier transform spectrum fusion method, the signal-to-noise ratio of the image is increased by 14% 23%, the clarity is increased by 6% 11% , and the average gradient is improved by 2% 6%. The experimental results show that the image processing by the above method can improve the quality of the restored image, improving the image clarity, and can effectively preserve the image information.

A new method of Quickbird own image fusion

NASA Astrophysics Data System (ADS)

Han, Ying; Jiang, Hong; Zhang, Xiuying

2009-10-01

With the rapid development of remote sensing technology, the means of accessing to remote sensing data become increasingly abundant, thus the same area can form a large number of multi-temporal, different resolution image sequence. At present, the fusion methods are mainly: HPF, IHS transform method, PCA method, Brovey, Mallat algorithm and wavelet transform and so on. There exists a serious distortion of the spectrums in the IHS transform, Mallat algorithm omits low-frequency information of the high spatial resolution images, the integration results of which has obvious blocking effects. Wavelet multi-scale decomposition for different sizes, the directions, details and the edges can have achieved very good results, but different fusion rules and algorithms can achieve different effects. This article takes the Quickbird own image fusion as an example, basing on wavelet transform and HVS, wavelet transform and IHS integration. The result shows that the former better. This paper introduces the correlation coefficient, the relative average spectral error index and usual index to evaluate the quality of image.
Simultaneous usage of pinhole and penumbral apertures for imaging small scale neutron sources from inertial confinement fusion experiments.

PubMed

Guler, N; Volegov, P; Danly, C R; Grim, G P; Merrill, F E; Wilde, C H

2012-10-01

Inertial confinement fusion experiments at the National Ignition Facility are designed to understand the basic principles of creating self-sustaining fusion reactions by laser driven compression of deuterium-tritium (DT) filled cryogenic plastic capsules. The neutron imaging diagnostic provides information on the distribution of the central fusion reaction region and the surrounding DT fuel by observing neutron images in two different energy bands for primary (13-17 MeV) and down-scattered (6-12 MeV) neutrons. From this, the final shape and size of the compressed capsule can be estimated and the symmetry of the compression can be inferred. These experiments provide small sources with high yield neutron flux. An aperture design that includes an array of pinholes and penumbral apertures has provided the opportunity to image the same source with two different techniques. This allows for an evaluation of these different aperture designs and reconstruction algorithms.
First downscattered neutron images from Inertial Confinement Fusion experiments at the National Ignition Facility

NASA Astrophysics Data System (ADS)

Guler, Nevzat; Aragonez, Robert J.; Archuleta, Thomas N.; Batha, Steven H.; Clark, David D.; Clark, Deborah J.; Danly, Chris R.; Day, Robert D.; Fatherley, Valerie E.; Finch, Joshua P.; Gallegos, Robert A.; Garcia, Felix P.; Grim, Gary; Hsu, Albert H.; Jaramillo, Steven A.; Loomis, Eric N.; Mares, Danielle; Martinson, Drew D.; Merrill, Frank E.; Morgan, George L.; Munson, Carter; Murphy, Thomas J.; Oertel, John A.; Polk, Paul J.; Schmidt, Derek W.; Tregillis, Ian L.; Valdez, Adelaida C.; Volegov, Petr L.; Wang, Tai-Sen F.; Wilde, Carl H.; Wilke, Mark D.; Wilson, Douglas C.; Atkinson, Dennis P.; Bower, Dan E.; Drury, Owen B.; Dzenitis, John M.; Felker, Brian; Fittinghoff, David N.; Frank, Matthias; Liddick, Sean N.; Moran, Michael J.; Roberson, George P.; Weiss, Paul; Buckles, Robert A.; Cradick, Jerry R.; Kaufman, Morris I.; Lutz, Steve S.; Malone, Robert M.; Traille, Albert

2013-11-01

Inertial Confinement Fusion experiments at the National Ignition Facility (NIF) are designed to understand and test the basic principles of self-sustaining fusion reactions by laser driven compression of deuterium-tritium (DT) filled cryogenic plastic (CH) capsules. The experimental campaign is ongoing to tune the implosions and characterize the burning plasma conditions. Nuclear diagnostics play an important role in measuring the characteristics of these burning plasmas, providing feedback to improve the implosion dynamics. The Neutron Imaging (NI) diagnostic provides information on the distribution of the central fusion reaction region and the surrounding DT fuel by collecting images at two different energy bands for primary (13-15 MeV) and downscattered (10-12 MeV) neutrons. From these distributions, the final shape and size of the compressed capsule can be estimated and the symmetry of the compression can be inferred. The first downscattered neutron images from imploding ICF capsules are shown in this paper.
The Nonsubsampled Contourlet Transform Based Statistical Medical Image Fusion Using Generalized Gaussian Density

PubMed Central

Yang, Guocheng; Li, Meiling; Chen, Leiting; Yu, Jie

2015-01-01

We propose a novel medical image fusion scheme based on the statistical dependencies between coefficients in the nonsubsampled contourlet transform (NSCT) domain, in which the probability density function of the NSCT coefficients is concisely fitted using generalized Gaussian density (GGD), as well as the similarity measurement of two subbands is accurately computed by Jensen-Shannon divergence of two GGDs. To preserve more useful information from source images, the new fusion rules are developed to combine the subbands with the varied frequencies. That is, the low frequency subbands are fused by utilizing two activity measures based on the regional standard deviation and Shannon entropy and the high frequency subbands are merged together via weight maps which are determined by the saliency values of pixels. The experimental results demonstrate that the proposed method significantly outperforms the conventional NSCT based medical image fusion approaches in both visual perception and evaluation indices. PMID:26557871
High resolution isotopic analysis of U-bearing particles via fusion of SIMS and EDS images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tarolli, Jay G.; Naes, Benjamin E.; Garcia, Benjamin J.

Image fusion of secondary ion mass spectrometry (SIMS) images and X-ray elemental maps from energy-dispersive spectroscopy (EDS) was performed to facilitate the isolation and re-analysis of isotopically unique U-bearing particles where the highest precision SIMS measurements are required. Image registration, image fusion and particle micromanipulation were performed on a subset of SIMS images obtained from a large area pre-screen of a particle distribution from a sample containing several certified reference materials (CRM) U129A, U015, U150, U500 and U850, as well as a standard reference material (SRM) 8704 (Buffalo River Sediment) to simulate particles collected on swipes during routine inspections ofmore » declared uranium enrichment facilities by the International Atomic Energy Agency (IAEA). In total, fourteen particles, ranging in size from 5 – 15 µm, were isolated and re-analyzed by SIMS in multi-collector mode identifying nine particles of CRM U129A, one of U150, one of U500 and three of U850. These identifications were made within a few percent errors from the National Institute of Standards and Technology (NIST) certified atom percent values for 234U, 235U and 238U for the corresponding CRMs. This work represents the first use of image fusion to enhance the accuracy and precision of isotope ratio measurements for isotopically unique U-bearing particles for nuclear safeguards applications. Implementation of image fusion is essential for the identification of particles of interests that fall below the spatial resolution of the SIMS images.« less
Dual-axis reflective continuous-wave terahertz confocal scanning polarization imaging and image fusion

NASA Astrophysics Data System (ADS)

Zhou, Yi; Li, Qi

2017-01-01

A dual-axis reflective continuous-wave terahertz (THz) confocal scanning polarization imaging system was adopted. THz polarization imaging experiments on gaps on film and metallic letters "BeLLE" were carried out. Imaging results indicate that the THz polarization imaging is sensitive to the tilted gap or wide flat gap, suggesting the THz polarization imaging is able to detect edges and stains. An image fusion method based on the digital image processing was proposed to ameliorate the imaging quality of metallic letters "BeLLE." Objective and subjective evaluation both prove that this method can improve the imaging quality.
The fusion of satellite and UAV data: simulation of high spatial resolution band

NASA Astrophysics Data System (ADS)

Jenerowicz, Agnieszka; Siok, Katarzyna; Woroszkiewicz, Malgorzata; Orych, Agata

2017-10-01

Remote sensing techniques used in the precision agriculture and farming that apply imagery data obtained with sensors mounted on UAV platforms became more popular in the last few years due to the availability of low- cost UAV platforms and low- cost sensors. Data obtained from low altitudes with low- cost sensors can be characterised by high spatial and radiometric resolution but quite low spectral resolution, therefore the application of imagery data obtained with such technology is quite limited and can be used only for the basic land cover classification. To enrich the spectral resolution of imagery data acquired with low- cost sensors from low altitudes, the authors proposed the fusion of RGB data obtained with UAV platform with multispectral satellite imagery. The fusion is based on the pansharpening process, that aims to integrate the spatial details of the high-resolution panchromatic image with the spectral information of lower resolution multispectral or hyperspectral imagery to obtain multispectral or hyperspectral images with high spatial resolution. The key of pansharpening is to properly estimate the missing spatial details of multispectral images while preserving their spectral properties. In the research, the authors presented the fusion of RGB images (with high spatial resolution) obtained with sensors mounted on low- cost UAV platforms and multispectral satellite imagery with satellite sensors, i.e. Landsat 8 OLI. To perform the fusion of UAV data with satellite imagery, the simulation of the panchromatic bands from RGB data based on the spectral channels linear combination, was conducted. Next, for simulated bands and multispectral satellite images, the Gram-Schmidt pansharpening method was applied. As a result of the fusion, the authors obtained several multispectral images with very high spatial resolution and then analysed the spatial and spectral accuracies of processed images.
Virtual pathology of cervical radiculopathy based on 3D MR/CT fusion images: impingement, flattening or twisted condition of the compressed nerve root in three cases.

PubMed

Kamogawa, Junji; Kato, Osamu; Morizane, Tatsunori; Hato, Taizo

2015-01-01

There have been several imaging studies of cervical radiculopathy, but no three-dimensional (3D) images have shown the path, position, and pathological changes of the cervical nerve roots and spinal root ganglion relative to the cervical bony structure. The objective of this study was to introduce a technique that enables the virtual pathology of the nerve root to be assessed using 3D magnetic resonance (MR)/computed tomography (CT) fusion images that show the compression of the proximal portion of the cervical nerve root by both the herniated disc and the preforaminal or foraminal bony spur in patients with cervical radiculopathy. MR and CT images were obtained from three patients with cervical radiculopathy. 3D MR images were placed onto 3D CT images using a computer workstation. The entire nerve root could be visualized in 3D with or without the vertebrae. The most important characteristic evident on the images was flattening of the nerve root by a bony spur. The affected root was constricted at a pre-ganglion site. In cases of severe deformity, the flattened portion of the root seemed to change the angle of its path, resulting in twisted condition. The 3D MR/CT fusion imaging technique enhances visualization of pathoanatomy in cervical hidden area that is composed of the root and intervertebral foramen. This technique provides two distinct advantages for diagnosis of cervical radiculopathy. First, the isolation of individual vertebra clarifies the deformities of the whole root groove, including both the uncinate process and superior articular process in the cervical spine. Second, the tortuous or twisted condition of a compressed root can be visualized. The surgeon can identify the narrowest face of the root if they view the MR/CT fusion image from the posterolateral-inferior direction. Surgeons use MR/CT fusion images as a pre-operative map and for intraoperative navigation. The MR/CT fusion images can also be used as educational materials for all hospital staff and for patients and patients' families who provide informed consent for treatments.
Enhancement of Tropical Land Cover Mapping with Wavelet-Based Fusion and Unsupervised Clustering of SAR and Landsat Image Data

NASA Technical Reports Server (NTRS)

LeMoigne, Jacqueline; Laporte, Nadine; Netanyahuy, Nathan S.; Zukor, Dorothy (Technical Monitor)

2001-01-01

The characterization and the mapping of land cover/land use of forest areas, such as the Central African rainforest, is a very complex task. This complexity is mainly due to the extent of such areas and, as a consequence, to the lack of full and continuous cloud-free coverage of those large regions by one single remote sensing instrument, In order to provide improved vegetation maps of Central Africa and to develop forest monitoring techniques for applications at the local and regional scales, we propose to utilize multi-sensor remote sensing observations coupled with in-situ data. Fusion and clustering of multi-sensor data are the first steps towards the development of such a forest monitoring system. In this paper, we will describe some preliminary experiments involving the fusion of SAR and Landsat image data of the Lope Reserve in Gabon. Similarly to previous fusion studies, our fusion method is wavelet-based. The fusion provides a new image data set which contains more detailed texture features and preserves the large homogeneous regions that are observed by the Thematic Mapper sensor. The fusion step is followed by unsupervised clustering and provides a vegetation map of the area.
A wavelet-based adaptive fusion algorithm of infrared polarization imaging

NASA Astrophysics Data System (ADS)

Yang, Wei; Gu, Guohua; Chen, Qian; Zeng, Haifang

2011-08-01

The purpose of infrared polarization image is to highlight man-made target from a complex natural background. For the infrared polarization images can significantly distinguish target from background with different features, this paper presents a wavelet-based infrared polarization image fusion algorithm. The method is mainly for image processing of high-frequency signal portion, as for the low frequency signal, the original weighted average method has been applied. High-frequency part is processed as follows: first, the source image of the high frequency information has been extracted by way of wavelet transform, then signal strength of 3*3 window area has been calculated, making the regional signal intensity ration of source image as a matching measurement. Extraction method and decision mode of the details are determined by the decision making module. Image fusion effect is closely related to the setting threshold of decision making module. Compared to the commonly used experiment way, quadratic interpolation optimization algorithm is proposed in this paper to obtain threshold. Set the endpoints and midpoint of the threshold searching interval as initial interpolation nodes, and compute the minimum quadratic interpolation function. The best threshold can be obtained by comparing the minimum quadratic interpolation function. A series of image quality evaluation results show this method has got improvement in fusion effect; moreover, it is not only effective for some individual image, but also for a large number of images.
Accuracy and feasibility of three different methods for software-based image fusion in whole-body PET and CT.

PubMed

Putzer, Daniel; Henninger, Benjamin; Kovacs, Peter; Uprimny, Christian; Kendler, Dorota; Jaschke, Werner; Bale, Reto J

2016-06-01

Even as PET/CT provides valuable diagnostic information in a great number of clinical indications, availability of hybrid PET/CT scanners is mainly limited to clinical centers. A software-based image fusion would facilitate combined image reading of CT and PET data sets if hardware image fusion is not available. To analyze the relevance of retrospective image fusion of separately acquired PET and CT data sets, we studied the accuracy, practicability and reproducibility of three different image registration techniques. We evaluated whole-body 18F-FDG-PET and CT data sets of 71 oncologic patients. Images were fused retrospectively using Stealth Station System, Treon (Medtronic Inc., Louisville, CO, USA) equipped with Cranial4 Software. External markers fixed to a vacuum mattress were used as reference for exact repositioning. Registration was repeated using internal anatomic landmarks and Automerge software, assessing accuracy for all three methods, measuring distances of liver representation in CT and PET with reference to a common coordinate system. On first measurement of image fusions with external markers, 53 were successful, 16 feasible and 2 not successful. Using anatomic landmarks, 42 were successful, 26 feasible and 3 not successful. Using Automerge Software only 13 were successful. The mean distance between center points in PET and CT was 7.69±4.96 mm on first, and 7.65±4.2 mm on second measurement. Results with external markers correlate very well and inaccuracies are significantly lower (P<0.001) than results using anatomical landmarks (10.38±6.13 mm and 10.83±6.23 mm). Analysis revealed a significantly faster alignment using external markers (P<0.001). External fiducials in combination with immobilization devices and breathing protocols allow for highly accurate image fusion cost-effectively and significantly less time, posing an attractive alternative for PET/CT interpretation when a hybrid scanner is not available.
Robust multi-atlas label propagation by deep sparse representation

PubMed Central

Zu, Chen; Wang, Zhengxia; Zhang, Daoqiang; Liang, Peipeng; Shi, Yonghong; Shen, Dinggang; Wu, Guorong

2016-01-01

Recently, multi-atlas patch-based label fusion has achieved many successes in medical imaging area. The basic assumption in the current state-of-the-art approaches is that the image patch at the target image point can be represented by a patch dictionary consisting of atlas patches from registered atlas images. Therefore, the label at the target image point can be determined by fusing labels of atlas image patches with similar anatomical structures. However, such assumption on image patch representation does not always hold in label fusion since (1) the image content within the patch may be corrupted due to noise and artifact; and (2) the distribution of morphometric patterns among atlas patches might be unbalanced such that the majority patterns can dominate label fusion result over other minority patterns. The violation of the above basic assumptions could significantly undermine the label fusion accuracy. To overcome these issues, we first consider forming label-specific group for the atlas patches with the same label. Then, we alter the conventional flat and shallow dictionary to a deep multi-layer structure, where the top layer (label-specific dictionaries) consists of groups of representative atlas patches and the subsequent layers (residual dictionaries) hierarchically encode the patchwise residual information in different scales. Thus, the label fusion follows the representation consensus across representative dictionaries. However, the representation of target patch in each group is iteratively optimized by using the representative atlas patches in each label-specific dictionary exclusively to match the principal patterns and also using all residual patterns across groups collaboratively to overcome the issue that some groups might be absent of certain variation patterns presented in the target image patch. Promising segmentation results have been achieved in labeling hippocampus on ADNI dataset, as well as basal ganglia and brainstem structures, compared to other counterpart label fusion methods. PMID:27942077
Robust multi-atlas label propagation by deep sparse representation.

PubMed

Zu, Chen; Wang, Zhengxia; Zhang, Daoqiang; Liang, Peipeng; Shi, Yonghong; Shen, Dinggang; Wu, Guorong

2017-03-01

Recently, multi-atlas patch-based label fusion has achieved many successes in medical imaging area. The basic assumption in the current state-of-the-art approaches is that the image patch at the target image point can be represented by a patch dictionary consisting of atlas patches from registered atlas images. Therefore, the label at the target image point can be determined by fusing labels of atlas image patches with similar anatomical structures. However, such assumption on image patch representation does not always hold in label fusion since (1) the image content within the patch may be corrupted due to noise and artifact; and (2) the distribution of morphometric patterns among atlas patches might be unbalanced such that the majority patterns can dominate label fusion result over other minority patterns. The violation of the above basic assumptions could significantly undermine the label fusion accuracy. To overcome these issues, we first consider forming label-specific group for the atlas patches with the same label. Then, we alter the conventional flat and shallow dictionary to a deep multi-layer structure, where the top layer ( label-specific dictionaries ) consists of groups of representative atlas patches and the subsequent layers ( residual dictionaries ) hierarchically encode the patchwise residual information in different scales. Thus, the label fusion follows the representation consensus across representative dictionaries. However, the representation of target patch in each group is iteratively optimized by using the representative atlas patches in each label-specific dictionary exclusively to match the principal patterns and also using all residual patterns across groups collaboratively to overcome the issue that some groups might be absent of certain variation patterns presented in the target image patch. Promising segmentation results have been achieved in labeling hippocampus on ADNI dataset, as well as basal ganglia and brainstem structures, compared to other counterpart label fusion methods.
Effects of spatial resolution ratio in image fusion

USGS Publications Warehouse

Ling, Y.; Ehlers, M.; Usery, E.L.; Madden, M.

2008-01-01

In image fusion, the spatial resolution ratio can be defined as the ratio between the spatial resolution of the high-resolution panchromatic image and that of the low-resolution multispectral image. This paper attempts to assess the effects of the spatial resolution ratio of the input images on the quality of the fused image. Experimental results indicate that a spatial resolution ratio of 1:10 or higher is desired for optimal multisensor image fusion provided the input panchromatic image is not downsampled to a coarser resolution. Due to the synthetic pixels generated from resampling, the quality of the fused image decreases as the spatial resolution ratio decreases (e.g. from 1:10 to 1:30). However, even with a spatial resolution ratio as small as 1:30, the quality of the fused image is still better than the original multispectral image alone for feature interpretation. In cases where the spatial resolution ratio is too small (e.g. 1:30), to obtain better spectral integrity of the fused image, one may downsample the input high-resolution panchromatic image to a slightly lower resolution before fusing it with the multispectral image.
Multiple-algorithm parallel fusion of infrared polarization and intensity images based on algorithmic complementarity and synergy

NASA Astrophysics Data System (ADS)

Zhang, Lei; Yang, Fengbao; Ji, Linna; Lv, Sheng

2018-01-01

Diverse image fusion methods perform differently. Each method has advantages and disadvantages compared with others. One notion is that the advantages of different image methods can be effectively combined. A multiple-algorithm parallel fusion method based on algorithmic complementarity and synergy is proposed. First, in view of the characteristics of the different algorithms and difference-features among images, an index vector-based feature-similarity is proposed to define the degree of complementarity and synergy. This proposed index vector is a reliable evidence indicator for algorithm selection. Second, the algorithms with a high degree of complementarity and synergy are selected. Then, the different degrees of various features and infrared intensity images are used as the initial weights for the nonnegative matrix factorization (NMF). This avoids randomness of the NMF initialization parameter. Finally, the fused images of different algorithms are integrated using the NMF because of its excellent data fusing performance on independent features. Experimental results demonstrate that the visual effect and objective evaluation index of the fused images obtained using the proposed method are better than those obtained using traditional methods. The proposed method retains all the advantages that individual fusion algorithms have.
3D SPECT/CT fusion using image data projection of bone SPECT onto 3D volume-rendered CT images: feasibility and clinical impact in the diagnosis of bone metastasis.

PubMed

Ogata, Yuji; Nakahara, Tadaki; Ode, Kenichi; Matsusaka, Yohji; Katagiri, Mari; Iwabuchi, Yu; Itoh, Kazunari; Ichimura, Akira; Jinzaki, Masahiro

2017-05-01

We developed a method of image data projection of bone SPECT into 3D volume-rendered CT images for 3D SPECT/CT fusion. The aims of our study were to evaluate its feasibility and clinical usefulness. Whole-body bone scintigraphy (WB) and SPECT/CT scans were performed in 318 cancer patients using a dedicated SPECT/CT systems. Volume data of bone SPECT and CT were fused to obtain 2D SPECT/CT images. To generate our 3D SPECT/CT images, colored voxel data of bone SPECT were projected onto the corresponding location of the volume-rendered CT data after a semi-automatic bone extraction. Then, the resultant 3D images were blended with conventional volume-rendered CT images, allowing to grasp the three-dimensional relationship between bone metabolism and anatomy. WB and SPECT (WB + SPECT), 2D SPECT/CT fusion, and 3D SPECT/CT fusion were evaluated by two independent reviewers in the diagnosis of bone metastasis. The inter-observer variability and diagnostic accuracy in these three image sets were investigated using a four-point diagnostic scale. Increased bone metabolism was found in 744 metastatic sites and 1002 benign changes. On a per-lesion basis, inter-observer agreements in the diagnosis of bone metastasis were 0.72 for WB + SPECT, 0.90 for 2D SPECT/CT, and 0.89 for 3D SPECT/CT. Receiver operating characteristic analyses for the diagnostic accuracy of bone metastasis showed that WB + SPECT, 2D SPECT/CT, and 3D SPECT/CT had an area under the curve of 0.800, 0.983, and 0.983 for reader 1, 0.865, 0.992, and 0.993 for reader 2, respectively (WB + SPECT vs. 2D or 3D SPECT/CT, p < 0.001; 2D vs. 3D SPECT/CT, n.s.). The durations of interpretation of WB + SPECT, 2D SPECT/CT, and 3D SPECT/CT images were 241 ± 75, 225 ± 73, and 182 ± 71 s for reader 1 and 207 ± 72, 190 ± 73, and 179 ± 73 s for reader 2, respectively. As a result, it took shorter time to read 3D SPECT/CT images than 2D SPECT/CT (p < 0.0001) or WB + SPECT images (p < 0.0001). 3D SPECT/CT fusion offers comparable diagnostic accuracy to 2D SPECT/CT fusion. The visual effect of 3D SPECT/CT fusion facilitates reduction of reading time compared to 2D SPECT/CT fusion.
Advanced Image Processing for NASA Applications

NASA Technical Reports Server (NTRS)

LeMoign, Jacqueline

2007-01-01

The future of space exploration will involve cooperating fleets of spacecraft or sensor webs geared towards coordinated and optimal observation of Earth Science phenomena. The main advantage of such systems is to utilize multiple viewing angles as well as multiple spatial and spectral resolutions of sensors carried on multiple spacecraft but acting collaboratively as a single system. Within this framework, our research focuses on all areas related to sensing in collaborative environments, which means systems utilizing intracommunicating spatially distributed sensor pods or crafts being deployed to monitor or explore different environments. This talk will describe the general concept of sensing in collaborative environments, will give a brief overview of several technologies developed at NASA Goddard Space Flight Center in this area, and then will concentrate on specific image processing research related to that domain, specifically image registration and image fusion.
Prostate seed implant quality assessment using MR and CT image fusion.

PubMed

Amdur, R J; Gladstone, D; Leopold, K A; Harris, R D

1999-01-01

After a seed implant of the prostate, computerized tomography (CT) is ideal for determining seed distribution but soft tissue anatomy is frequently not well visualized. Magnetic resonance (MR) images soft tissue anatomy well but seed visualization is problematic. We describe a method of fusing CT and MR images to exploit the advantages of both of these modalities when assessing the quality of a prostate seed implant. Eleven consecutive prostate seed implant patients were imaged with axial MR and CT scans. MR and CT images were fused in three dimensions using the Pinnacle 3.0 version of the ADAC treatment planning system. The urethra and bladder base were used to "line up" MR and CT image sets during image fusion. Alignment was accomplished using translation and rotation in the three ortho-normal planes. Accuracy of image fusion was evaluated by calculating the maximum deviation in millimeters between the center of the urethra on axial MR versus CT images. Implant quality was determined by comparing dosimetric results to previously set parameters. Image fusion was performed with a high degree of accuracy. When lining up the urethra and base of bladder, the maximum difference in axial position of the urethra between MR and CT averaged 2.5 mm (range 1.3-4.0 mm, SD 0.9 mm). By projecting CT-derived dose distributions over MR images of soft tissue structures, qualitative and quantitative evaluation of implant quality is straightforward. The image-fusion process we describe provides a sophisticated way of assessing the quality of a prostate seed implant. Commercial software makes the process time-efficient and available to any clinical practice with a high-quality treatment planning system. While we use MR to image soft tissue structures, the process could be used with any imaging modality that is able to visualize the prostatic urethra (e.g., ultrasound).
Automated image-based assay for evaluation of HIV neutralization and cell-to-cell fusion inhibition.

PubMed

Sheik-Khalil, Enas; Bray, Mark-Anthony; Özkaya Şahin, Gülsen; Scarlatti, Gabriella; Jansson, Marianne; Carpenter, Anne E; Fenyö, Eva Maria

2014-08-30

Standardized techniques to detect HIV-neutralizing antibody responses are of great importance in the search for an HIV vaccine. Here, we present a high-throughput, high-content automated plaque reduction (APR) assay based on automated microscopy and image analysis that allows evaluation of neutralization and inhibition of cell-cell fusion within the same assay. Neutralization of virus particles is measured as a reduction in the number of fluorescent plaques, and inhibition of cell-cell fusion as a reduction in plaque area. We found neutralization strength to be a significant factor in the ability of virus to form syncytia. Further, we introduce the inhibitory concentration of plaque area reduction (ICpar) as an additional measure of antiviral activity, i.e. fusion inhibition. We present an automated image based high-throughput, high-content HIV plaque reduction assay. This allows, for the first time, simultaneous evaluation of neutralization and inhibition of cell-cell fusion within the same assay, by quantifying the reduction in number of plaques and mean plaque area, respectively. Inhibition of cell-to-cell fusion requires higher quantities of inhibitory reagent than inhibition of virus neutralization.
Infrared and visible image fusion based on visual saliency map and weighted least square optimization

NASA Astrophysics Data System (ADS)

Ma, Jinlei; Zhou, Zhiqiang; Wang, Bo; Zong, Hua

2017-05-01

The goal of infrared (IR) and visible image fusion is to produce a more informative image for human observation or some other computer vision tasks. In this paper, we propose a novel multi-scale fusion method based on visual saliency map (VSM) and weighted least square (WLS) optimization, aiming to overcome some common deficiencies of conventional methods. Firstly, we introduce a multi-scale decomposition (MSD) using the rolling guidance filter (RGF) and Gaussian filter to decompose input images into base and detail layers. Compared with conventional MSDs, this MSD can achieve the unique property of preserving the information of specific scales and reducing halos near edges. Secondly, we argue that the base layers obtained by most MSDs would contain a certain amount of residual low-frequency information, which is important for controlling the contrast and overall visual appearance of the fused image, and the conventional "averaging" fusion scheme is unable to achieve desired effects. To address this problem, an improved VSM-based technique is proposed to fuse the base layers. Lastly, a novel WLS optimization scheme is proposed to fuse the detail layers. This optimization aims to transfer more visual details and less irrelevant IR details or noise into the fused image. As a result, the fused image details would appear more naturally and be suitable for human visual perception. Experimental results demonstrate that our method can achieve a superior performance compared with other fusion methods in both subjective and objective assessments.

Assessment of a liquid lens enabled in vivo optical coherence microscope.

PubMed

Murali, Supraja; Meemon, Panomsak; Lee, Kye-Sung; Kuhn, William P; Thompson, Kevin P; Rolland, Jannick P

2010-06-01

The optical aberrations induced by imaging through skin can be predicted using formulas for Seidel aberrations of a plane-parallel plate. Knowledge of these aberrations helps to guide the choice of numerical aperture (NA) of the optics we can use in an implementation of Gabor domain optical coherence microscopy (GD-OCM), where the focus is the only aberration adjustment made through depth. On this basis, a custom-designed, liquid-lens enabled dynamic focusing optical coherence microscope operating at 0.2 NA is analyzed and validated experimentally. As part of the analysis, we show that the full width at half-maximum metric, as a characteristic descriptor for the point spread function, while commonly used, is not a useful metric for quantifying resolution in non-diffraction-limited systems. Modulation transfer function (MTF) measurements quantify that the liquid lens performance is as predicted by design, even when accounting for the effect of gravity. MTF measurements in a skinlike scattering medium also quantify the performance of the microscope in its potential applications. To guide the fusion of images across the various focus positions of the microscope, as required in GD-OCM, we present depth of focus measurements that can be used to determine the effective number of focusing zones required for a given goal resolution. Subcellular resolution in an onion sample, and high-definition in vivo imaging in human skin are demonstrated with the custom-designed and built microscope.
Adaptive multiple super fast simulated annealing for stochastic microstructure reconstruction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ryu, Seun; Lin, Guang; Sun, Xin

2013-01-01

Fast image reconstruction from statistical information is critical in image fusion from multimodality chemical imaging instrumentation to create high resolution image with large domain. Stochastic methods have been used widely in image reconstruction from two point correlation function. The main challenge is to increase the efficiency of reconstruction. A novel simulated annealing method is proposed for fast solution of image reconstruction. Combining the advantage of very fast cooling schedules, dynamic adaption and parallelization, the new simulation annealing algorithm increases the efficiencies by several orders of magnitude, making the large domain image fusion feasible.
Dense Plasma Focus - From Alternative Fusion Source to Versatile High Energy Density Plasma Source for Plasma Nanotechnology

NASA Astrophysics Data System (ADS)

Rawat, R. S.

2015-03-01

The dense plasma focus (DPF), a coaxial plasma gun, utilizes pulsed high current electrical discharge to heat and compress the plasma to very high density and temperature with energy densities in the range of 1-10 × 1010 J/m3. The DPF device has always been in the company of several alternative magnetic fusion devices as it produces intense fusion neutrons. Several experiments conducted on many different DPF devices ranging over several order of storage energy have demonstrated that at higher storage energy the neutron production does not follow I4 scaling laws and deteriorate significantly raising concern about the device's capability and relevance for fusion energy. On the other hand, the high energy density pinch plasma in DPF device makes it a multiple radiation source of ions, electron, soft and hard x-rays, and neutrons, making it useful for several applications in many different fields such as lithography, radiography, imaging, activation analysis, radioisotopes production etc. Being a source of hot dense plasma, strong shockwave, intense energetic beams and radiation, etc, the DPF device, additionally, shows tremendous potential for applications in plasma nanoscience and plasma nanotechnology. In the present paper, the key features of plasma focus device are critically discussed to understand the novelties and opportunities that this device offers in processing and synthesis of nanophase materials using, both, the top-down and bottom-up approach. The results of recent key experimental investigations performed on (i) the processing and modification of bulk target substrates for phase change, surface reconstruction and nanostructurization, (ii) the nanostructurization of PLD grown magnetic thin films, and (iii) direct synthesis of nanostructured (nanowire, nanosheets and nanoflowers) materials using anode target material ablation, ablated plasma and background reactive gas based synthesis and purely gas phase synthesis of various different types of nanostructured materials using DPF device will discussed to establish this device as versatile tool for plasma nanotechnology.
Object-based land cover classification based on fusion of multifrequency SAR data and THAICHOTE optical imagery

NASA Astrophysics Data System (ADS)

Sukawattanavijit, Chanika; Srestasathiern, Panu

2017-10-01

Land Use and Land Cover (LULC) information are significant to observe and evaluate environmental change. LULC classification applying remotely sensed data is a technique popularly employed on a global and local dimension particularly, in urban areas which have diverse land cover types. These are essential components of the urban terrain and ecosystem. In the present, object-based image analysis (OBIA) is becoming widely popular for land cover classification using the high-resolution image. COSMO-SkyMed SAR data was fused with THAICHOTE (namely, THEOS: Thailand Earth Observation Satellite) optical data for land cover classification using object-based. This paper indicates a comparison between object-based and pixel-based approaches in image fusion. The per-pixel method, support vector machines (SVM) was implemented to the fused image based on Principal Component Analysis (PCA). For the objectbased classification was applied to the fused images to separate land cover classes by using nearest neighbor (NN) classifier. Finally, the accuracy assessment was employed by comparing with the classification of land cover mapping generated from fused image dataset and THAICHOTE image. The object-based data fused COSMO-SkyMed with THAICHOTE images demonstrated the best classification accuracies, well over 85%. As the results, an object-based data fusion provides higher land cover classification accuracy than per-pixel data fusion.
The impact of early shame memories in Binge Eating Disorder: The mediator effect of current body image shame and cognitive fusion.

PubMed

Duarte, Cristiana; Pinto-Gouveia, José

2017-12-01

This study examined the phenomenology of shame experiences from childhood and adolescence in a sample of women with Binge Eating Disorder. Moreover, a path analysis was investigated testing whether the association between shame-related memories which are traumatic and central to identity, and binge eating symptoms' severity, is mediated by current external shame, body image shame and body image cognitive fusion. Participants in this study were 114 patients, who were assessed through the Eating Disorder Examination and the Shame Experiences Interview, and through self-report measures of external shame, body image shame, body image cognitive fusion and binge eating symptoms. Shame experiences where physical appearance was negatively commented or criticized by others were the most frequently recalled. A path analysis showed a good fit between the hypothesised mediational model and the data. The traumatic and centrality qualities of shame-related memories predicted current external shame, especially body image shame. Current shame feelings were associated with body image cognitive fusion, which, in turn, predicted levels of binge eating symptomatology. Findings support the relevance of addressing early shame-related memories and negative affective and self-evaluative experiences, namely related to body image, in the understanding and management of binge eating. Copyright © 2017 Elsevier B.V. All rights reserved.
Statistical image quantification toward optimal scan fusion and change quantification

NASA Astrophysics Data System (ADS)

Potesil, Vaclav; Zhou, Xiang Sean

2007-03-01

Recent advance of imaging technology has brought new challenges and opportunities for automatic and quantitative analysis of medical images. With broader accessibility of more imaging modalities for more patients, fusion of modalities/scans from one time point and longitudinal analysis of changes across time points have become the two most critical differentiators to support more informed, more reliable and more reproducible diagnosis and therapy decisions. Unfortunately, scan fusion and longitudinal analysis are both inherently plagued with increased levels of statistical errors. A lack of comprehensive analysis by imaging scientists and a lack of full awareness by physicians pose potential risks in clinical practice. In this paper, we discuss several key error factors affecting imaging quantification, studying their interactions, and introducing a simulation strategy to establish general error bounds for change quantification across time. We quantitatively show that image resolution, voxel anisotropy, lesion size, eccentricity, and orientation are all contributing factors to quantification error; and there is an intricate relationship between voxel anisotropy and lesion shape in affecting quantification error. Specifically, when two or more scans are to be fused at feature level, optimal linear fusion analysis reveals that scans with voxel anisotropy aligned with lesion elongation should receive a higher weight than other scans. As a result of such optimal linear fusion, we will achieve a lower variance than naïve averaging. Simulated experiments are used to validate theoretical predictions. Future work based on the proposed simulation methods may lead to general guidelines and error lower bounds for quantitative image analysis and change detection.
Covariance descriptor fusion for target detection

NASA Astrophysics Data System (ADS)

Cukur, Huseyin; Binol, Hamidullah; Bal, Abdullah; Yavuz, Fatih

2016-05-01

Target detection is one of the most important topics for military or civilian applications. In order to address such detection tasks, hyperspectral imaging sensors provide useful images data containing both spatial and spectral information. Target detection has various challenging scenarios for hyperspectral images. To overcome these challenges, covariance descriptor presents many advantages. Detection capability of the conventional covariance descriptor technique can be improved by fusion methods. In this paper, hyperspectral bands are clustered according to inter-bands correlation. Target detection is then realized by fusion of covariance descriptor results based on the band clusters. The proposed combination technique is denoted Covariance Descriptor Fusion (CDF). The efficiency of the CDF is evaluated by applying to hyperspectral imagery to detect man-made objects. The obtained results show that the CDF presents better performance than the conventional covariance descriptor.
[Time consumption and quality of an automated fusion tool for SPECT and MRI images of the brain].

PubMed

Fiedler, E; Platsch, G; Schwarz, A; Schmiedehausen, K; Tomandl, B; Huk, W; Rupprecht, Th; Rahn, N; Kuwert, T

2003-10-01

Although the fusion of images from different modalities may improve diagnostic accuracy, it is rarely used in clinical routine work due to logistic problems. Therefore we evaluated performance and time needed for fusing MRI and SPECT images using a semiautomated dedicated software. PATIENTS, MATERIAL AND METHOD: In 32 patients regional cerebral blood flow was measured using (99m)Tc ethylcystein dimer (ECD) and the three-headed SPECT camera MultiSPECT 3. MRI scans of the brain were performed using either a 0,2 T Open or a 1,5 T Sonata. Twelve of the MRI data sets were acquired using a 3D-T1w MPRAGE sequence, 20 with a 2D acquisition technique and different echo sequences. Image fusion was performed on a Syngo workstation using an entropy minimizing algorithm by an experienced user of the software. The fusion results were classified. We measured the time needed for the automated fusion procedure and in case of need that for manual realignment after automated, but insufficient fusion. The mean time of the automated fusion procedure was 123 s. It was for the 2D significantly shorter than for the 3D MRI datasets. For four of the 2D data sets and two of the 3D data sets an optimal fit was reached using the automated approach. The remaining 26 data sets required manual correction. The sum of the time required for automated fusion and that needed for manual correction averaged 320 s (50-886 s). The fusion of 3D MRI data sets lasted significantly longer than that of the 2D MRI data. The automated fusion tool delivered in 20% an optimal fit, in 80% manual correction was necessary. Nevertheless, each of the 32 SPECT data sets could be merged in less than 15 min with the corresponding MRI data, which seems acceptable for clinical routine use.
Integrating image quality in 2nu-SVM biometric match score fusion.

PubMed

Vatsa, Mayank; Singh, Richa; Noore, Afzel

2007-10-01

This paper proposes an intelligent 2nu-support vector machine based match score fusion algorithm to improve the performance of face and iris recognition by integrating the quality of images. The proposed algorithm applies redundant discrete wavelet transform to evaluate the underlying linear and non-linear features present in the image. A composite quality score is computed to determine the extent of smoothness, sharpness, noise, and other pertinent features present in each subband of the image. The match score and the corresponding quality score of an image are fused using 2nu-support vector machine to improve the verification performance. The proposed algorithm is experimentally validated using the FERET face database and the CASIA iris database. The verification performance and statistical evaluation show that the proposed algorithm outperforms existing fusion algorithms.
Pros and Cons of 3D Image Fusion in Endovascular Aortic Repair: A Systematic Review and Meta-analysis.

PubMed

Goudeketting, Seline R; Heinen, Stefan G H; Ünlü, Çağdaş; van den Heuvel, Daniel A F; de Vries, Jean-Paul P M; van Strijen, Marco J; Sailer, Anna M

2017-08-01

To systematically review and meta-analyze the added value of 3-dimensional (3D) image fusion technology in endovascular aortic repair for its potential to reduce contrast media volume, radiation dose, procedure time, and fluoroscopy time. Electronic databases were systematically searched for studies published between January 2010 and March 2016 that included a control group describing 3D fusion imaging in endovascular aortic procedures. Two independent reviewers assessed the methodological quality of the included studies and extracted data on iodinated contrast volume, radiation dose, procedure time, and fluoroscopy time. The contrast use for standard and complex endovascular aortic repairs (fenestrated, branched, and chimney) were pooled using a random-effects model; outcomes are reported as the mean difference with 95% confidence intervals (CIs). Seven studies, 5 retrospective and 2 prospective, involving 921 patients were selected for analysis. The methodological quality of the studies was moderate (median 17, range 15-18). The use of fusion imaging led to an estimated mean reduction in iodinated contrast of 40.1 mL (95% CI 16.4 to 63.7, p=0.002) for standard procedures and a mean 70.7 mL (95% CI 44.8 to 96.6, p<0.001) for complex repairs. Secondary outcome measures were not pooled because of potential bias in nonrandomized data, but radiation doses, procedure times, and fluoroscopy times were lower, although not always significantly, in the fusion group in 6 of the 7 studies. Compared with the control group, 3D fusion imaging is associated with a significant reduction in the volume of contrast employed for standard and complex endovascular aortic procedures, which can be particularly important in patients with renal failure. Radiation doses, procedure times, and fluoroscopy times were reduced when 3D fusion was used.
Novel fusion for hybrid optical/microcomputed tomography imaging based on natural light surface reconstruction and iterated closest point

NASA Astrophysics Data System (ADS)

Ning, Nannan; Tian, Jie; Liu, Xia; Deng, Kexin; Wu, Ping; Wang, Bo; Wang, Kun; Ma, Xibo

2014-02-01

In mathematics, optical molecular imaging including bioluminescence tomography (BLT), fluorescence tomography (FMT) and Cerenkov luminescence tomography (CLT) are concerned with a similar inverse source problem. They all involve the reconstruction of the 3D location of a single/multiple internal luminescent/fluorescent sources based on 3D surface flux distribution. To achieve that, an accurate fusion between 2D luminescent/fluorescent images and 3D structural images that may be acquired form micro-CT, MRI or beam scanning is extremely critical. However, the absence of a universal method that can effectively convert 2D optical information into 3D makes the accurate fusion challengeable. In this study, to improve the fusion accuracy, a new fusion method for dual-modality tomography (luminescence/fluorescence and micro-CT) based on natural light surface reconstruction (NLSR) and iterated closest point (ICP) was presented. It consisted of Octree structure, exact visual hull from marching cubes and ICP. Different from conventional limited projection methods, it is 360° free-space registration, and utilizes more luminescence/fluorescence distribution information from unlimited multi-orientation 2D optical images. A mouse mimicking phantom (one XPM-2 Phantom Light Source, XENOGEN Corporation) and an in-vivo BALB/C mouse with implanted one luminescent light source were used to evaluate the performance of the new fusion method. Compared with conventional fusion methods, the average error of preset markers was improved by 0.3 and 0.2 pixels from the new method, respectively. After running the same 3D internal light source reconstruction algorithm of the BALB/C mouse, the distance error between the actual and reconstructed internal source was decreased by 0.19 mm.
Value of C-Arm Cone Beam Computed Tomography Image Fusion in Maximizing the Versatility of Endovascular Robotics.

PubMed

Chinnadurai, Ponraj; Duran, Cassidy; Al-Jabbari, Odeaa; Abu Saleh, Walid K; Lumsden, Alan; Bismuth, Jean

2016-01-01

To report our initial experience and highlight the value of using intraoperative C-arm cone beam computed tomography (CT; DynaCT(®)) image fusion guidance along with steerable robotic endovascular catheter navigation to optimize vessel cannulation. Between May 2013 and January 2015, all patients who underwent endovascular procedures using DynaCT image fusion technique along with Hansen Magellan vascular robotic catheter were included in this study. As a part of preoperative planning, relevant vessel landmarks were electronically marked in contrast-enhanced multi-slice computed tomography images and stored. At the beginning of procedure, an intraoperative noncontrast C-arm cone beam CT (syngo DynaCT(®), Siemens Medical Solutions USA Inc.) was acquired in the hybrid suite. Preoperative images were then coregistered to intraoperative DynaCT images using aortic wall calcifications and bone landmarks. Stored landmarks were then overlaid on 2-dimensional (2D) live fluoroscopic images as virtual markers that are updated in real-time with C-arm, table movements and image zoom. Vascular access and robotic catheter (Magellan(®), Hansen Medical) was setup per standard. Vessel cannulation was performed based on electronic virtual markers on live fluoroscopy using robotic catheter. The impact of 3-dimensional (3D) image fusion guidance on robotic vessel cannulation was evaluated retrospectively, by assessing quantitative parameters like number of angiograms acquired before vessel cannulation and qualitative parameters like accuracy of vessel ostium and centerline markers. All 17 vessels were cannulated successfully in 14 patients' attempted using robotic catheter and image fusion guidance. Median vessel diameter at origin was 5.4 mm (range, 2.3-13 mm), whereas 12 of 17 (70.6%) vessels had either calcified and/or stenosed origin from parent vessel. Nine of 17 vessels (52.9 %) were cannulated without any contrast injection. Median number of angiograms required before cannulation was 0 (range, 0-2). On qualitative assessment, 14 of 15 vessels (93.3%) had grade = 1 accuracy (guidewire inside virtual ostial marker). Fourteen of 14 vessels had grade = 1 accuracy (virtual centerlines that matched with the actual vessel trajectory during cannulation). In this small series, the experience of using DynaCT image fusion guidance together with a steerable endovascular robotic catheter indicates that such image fusion strategies can enhance intraoperative 2D fluoroscopy by bringing preoperative 3D information about vascular stenosis and/or calcification, angulation, and take off from main vessel thereby facilitating ultimate vessel cannulation. Copyright © 2016 Elsevier Inc. All rights reserved.
Sensor fusion II: Human and machine strategies; Proceedings of the Meeting, Philadelphia, PA, Nov. 6-9, 1989

NASA Technical Reports Server (NTRS)

Schenker, Paul S. (Editor)

1990-01-01

Various papers on human and machine strategies in sensor fusion are presented. The general topics addressed include: active vision, measurement and analysis of visual motion, decision models for sensor fusion, implementation of sensor fusion algorithms, applying sensor fusion to image analysis, perceptual modules and their fusion, perceptual organization and object recognition, planning and the integration of high-level knowledge with perception, using prior knowledge and context in sensor fusion.
Magnetic resonance imaging-ultrasound fusion biopsy for prediction of final prostate pathology.

PubMed

Le, Jesse D; Stephenson, Samuel; Brugger, Michelle; Lu, David Y; Lieu, Patricia; Sonn, Geoffrey A; Natarajan, Shyam; Dorey, Frederick J; Huang, Jiaoti; Margolis, Daniel J A; Reiter, Robert E; Marks, Leonard S

2014-11-01

We explored the impact of magnetic resonance imaging-ultrasound fusion prostate biopsy on the prediction of final surgical pathology. A total of 54 consecutive men undergoing radical prostatectomy at UCLA after fusion biopsy were included in this prospective, institutional review board approved pilot study. Using magnetic resonance imaging-ultrasound fusion, tissue was obtained from a 12-point systematic grid (mapping biopsy) and from regions of interest detected by multiparametric magnetic resonance imaging (targeted biopsy). A single radiologist read all magnetic resonance imaging, and a single pathologist independently rereviewed all biopsy and whole mount pathology, blinded to prior interpretation and matched specimen. Gleason score concordance between biopsy and prostatectomy was the primary end point. Mean patient age was 62 years and median prostate specific antigen was 6.2 ng/ml. Final Gleason score at prostatectomy was 6 (13%), 7 (70%) and 8-9 (17%). A tertiary pattern was detected in 17 (31%) men. Of 45 high suspicion (image grade 4-5) magnetic resonance imaging targets 32 (71%) contained prostate cancer. The per core cancer detection rate was 20% by systematic mapping biopsy and 42% by targeted biopsy. The highest Gleason pattern at prostatectomy was detected by systematic mapping biopsy in 54%, targeted biopsy in 54% and a combination in 81% of cases. Overall 17% of cases were upgraded from fusion biopsy to final pathology and 1 (2%) was downgraded. The combination of targeted biopsy and systematic mapping biopsy was needed to obtain the best predictive accuracy. In this pilot study magnetic resonance imaging-ultrasound fusion biopsy allowed for the prediction of final prostate pathology with greater accuracy than that reported previously using conventional methods (81% vs 40% to 65%). If confirmed, these results will have important clinical implications. Copyright © 2014 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.
Focal Laser Ablation of Prostate Cancer: Feasibility of Magnetic Resonance Imaging-Ultrasound Fusion for Guidance.

PubMed

Natarajan, Shyam; Jones, Tonye A; Priester, Alan M; Geoghegan, Rory; Lieu, Patricia; Delfin, Merdie; Felker, Ely; Margolis, Daniel J A; Sisk, Anthony; Pantuck, Allan; Grundfest, Warren; Marks, Leonard S

2017-10-01

Focal laser ablation is a potential treatment in some men with prostate cancer. Currently focal laser ablation is performed by radiologists in a magnetic resonance imaging unit (in bore). We evaluated the safety and feasibility of performing focal laser ablation in a urology clinic (out of bore) using magnetic resonance imaging-ultrasound fusion for guidance. A total of 11 men with intermediate risk prostate cancer were enrolled in this prospective, institutional review board approved pilot study. Magnetic resonance imaging-ultrasound fusion was used to guide laser fibers transrectally into regions of interest harboring intermediate risk prostate cancer. Thermal probes were inserted for real-time monitoring of intraprostatic temperatures during laser activation. Multiparametric magnetic resonance imaging (3 Tesla) was done immediately after treatment and at 6 months along with comprehensive fusion biopsy. Ten of 11 patients were successfully treated while under local anesthesia. Mean procedure time was 95 minutes (range 71 to 105). Posttreatment magnetic resonance imaging revealed a confined zone of nonperfusion in all 10 men. Mean zone volume was 4.3 cc (range 2.1 to 6.0). No CTCAE grade 3 or greater adverse events developed and no changes were observed in urinary or sexual function. At 6 months magnetic resonance imaging-ultrasound fusion biopsy of the treatment site showed no cancer in 3 patients, microfocal Gleason 3 + 3 in another 3 and persistent intermediate risk prostate cancer in 4. Focal laser ablation of prostate cancer appears safe and feasible with the patient under local anesthesia in a urology clinic using magnetic resonance imaging-ultrasound fusion for guidance and thermal probes for monitoring. Further development is necessary to refine out of bore focal laser ablation and additional studies are needed to determine appropriate treatment margins and oncologic efficacy. Copyright © 2017 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.
Ashamed and Fused with Body Image and Eating: Binge Eating as an Avoidance Strategy.

PubMed

Duarte, Cristiana; Pinto-Gouveia, José; Ferreira, Cláudia

2017-01-01

Binge Eating Disorder (BED) is currently recognized as a severe disorder associated with relevant psychiatric and physical comorbidity, and marked emotional distress. Shame is a specific negative emotion that has been highlighted as central in eating disorders. However, the effect of shame and underlying mechanisms on binge eating symptomatology severity remained unclear. This study examines the role of shame, depressive symptoms, weight and shape concerns and eating concerns, and body image-related cognitive fusion, on binge eating symptomatology severity. Participated in this study 73 patients with the diagnosis of BED, established through a clinical interview-Eating Disorder Examination 17.0D-who completed measures of external shame, body-image related cognitive fusion, depressive symptoms and binge eating symptomatology. Results revealed positive associations between binge eating severity and depressive symptoms, shame, weight and shape concerns, eating concerns and body image-related cognitive fusion. A path analysis showed that, when controlling for the effect of depressive symptoms, external shame has a direct effect on binge eating severity, and an indirect effect mediated by increased eating concern and higher levels of body image-related cognitive fusion. Results confirmed the plausibility of the model, which explained 43% of the severity of binge eating symptoms. The proposed model suggests that, in BED patients, perceiving that others see the self negatively may be associated with an entanglement with body image-related thoughts and concerns about eating, which may, in turn, fuel binge eating symptoms. Findings have important clinical implications supporting the relevance of addressing shame and associated processes in binge eating. Copyright © 2015 John Wiley & Sons, Ltd. Shame is a significant predictor of symptomatology severity of BED patients. Shame significantly impacts binge eating, even controlling for depressive symptoms. Shame significantly predicts body image-related cognitive fusion and eating concern. Body image-fusion and eating concern mediate the link between shame and binge eating. Binge eating may be seen as an avoidance strategy from negative self-evaluations. Copyright © 2015 John Wiley & Sons, Ltd.
18F-FDG PET/MRI fusion in characterizing pancreatic tumors: comparison to PET/CT.

PubMed

Tatsumi, Mitsuaki; Isohashi, Kayako; Onishi, Hiromitsu; Hori, Masatoshi; Kim, Tonsok; Higuchi, Ichiro; Inoue, Atsuo; Shimosegawa, Eku; Takeda, Yutaka; Hatazawa, Jun

2011-08-01

To demonstrate that positron emission tomography (PET)/magnetic resonance imaging (MRI) fusion was feasible in characterizing pancreatic tumors (PTs), comparing MRI and computed tomography (CT) as mapping images for fusion with PET as well as fused PET/MRI and PET/CT. We retrospectively reviewed 47 sets of (18)F-fluorodeoxyglucose ((18)F -FDG) PET/CT and MRI examinations to evaluate suspected or known pancreatic cancer. To assess the ability of mapping images for fusion with PET, CT (of PET/CT), T1- and T2-weighted (w) MR images (all non-contrast) were graded regarding the visibility of PT (5-point confidence scale). Fused PET/CT, PET/T1-w or T2-w MR images of the upper abdomen were evaluated to determine whether mapping images provided additional diagnostic information to PET alone (3-point scale). The overall quality of PET/CT or PET/MRI sets in diagnosis was also assessed (3-point scale). These PET/MRI-related scores were compared to PET/CT-related scores and the accuracy in characterizing PTs was compared. Forty-three PTs were visualized on CT or MRI, including 30 with abnormal FDG uptake and 13 without. The confidence score for the visibility of PT was significantly higher on T1-w MRI than CT. The scores for additional diagnostic information to PET and overall quality of each image set in diagnosis were significantly higher on the PET/T1-w MRI set than the PET/CT set. The diagnostic accuracy was higher on PET/T1-w or PET/T2-w MRI (93.0 and 90.7%, respectively) than PET/CT (88.4%), but statistical significance was not obtained. PET/MRI fusion, especially PET with T1-w MRI, was demonstrated to be superior to PET/CT in characterizing PTs, offering better mapping and fusion image quality.
Fusion of Modis and Palsar Principal Component Images Through Curvelet Transform for Land Cover Classification

NASA Astrophysics Data System (ADS)

Singh, Dharmendra; Kumar, Harish

Earth observation satellites provide data that covers different portions of the electromagnetic spectrum at different spatial and spectral resolutions. The increasing availability of information products generated from satellite images are extending the ability to understand the patterns and dynamics of the earth resource systems at all scales of inquiry. In which one of the most important application is the generation of land cover classification from satellite images for understanding the actual status of various land cover classes. The prospect for the use of satel-lite images in land cover classification is an extremely promising one. The quality of satellite images available for land-use mapping is improving rapidly by development of advanced sensor technology. Particularly noteworthy in this regard is the improved spatial and spectral reso-lution of the images captured by new satellite sensors like MODIS, ASTER, Landsat 7, and SPOT 5. For the full exploitation of increasingly sophisticated multisource data, fusion tech-niques are being developed. Fused images may enhance the interpretation capabilities. The images used for fusion have different temporal, and spatial resolution. Therefore, the fused image provides a more complete view of the observed objects. It is one of the main aim of image fusion to integrate different data in order to obtain more information that can be de-rived from each of the single sensor data alone. A good example of this is the fusion of images acquired by different sensors having a different spatial resolution and of different spectral res-olution. Researchers are applying the fusion technique since from three decades and propose various useful methods and techniques. The importance of high-quality synthesis of spectral information is well suited and implemented for land cover classification. More recently, an underlying multiresolution analysis employing the discrete wavelet transform has been used in image fusion. It was found that multisensor image fusion is a tradeoff between the spectral information from a low resolution multi-spectral images and the spatial information from a high resolution multi-spectral images. With the wavelet transform based fusion method, it is easy to control this tradeoff. A new transform, the curvelet transform was used in recent years by Starck. A ridgelet transform is applied to square blocks of detail frames of undecimated wavelet decomposition, consequently the curvelet transform is obtained. Since the ridgelet transform possesses basis functions matching directional straight lines therefore, the curvelet transform is capable of representing piecewise linear contours on multiple scales through few significant coefficients. This property leads to a better separation between geometric details and background noise, which may be easily reduced by thresholding curvelet coefficients before they are used for fusion. The Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) instrument provides high radiometric sensitivity (12 bit) in 36 spectral bands ranging in wavelength from 0.4 m to 14.4 m and also it is freely available. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km. In this paper, the band 1 of spatial resolution 250 m and bandwidth 620-670 nm, and band 2, of spatial resolution of 250m and bandwidth 842-876 nm is considered as these bands has special features to identify the agriculture and other land covers. In January 2006, the Advanced Land Observing Satellite (ALOS) was successfully launched by the Japan Aerospace Exploration Agency (JAXA). The Phased Arraytype L-band SAR (PALSAR) sensor onboard the satellite acquires SAR imagery at a wavelength of 23.5 cm (frequency 1.27 GHz) with capabilities of multimode and multipolarization observation. PALSAR can operate in several modes: the fine-beam single (FBS) polarization mode (HH), fine-beam dual (FBD) polariza-tion mode (HH/HV or VV/VH), polarimetric (PLR) mode (HH/HV/VH/VV), and ScanSAR (WB) mode (HH/VV) [15]. These makes PALSAR imagery very attractive for spatially and temporally consistent monitoring system. The Overview of Principal Component Analysis is that the most of the information within all the bands can be compressed into a much smaller number of bands with little loss of information. It allows us to extract the low-dimensional subspaces that capture the main linear correlation among the high-dimensional image data. This facilitates viewing the explained variance or signal in the available imagery, allowing both gross and more subtle features in the imagery to be seen. In this paper we have explored the fusion technique for enhancing the land cover classification of low resolution satellite data espe-cially freely available satellite data. For this purpose, we have considered to fuse the PALSAR principal component data with MODIS principal component data. Initially, the MODIS band 1 and band 2 is considered, its principal component is computed. Similarly the PALSAR HH, HV and VV polarized data are considered, and there principal component is also computed. con-sequently, the PALSAR principal component image is fused with MODIS principal component image. The aim of this paper is to analyze the effect of classification accuracy on major type of land cover types like agriculture, water and urban bodies with fusion of PALSAR data to MODIS data. Curvelet transformation has been applied for fusion of these two satellite images and Minimum Distance classification technique has been applied for the resultant fused image. It is qualitatively and visually observed that the overall classification accuracy of MODIS image after fusion is enhanced. This type of fusion technique may be quite helpful in near future to use freely available satellite data to develop monitoring system for different land cover classes on the earth.
Gender recognition from unconstrained and articulated human body.

PubMed

Wu, Qin; Guo, Guodong

2014-01-01

Gender recognition has many useful applications, ranging from business intelligence to image search and social activity analysis. Traditional research on gender recognition focuses on face images in a constrained environment. This paper proposes a method for gender recognition in articulated human body images acquired from an unconstrained environment in the real world. A systematic study of some critical issues in body-based gender recognition, such as which body parts are informative, how many body parts are needed to combine together, and what representations are good for articulated body-based gender recognition, is also presented. This paper also pursues data fusion schemes and efficient feature dimensionality reduction based on the partial least squares estimation. Extensive experiments are performed on two unconstrained databases which have not been explored before for gender recognition.
Gender Recognition from Unconstrained and Articulated Human Body

PubMed Central

Wu, Qin; Guo, Guodong

2014-01-01

Gender recognition has many useful applications, ranging from business intelligence to image search and social activity analysis. Traditional research on gender recognition focuses on face images in a constrained environment. This paper proposes a method for gender recognition in articulated human body images acquired from an unconstrained environment in the real world. A systematic study of some critical issues in body-based gender recognition, such as which body parts are informative, how many body parts are needed to combine together, and what representations are good for articulated body-based gender recognition, is also presented. This paper also pursues data fusion schemes and efficient feature dimensionality reduction based on the partial least squares estimation. Extensive experiments are performed on two unconstrained databases which have not been explored before for gender recognition. PMID:24977203

Evaluation of Night Vision Devices for Image Fusion Studies

DTIC Science & Technology

2004-12-01

July 2004. http://www.sensorsmag.com/articles/0400/34/main.shtml Task, Harry L., Hartman, Richard T., Marasco , Peter L., Methods for Measuring...Press, Bellingham, Washington, 1998. Burt, Peter J. & Kolczynski, Raymond J., David Sarnoff Research Center, Enhanced Image Capture through Fusion
Non-contrast magnetic resonance imaging for bladder cancer: fused high b value diffusion-weighted imaging and T2-weighted imaging helps evaluate depth of invasion.

PubMed

Lee, Minsu; Shin, Su-Jin; Oh, Young Taik; Jung, Dae Chul; Cho, Nam Hoon; Choi, Young Deuk; Park, Sung Yoon

2017-09-01

To investigate the utility of fused high b value diffusion-weighted imaging (DWI) and T2-weighted imaging (T2WI) for evaluating depth of invasion in bladder cancer. We included 62 patients with magnetic resonance imaging (MRI) and surgically confirmed urothelial carcinoma in the urinary bladder. An experienced genitourinary radiologist analysed the depth of invasion (T stage <2 or ≥2) using T2WI, DWI, T2WI plus DWI, and fused DWI and T2WI (fusion MRI). Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy were investigated. Area under the curve (AUC) was analysed to identify T stage ≥2. The rate of patients with surgically confirmed T stage ≥2 was 41.9% (26/62). Sensitivity, specificity, PPV, NPV and accuracy were 50.0%, 55.6%, 44.8%, 60.6% and 53.2%, respectively, with T2WI; 57.7%, 77.8%, 65.2%, 71.8% and 69.4%, respectively, with DWI; 65.4%, 80.6%, 70.8%, 76.3% and 74.2%, respectively, with T2WI plus DWI and 80.8%, 77.8%, 72.4%, 84.9% and 79.0%, respectively, with fusion MRI. AUC was 0.528 with T2WI, 0.677 with DWI, 0.730 with T2WI plus DWI and 0.793 with fusion MRI for T stage ≥2. Fused high b value DWI and T2WI may be a promising non-contrast MRI technique for assessing depth of invasion in bladder cancer. • Accuracy of fusion MRI was 79.0% for T stage ≥2 in bladder cancer. • AUC of fusion MRI was 0.793 for T stage ≥2 in bladder cancer. • Diagnostic performance of fusion MRI was comparable with T2WI plus DWI. • As a non-contrast MRI technique, fusion MRI is useful for bladder cancer.
Electron cyclotron emission imaging and applications in magnetic fusion energy

NASA Astrophysics Data System (ADS)

Tobias, Benjamin John

Energy production through the burning of fossil fuels is an unsustainable practice. Exponentially increasing energy consumption and dwindling natural resources ensure that coal and gas fueled power plants will someday be a thing of the past. However, even before fuel reserves are depleted, our planet may well succumb to disastrous side effects, namely the build up of carbon emissions in the environment triggering world-wide climate change and the countless industrial spills of pollutants that continue to this day. Many alternatives are currently being developed, but none has so much promise as fusion nuclear energy, the energy of the sun. The confinement of hot plasma at temperatures in excess of 100 million Kelvin by a carefully arranged magnetic field for the realization of a self-sustaining fusion power plant requires new technologies and improved understanding of fundamental physical phenomena. Imaging of electron cyclotron radiation lends insight into the spatial and temporal behavior of electron temperature fluctuations and instabilities, providing a powerful diagnostic for investigations into basic plasma physics and nuclear fusion reactor operation. This dissertation presents the design and implementation of a new generation of Electron Cyclotron Emission Imaging (ECEI) diagnostics on toroidal magnetic fusion confinement devices, or tokamaks, around the world. The underlying physics of cyclotron radiation in fusion plasmas is reviewed, and a thorough discussion of millimeter wave imaging techniques and heterodyne radiometry in ECEI follows. The imaging of turbulence and fluid flows has evolved over half a millennium since Leonardo da Vinci's first sketches of cascading water, and applications for ECEI in fusion research are broad ranging. Two areas of physical investigation are discussed in this dissertation: the identification of poloidal shearing in Alfven eigenmode structures predicted by hybrid gyrofluid-magnetohydrodynamic (gyrofluid-MHD) modeling, and magnetic field line displacement during precursor oscillations associated with the sawtooth crash, a disruptive instability observed both in tokamak plasmas with high core current and in the magnetized plasmas of solar flares and other interstellar plasmas. Understanding both of these phenomena is essential for the future of magnetic fusion energy, and important new observations described herein underscore the advantages of imaging techniques in experimental physics.
Parametric PET/MR Fusion Imaging to Differentiate Aggressive from Indolent Primary Prostate Cancer with Application for Image-Guided Prostate Cancer Biopsies

DTIC Science & Technology

2014-10-01

Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT The study investigates whether fusion PET/MRI imaging with 18F- choline PET/CT and...imaging with 18F- choline PET/CT and diffusion-weighted MRI can be successfully applied to target prostate cancer using image-guided prostate...Completed task. The 18F- choline synthesis was implemented and optimized for routine radiotracer production. RDRC committee approval as part of the IRB
Measurement of spatial refractive index distributions of fusion spliced optical fibers by digital holographic microtomography

NASA Astrophysics Data System (ADS)

Pan, Feng; Deng, Yating; Ma, Xichao; Xiao, Wen

2017-11-01

Digital holographic microtomography is improved and applied to the measurements of three-dimensional refractive index distributions of fusion spliced optical fibers. Tomographic images are reconstructed from full-angle phase projection images obtained with a setup-rotation approach, in which the laser source, the optical system and the image sensor are arranged on an optical breadboard and synchronously rotated around the fixed object. For retrieving high-quality tomographic images, a numerical method is proposed to compensate the unwanted movements of the object in the lateral, axial and vertical directions during rotation. The compensation is implemented on the two-dimensional phase images instead of the sinogram. The experimental results exhibit distinctly the internal structures of fusion splices between a single-mode fiber and other fibers, including a multi-mode fiber, a panda polarization maintaining fiber, a bow-tie polarization maintaining fiber and a photonic crystal fiber. In particular, the internal structure distortion in the fusion areas can be intuitively observed, such as the expansion of the stress zones of polarization maintaining fibers, the collapse of the air holes of photonic crystal fibers, etc.
Towards Omni-Tomography—Grand Fusion of Multiple Modalities for Simultaneous Interior Tomography

PubMed Central

Wang, Ge; Zhang, Jie; Gao, Hao; Weir, Victor; Yu, Hengyong; Cong, Wenxiang; Xu, Xiaochen; Shen, Haiou; Bennett, James; Furth, Mark; Wang, Yue; Vannier, Michael

2012-01-01

We recently elevated interior tomography from its origin in computed tomography (CT) to a general tomographic principle, and proved its validity for other tomographic modalities including SPECT, MRI, and others. Here we propose “omni-tomography”, a novel concept for the grand fusion of multiple tomographic modalities for simultaneous data acquisition in a region of interest (ROI). Omni-tomography can be instrumental when physiological processes under investigation are multi-dimensional, multi-scale, multi-temporal and multi-parametric. Both preclinical and clinical studies now depend on in vivo tomography, often requiring separate evaluations by different imaging modalities. Over the past decade, two approaches have been used for multimodality fusion: Software based image registration and hybrid scanners such as PET-CT, PET-MRI, and SPECT-CT among others. While there are intrinsic limitations with both approaches, the main obstacle to the seamless fusion of multiple imaging modalities has been the bulkiness of each individual imager and the conflict of their physical (especially spatial) requirements. To address this challenge, omni-tomography is now unveiled as an emerging direction for biomedical imaging and systems biomedicine. PMID:22768108
Research on multi-source image fusion technology in haze environment

NASA Astrophysics Data System (ADS)

Ma, GuoDong; Piao, Yan; Li, Bing

2017-11-01

In the haze environment, the visible image collected by a single sensor can express the details of the shape, color and texture of the target very well, but because of the haze, the sharpness is low and some of the target subjects are lost; Because of the expression of thermal radiation and strong penetration ability, infrared image collected by a single sensor can clearly express the target subject, but it will lose detail information. Therefore, the multi-source image fusion method is proposed to exploit their respective advantages. Firstly, the improved Dark Channel Prior algorithm is used to preprocess the visible haze image. Secondly, the improved SURF algorithm is used to register the infrared image and the haze-free visible image. Finally, the weighted fusion algorithm based on information complementary is used to fuse the image. Experiments show that the proposed method can improve the clarity of the visible target and highlight the occluded infrared target for target recognition.
A research on radiation calibration of high dynamic range based on the dual channel CMOS

NASA Astrophysics Data System (ADS)

Ma, Kai; Shi, Zhan; Pan, Xiaodong; Wang, Yongsheng; Wang, Jianghua

2017-10-01

The dual channel complementary metal-oxide semiconductor (CMOS) can get high dynamic range (HDR) image through extending the gray level of the image by using image fusion with high gain channel image and low gain channel image in a same frame. In the process of image fusion with dual channel, it adopts the coefficients of radiation response of a pixel from dual channel in a same frame, and then calculates the gray level of the pixel in the HDR image. For the coefficients of radiation response play a crucial role in image fusion, it has to find an effective method to acquire these parameters. In this article, it makes a research on radiation calibration of high dynamic range based on the dual channel CMOS, and designs an experiment to calibrate the coefficients of radiation response for the sensor it used. In the end, it applies these response parameters in the dual channel CMOS which calibrates, and verifies the correctness and feasibility of the method mentioned in this paper.
Target detection method by airborne and spaceborne images fusion based on past images

NASA Astrophysics Data System (ADS)

Chen, Shanjing; Kang, Qing; Wang, Zhenggang; Shen, ZhiQiang; Pu, Huan; Han, Hao; Gu, Zhongzheng

2017-11-01

To solve the problem that remote sensing target detection method has low utilization rate of past remote sensing data on target area, and can not recognize camouflage target accurately, a target detection method by airborne and spaceborne images fusion based on past images is proposed in this paper. The target area's past of space remote sensing image is taken as background. The airborne and spaceborne remote sensing data is fused and target feature is extracted by the means of airborne and spaceborne images registration, target change feature extraction, background noise suppression and artificial target feature extraction based on real-time aerial optical remote sensing image. Finally, the support vector machine is used to detect and recognize the target on feature fusion data. The experimental results have established that the proposed method combines the target area change feature of airborne and spaceborne remote sensing images with target detection algorithm, and obtains fine detection and recognition effect on camouflage and non-camouflage targets.
Multimodal Medical Image Fusion by Adaptive Manifold Filter.

PubMed

Geng, Peng; Liu, Shuaiqi; Zhuang, Shanna

2015-01-01

Medical image fusion plays an important role in diagnosis and treatment of diseases such as image-guided radiotherapy and surgery. The modified local contrast information is proposed to fuse multimodal medical images. Firstly, the adaptive manifold filter is introduced into filtering source images as the low-frequency part in the modified local contrast. Secondly, the modified spatial frequency of the source images is adopted as the high-frequency part in the modified local contrast. Finally, the pixel with larger modified local contrast is selected into the fused image. The presented scheme outperforms the guided filter method in spatial domain, the dual-tree complex wavelet transform-based method, nonsubsampled contourlet transform-based method, and four classic fusion methods in terms of visual quality. Furthermore, the mutual information values by the presented method are averagely 55%, 41%, and 62% higher than the three methods and those values of edge based similarity measure by the presented method are averagely 13%, 33%, and 14% higher than the three methods for the six pairs of source images.
Wavelet-Based Visible and Infrared Image Fusion: A Comparative Study

PubMed Central

Sappa, Angel D.; Carvajal, Juan A.; Aguilera, Cristhian A.; Oliveira, Miguel; Romero, Dennis; Vintimilla, Boris X.

2016-01-01

This paper evaluates different wavelet-based cross-spectral image fusion strategies adopted to merge visible and infrared images. The objective is to find the best setup independently of the evaluation metric used to measure the performance. Quantitative performance results are obtained with state of the art approaches together with adaptations proposed in the current work. The options evaluated in the current work result from the combination of different setups in the wavelet image decomposition stage together with different fusion strategies for the final merging stage that generates the resulting representation. Most of the approaches evaluate results according to the application for which they are intended for. Sometimes a human observer is selected to judge the quality of the obtained results. In the current work, quantitative values are considered in order to find correlations between setups and performance of obtained results; these correlations can be used to define a criteria for selecting the best fusion strategy for a given pair of cross-spectral images. The whole procedure is evaluated with a large set of correctly registered visible and infrared image pairs, including both Near InfraRed (NIR) and Long Wave InfraRed (LWIR). PMID:27294938
Wavelet-Based Visible and Infrared Image Fusion: A Comparative Study.

PubMed

Sappa, Angel D; Carvajal, Juan A; Aguilera, Cristhian A; Oliveira, Miguel; Romero, Dennis; Vintimilla, Boris X

2016-06-10

This paper evaluates different wavelet-based cross-spectral image fusion strategies adopted to merge visible and infrared images. The objective is to find the best setup independently of the evaluation metric used to measure the performance. Quantitative performance results are obtained with state of the art approaches together with adaptations proposed in the current work. The options evaluated in the current work result from the combination of different setups in the wavelet image decomposition stage together with different fusion strategies for the final merging stage that generates the resulting representation. Most of the approaches evaluate results according to the application for which they are intended for. Sometimes a human observer is selected to judge the quality of the obtained results. In the current work, quantitative values are considered in order to find correlations between setups and performance of obtained results; these correlations can be used to define a criteria for selecting the best fusion strategy for a given pair of cross-spectral images. The whole procedure is evaluated with a large set of correctly registered visible and infrared image pairs, including both Near InfraRed (NIR) and Long Wave InfraRed (LWIR).
Single-Scale Fusion: An Effective Approach to Merging Images.

PubMed

Ancuti, Codruta O; Ancuti, Cosmin; De Vleeschouwer, Christophe; Bovik, Alan C

2017-01-01

Due to its robustness and effectiveness, multi-scale fusion (MSF) based on the Laplacian pyramid decomposition has emerged as a popular technique that has shown utility in many applications. Guided by several intuitive measures (weight maps) the MSF process is versatile and straightforward to be implemented. However, the number of pyramid levels increases with the image size, which implies sophisticated data management and memory accesses, as well as additional computations. Here, we introduce a simplified formulation that reduces MSF to only a single level process. Starting from the MSF decomposition, we explain both mathematically and intuitively (visually) a way to simplify the classical MSF approach with minimal loss of information. The resulting single-scale fusion (SSF) solution is a close approximation of the MSF process that eliminates important redundant computations. It also provides insights regarding why MSF is so effective. While our simplified expression is derived in the context of high dynamic range imaging, we show its generality on several well-known fusion-based applications, such as image compositing, extended depth of field, medical imaging, and blending thermal (infrared) images with visible light. Besides visual validation, quantitative evaluations demonstrate that our SSF strategy is able to yield results that are highly competitive with traditional MSF approaches.
Change Detection of High-Resolution Remote Sensing Images Based on Adaptive Fusion of Multiple Features

NASA Astrophysics Data System (ADS)

Wang, G. H.; Wang, H. B.; Fan, W. F.; Liu, Y.; Chen, C.

2018-04-01

In view of the traditional change detection algorithm mainly depends on the spectral information image spot, failed to effectively mining and fusion of multi-image feature detection advantage, the article borrows the ideas of object oriented analysis proposed a multi feature fusion of remote sensing image change detection algorithm. First by the multi-scale segmentation of image objects based; then calculate the various objects of color histogram and linear gradient histogram; utilizes the color distance and edge line feature distance between EMD statistical operator in different periods of the object, using the adaptive weighted method, the color feature distance and edge in a straight line distance of combination is constructed object heterogeneity. Finally, the curvature histogram analysis image spot change detection results. The experimental results show that the method can fully fuse the color and edge line features, thus improving the accuracy of the change detection.
Chemical heterogeneity as a result of hydroxylamine cleavage of a fusion protein of human insulin-like growth factor I.

PubMed Central

Canova-Davis, E; Eng, M; Mukku, V; Reifsnyder, D H; Olson, C V; Ling, V T

1992-01-01

Recombinant DNA techniques were used to biosynthesize human insulin-like growth factor I (hIGF-I) as a fusion protein wherein the fusion polypeptide is an IgG-binding moiety derived from staphylococcal protein A. This fusion protein is produced in Escherichia coli and secreted into the fermentation broth. In order to release mature recombinant-derived hIGF-I (rhIGF-I), the fusion protein is treated with hydroxylamine, which cleaves a susceptible Asn-Gly bond that has been engineered into the fusion protein gene. Reversed-phase h.p.l.c. was used to estimate the purity of the rhIGF-I preparations, especially for the quantification of the methionine sulphoxide-containing variant. It was determined that hydroxylamine cleavage of the fusion protein produced, as a side reaction, hydroxamates of the asparagine and glutamine residues in rhIGF-I. Although isoelectric focusing was effective in detecting, and reversed-phase h.p.l.c. for producing enriched fractions of the hydroxamate variants, ion-exchange chromatography was a more definitive procedure, as it allowed quantification and facile removal of these variants. The identity of the variants as hydroxamates was established by Staphylococcus aureus V8 proteinase digestion, followed by m.s., as the modification was transparent to amino acid and N-terminal sequence analyses. The biological activity of rhIGF-I was established by its ability to incorporate [3H]thymidine into the DNA of BALB/c373 cells and by a radioreceptor assay utilizing human placental membranes. Both assays demonstrate that the native, recombinant and methionine sulphoxide and hydroxamate IGF-I variants are essentially equipotent. Images Fig. 2. PMID:1637301
Spatial Aspects of Multi-Sensor Data Fusion: Aerosol Optical Thickness

NASA Technical Reports Server (NTRS)

Leptoukh, Gregory; Zubko, V.; Gopalan, A.

2007-01-01

The Goddard Earth Sciences Data and Information Services Center (GES DISC) investigated the applicability and limitations of combining multi-sensor data through data fusion, to increase the usefulness of the multitude of NASA remote sensing data sets, and as part of a larger effort to integrate this capability in the GES-DISC Interactive Online Visualization and Analysis Infrastructure (Giovanni). This initial study focused on merging daily mean Aerosol Optical Thickness (AOT), as measured by the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites, to increase spatial coverage and produce complete fields to facilitate comparison with models and station data. The fusion algorithm used the maximum likelihood technique to merge the pixel values where available. The algorithm was applied to two regional AOT subsets (with mostly regular and irregular gaps, respectively) and a set of AOT fields that differed only in the size and location of artificially created gaps. The Cumulative Semivariogram (CSV) was found to be sensitive to the spatial distribution of gap areas and, thus, useful for assessing the sensitivity of the fused data to spatial gaps.
A genetically encoded fluorescent tRNA is active in live-cell protein synthesis

PubMed Central

Masuda, Isao; Igarashi, Takao; Sakaguchi, Reiko; Nitharwal, Ram G.; Takase, Ryuichi; Han, Kyu Young; Leslie, Benjamin J.; Liu, Cuiping; Gamper, Howard; Ha, Taekjip; Sanyal, Suparna

2017-01-01

Abstract Transfer RNAs (tRNAs) perform essential tasks for all living cells. They are major components of the ribosomal machinery for protein synthesis and they also serve in non-ribosomal pathways for regulation and signaling metabolism. We describe the development of a genetically encoded fluorescent tRNA fusion with the potential for imaging in live Escherichia coli cells. This tRNA fusion carries a Spinach aptamer that becomes fluorescent upon binding of a cell-permeable and non-toxic fluorophore. We show that, despite having a structural framework significantly larger than any natural tRNA species, this fusion is a viable probe for monitoring tRNA stability in a cellular quality control mechanism that degrades structurally damaged tRNA. Importantly, this fusion is active in E. coli live-cell protein synthesis allowing peptidyl transfer at a rate sufficient to support cell growth, indicating that it is accommodated by translating ribosomes. Imaging analysis shows that this fusion and ribosomes are both excluded from the nucleoid, indicating that the fusion and ribosomes are in the cytosol together possibly engaged in protein synthesis. This fusion methodology has the potential for developing new tools for live-cell imaging of tRNA with the unique advantage of both stoichiometric labeling and broader application to all cells amenable to genetic engineering. PMID:27956502
Fusion of imaging and nonimaging data for surveillance aircraft

NASA Astrophysics Data System (ADS)

Shahbazian, Elisa; Gagnon, Langis; Duquet, Jean Remi; Macieszczak, Maciej; Valin, Pierre

1997-06-01

This paper describes a phased incremental integration approach for application of image analysis and data fusion technologies to provide automated intelligent target tracking and identification for airborne surveillance on board an Aurora Maritime Patrol Aircraft. The sensor suite of the Aurora consists of a radar, an identification friend or foe (IFF) system, an electronic support measures (ESM) system, a spotlight synthetic aperture radar (SSAR), a forward looking infra-red (FLIR) sensor and a link-11 tactical datalink system. Lockheed Martin Canada (LMCan) is developing a testbed, which will be used to analyze and evaluate approaches for combining the data provided by the existing sensors, which were initially not designed to feed a fusion system. Three concurrent research proof-of-concept activities provide techniques, algorithms and methodology into three sequential phases of integration of this testbed. These activities are: (1) analysis of the fusion architecture (track/contact/hybrid) most appropriate for the type of data available, (2) extraction and fusion of simple features from the imaging data into the fusion system performing automatic target identification, and (3) development of a unique software architecture which will permit integration and independent evolution, enhancement and optimization of various decision aid capabilities, such as multi-sensor data fusion (MSDF), situation and threat assessment (STA) and resource management (RM).
Simulated disparity and peripheral blur interact during binocular fusion.

PubMed

Maiello, Guido; Chessa, Manuela; Solari, Fabio; Bex, Peter J

2014-07-17

We have developed a low-cost, practical gaze-contingent display in which natural images are presented to the observer with dioptric blur and stereoscopic disparity that are dependent on the three-dimensional structure of natural scenes. Our system simulates a distribution of retinal blur and depth similar to that experienced in real-world viewing conditions by emmetropic observers. We implemented the system using light-field photographs taken with a plenoptic camera which supports digital refocusing anywhere in the images. We coupled this capability with an eye-tracking system and stereoscopic rendering. With this display, we examine how the time course of binocular fusion depends on depth cues from blur and stereoscopic disparity in naturalistic images. Our results show that disparity and peripheral blur interact to modify eye-movement behavior and facilitate binocular fusion, and the greatest benefit was gained by observers who struggled most to achieve fusion. Even though plenoptic images do not replicate an individual’s aberrations, the results demonstrate that a naturalistic distribution of depth-dependent blur may improve 3-D virtual reality, and that interruptions of this pattern (e.g., with intraocular lenses) which flatten the distribution of retinal blur may adversely affect binocular fusion. © 2014 ARVO.
Simulated disparity and peripheral blur interact during binocular fusion

PubMed Central

Maiello, Guido; Chessa, Manuela; Solari, Fabio; Bex, Peter J

2014-01-01

We have developed a low-cost, practical gaze-contingent display in which natural images are presented to the observer with dioptric blur and stereoscopic disparity that are dependent on the three-dimensional structure of natural scenes. Our system simulates a distribution of retinal blur and depth similar to that experienced in real-world viewing conditions by emmetropic observers. We implemented the system using light-field photographs taken with a plenoptic camera which supports digital refocusing anywhere in the images. We coupled this capability with an eye-tracking system and stereoscopic rendering. With this display, we examine how the time course of binocular fusion depends on depth cues from blur and stereoscopic disparity in naturalistic images. Our results show that disparity and peripheral blur interact to modify eye-movement behavior and facilitate binocular fusion, and the greatest benefit was gained by observers who struggled most to achieve fusion. Even though plenoptic images do not replicate an individual's aberrations, the results demonstrate that a naturalistic distribution of depth-dependent blur may improve 3-D virtual reality, and that interruptions of this pattern (e.g., with intraocular lenses) which flatten the distribution of retinal blur may adversely affect binocular fusion. PMID:25034260

Gabor fusion master slave optical coherence tomography

PubMed Central

Cernat, Ramona; Bradu, Adrian; Israelsen, Niels Møller; Bang, Ole; Rivet, Sylvain; Keane, Pearse A.; Heath, David-Garway; Rajendram, Ranjan; Podoleanu, Adrian

2017-01-01

This paper describes the application of the Gabor filtering protocol to a Master/Slave (MS) swept source optical coherence tomography (SS)-OCT system at 1300 nm. The MS-OCT system delivers information from selected depths, a property that allows operation similar to that of a time domain OCT system, where dynamic focusing is possible. The Gabor filtering processing following collection of multiple data from different focus positions is different from that utilized by a conventional swept source OCT system using a Fast Fourier transform (FFT) to produce an A-scan. Instead of selecting the bright parts of A-scans for each focus position, to be placed in a final B-scan image (or in a final volume), and discarding the rest, the MS principle can be employed to advantageously deliver signal from the depths within each focus range only. The MS procedure is illustrated on creating volumes of data of constant transversal resolution from a cucumber and from an insect by repeating data acquisition for 4 different focus positions. In addition, advantage is taken from the tolerance to dispersion of the MS principle that allows automatic compensation for dispersion created by layers above the object of interest. By combining the two techniques, Gabor filtering and Master/Slave, a powerful imaging instrument is demonstrated. The master/slave technique allows simultaneous display of three categories of images in one frame: multiple depth en-face OCT images, two cross-sectional OCT images and a confocal like image obtained by averaging the en-face ones. We also demonstrate the superiority of MS-OCT over its FFT based counterpart when used with a Gabor filtering OCT instrument in terms of the speed of assembling the fused volume. For our case, we show that when more than 4 focus positions are required to produce the final volume, MS is faster than the conventional FFT based procedure. PMID:28270987
Fusion of MultiSpectral and Panchromatic Images Based on Morphological Operators.

PubMed

Restaino, Rocco; Vivone, Gemine; Dalla Mura, Mauro; Chanussot, Jocelyn

2016-04-20

Nonlinear decomposition schemes constitute an alternative to classical approaches for facing the problem of data fusion. In this paper we discuss the application of this methodology to a popular remote sensing application called pansharpening, which consists in the fusion of a low resolution multispectral image and a high resolution panchromatic image. We design a complete pansharpening scheme based on the use of morphological half gradients operators and demonstrate the suitability of this algorithm through the comparison with state of the art approaches. Four datasets acquired by the Pleiades, Worldview-2, Ikonos and Geoeye-1 satellites are employed for the performance assessment, testifying the effectiveness of the proposed approach in producing top-class images with a setting independent of the specific sensor.
Calibration of Fuji BAS-SR type imaging plate as high spatial resolution x-ray radiography recorder

NASA Astrophysics Data System (ADS)

Yan, Ji; Zheng, Jianhua; Zhang, Xing; Chen, Li; Wei, Minxi

2017-05-01

Image Plates as x-ray recorder have advantages including reusable, high dynamic range, large active area, and so on. In this work, Fuji BAS-SR type image plate combined with BAS-5000 scanner is calibrated. The fade rates of Image Plates has been measured using x-ray diffractometric in different room temperature; the spectral response of Image Plates has been measured using 241Am radioactive sealed source and fitting with linear model; the spatial resolution of Image Plates has been measured using micro-focus x-ray tube. The results show that Image Plates has an exponent decade curve and double absorption edge response curve. The spatial resolution of Image Plates with 25μ/50μ scanner resolution is 6.5lp/mm, 11.9lp/mm respectively and gold grid radiography is collected with 80lp/mm spatial resolution using SR-type Image Plates. BAS-SR type Image Plates can do high spatial resolution and quantitative radiographic works. It can be widely used in High energy density physics (HEDP), inertial confinement fusion (ICF) and laboratory astronomy physics.
[Image fusion of gated-SPECT and CT angiography in coronary artery disease. Importance of anatomic-functional correlation].

PubMed

Nazarena Pizzi, M; Aguadé Bruix, S; Cuéllar Calabria, H; Aliaga, V; Candell Riera, J

2010-01-01

A 77-year old patient was admitted for acute coronary syndrome without ST elevation. His risk was stratified using the myocardial perfusion gated SPECT, mild inferior ischemia being observed. Thus, medical therapy was optimized and the patient was discharged. He continued with exertional dyspnea so a coronary CT angiography was performed. It revealed severe lesions in the proximal RCA. SPECT-CT fusion images correlated the myocardial perfusion defect with a posterior descending artery from the RCA, in a co-dominant coronary area. Subsequently, cardiac catheterism was indicated for his treatment. The current use of image fusion studies is limited to patients in whom it is difficult to attribute a perfusion defect to a specific coronary artery. In our patient, the fusion images helped to distinguish between the RCA and the circumflex artery as the culprit artery of ischemia. Copyright © 2010 Elsevier España, S.L. y SEMNIM. All rights reserved.
Fusion of LBP and SWLD using spatio-spectral information for hyperspectral face recognition

NASA Astrophysics Data System (ADS)

Xie, Zhihua; Jiang, Peng; Zhang, Shuai; Xiong, Jinquan

2018-01-01

Hyperspectral imaging, recording intrinsic spectral information of the skin cross different spectral bands, become an important issue for robust face recognition. However, the main challenges for hyperspectral face recognition are high data dimensionality, low signal to noise ratio and inter band misalignment. In this paper, hyperspectral face recognition based on LBP (Local binary pattern) and SWLD (Simplified Weber local descriptor) is proposed to extract discriminative local features from spatio-spectral fusion information. Firstly, the spatio-spectral fusion strategy based on statistical information is used to attain discriminative features of hyperspectral face images. Secondly, LBP is applied to extract the orientation of the fusion face edges. Thirdly, SWLD is proposed to encode the intensity information in hyperspectral images. Finally, we adopt a symmetric Kullback-Leibler distance to compute the encoded face images. The hyperspectral face recognition is tested on Hong Kong Polytechnic University Hyperspectral Face database (PolyUHSFD). Experimental results show that the proposed method has higher recognition rate (92.8%) than the state of the art hyperspectral face recognition algorithms.
Cognitive Fusion Questionnaire-Body Image: Psychometric Properties and Its Incremental Power in the Prediction of Binge Eating Severity.

PubMed

Lucena-Santos, Paola; Trindade, Inês A; Oliveira, Margareth; Pinto-Gouveia, José

2017-05-19

Given the clinical usefulness of the CFQ-BI (Cognitive Fusion Questionnaire-Body Image; the only existing measure to assess the body-image-related cognitive fusion), the present study aimed to confirm its one-factor structure, to verify its measurement invariance between clinical and non-clinical samples, to analyze its internal consistency and sensitivity to detect differences between samples, as well as to explore the incremental and convergent validities of the CFQ-BI scores in Brazilian samples. This was a cross-sectional study, which was conducted in clinical (women with overweight or obesity in treatment for weight loss) and non-clinical samples (women from the general population). The one-factor structure was confirmed showing factorial measurement invariance across clinical and non-clinical samples. The CFQ-BI scores presented an excellent internal consistency, were able to discriminate clinical and non-clinical samples, and were positively associated with binge eating severity, general cognitive fusion, and psychological inflexibility. Furthermore, body-image-related cognitive fusion scores (CFQ-BI) presented incremental validity over a general measure of cognitive fusion in the prediction of binge eating symptoms. This study demonstrated that CFQ-BI is a short scale with reliable and robust scores in Brazilian samples, presenting incremental and convergent validities, measurement invariance, and sensitivity to detect differences between clinical and non-clinical groups of women, enabling comparative studies between them.
Fusion of an Ensemble of Augmented Image Detectors for Robust Object Detection

PubMed Central

Wei, Pan; Anderson, Derek T.

2018-01-01

A significant challenge in object detection is accurate identification of an object’s position in image space, whereas one algorithm with one set of parameters is usually not enough, and the fusion of multiple algorithms and/or parameters can lead to more robust results. Herein, a new computational intelligence fusion approach based on the dynamic analysis of agreement among object detection outputs is proposed. Furthermore, we propose an online versus just in training image augmentation strategy. Experiments comparing the results both with and without fusion are presented. We demonstrate that the augmented and fused combination results are the best, with respect to higher accuracy rates and reduction of outlier influences. The approach is demonstrated in the context of cone, pedestrian and box detection for Advanced Driver Assistance Systems (ADAS) applications. PMID:29562609
Vergence-accommodation conflicts hinder visual performance and cause visual fatigue.

PubMed

Hoffman, David M; Girshick, Ahna R; Akeley, Kurt; Banks, Martin S

2008-03-28

Three-dimensional (3D) displays have become important for many applications including vision research, operation of remote devices, medical imaging, surgical training, scientific visualization, virtual prototyping, and more. In many of these applications, it is important for the graphic image to create a faithful impression of the 3D structure of the portrayed object or scene. Unfortunately, 3D displays often yield distortions in perceived 3D structure compared with the percepts of the real scenes the displays depict. A likely cause of such distortions is the fact that computer displays present images on one surface. Thus, focus cues-accommodation and blur in the retinal image-specify the depth of the display rather than the depths in the depicted scene. Additionally, the uncoupling of vergence and accommodation required by 3D displays frequently reduces one's ability to fuse the binocular stimulus and causes discomfort and fatigue for the viewer. We have developed a novel 3D display that presents focus cues that are correct or nearly correct for the depicted scene. We used this display to evaluate the influence of focus cues on perceptual distortions, fusion failures, and fatigue. We show that when focus cues are correct or nearly correct, (1) the time required to identify a stereoscopic stimulus is reduced, (2) stereoacuity in a time-limited task is increased, (3) distortions in perceived depth are reduced, and (4) viewer fatigue and discomfort are reduced. We discuss the implications of this work for vision research and the design and use of displays.
Dynamics of laser-driven proton beam focusing and transport into solid density matter

NASA Astrophysics Data System (ADS)

Kim, J.; McGuffey, C.; Beg, F.; Wei, M.; Mariscal, D.; Chen, S.; Fuchs, J.

2016-10-01

Isochoric heating and local energy deposition capabilities make intense proton beams appealing for studying high energy density physics and the Fast Ignition of inertial confinement fusion. To study proton beam focusing that results in high beam density, experiments have been conducted using different target geometries irradiated by a kilojoule, 10 ps pulse of the OMEGA EP laser. The beam focus was measured by imaging beam-induced Cu K-alpha emission on a Cu foil that was positioned at a fixed distance. Compared to a free target, structured targets having shapes of wedge and cone show a brighter and narrower K-alpha radiation emission spot on a Cu foil indicating higher beam focusability. Experimentally observed images with proton radiography demonstrate the existence of transverse fields on the structures. Full-scale simulations including the contribution of a long pulse duration of the laser confirm that such fields can be caused by hot electrons moving through the structures. The simulated fields are strong enough to reflect the diverging main proton beam and pinch a transverse probe beam. Detailed simulation results including the beam focusing and transport of the focused intense proton beam in Cu foil will be presented. This work was supported by the National Laser User Facility Program through Award DE-NA0002034.
The role of imaging based prostate biopsy morphology in a data fusion paradigm for transducing prognostic predictions

NASA Astrophysics Data System (ADS)

Khan, Faisal M.; Kulikowski, Casimir A.

2016-03-01

A major focus area for precision medicine is in managing the treatment of newly diagnosed prostate cancer patients. For patients with a positive biopsy, clinicians aim to develop an individualized treatment plan based on a mechanistic understanding of the disease factors unique to each patient. Recently, there has been a movement towards a multi-modal view of the cancer through the fusion of quantitative information from multiple sources, imaging and otherwise. Simultaneously, there have been significant advances in machine learning methods for medical prognostics which integrate a multitude of predictive factors to develop an individualized risk assessment and prognosis for patients. An emerging area of research is in semi-supervised approaches which transduce the appropriate survival time for censored patients. In this work, we apply a novel semi-supervised approach for support vector regression to predict the prognosis for newly diagnosed prostate cancer patients. We integrate clinical characteristics of a patient's disease with imaging derived metrics for biomarker expression as well as glandular and nuclear morphology. In particular, our goal was to explore the performance of nuclear and glandular architecture within the transduction algorithm and assess their predictive power when compared with the Gleason score manually assigned by a pathologist. Our analysis in a multi-institutional cohort of 1027 patients indicates that not only do glandular and morphometric characteristics improve the predictive power of the semi-supervised transduction algorithm; they perform better when the pathological Gleason is absent. This work represents one of the first assessments of quantitative prostate biopsy architecture versus the Gleason grade in the context of a data fusion paradigm which leverages a semi-supervised approach for risk prognosis.
Early melanoma diagnosis with mobile imaging.

PubMed

Do, Thanh-Toan; Zhou, Yiren; Zheng, Haitian; Cheung, Ngai-Man; Koh, Dawn

2014-01-01

We research a mobile imaging system for early diagnosis of melanoma. Different from previous work, we focus on smartphone-captured images, and propose a detection system that runs entirely on the smartphone. Smartphone-captured images taken under loosely-controlled conditions introduce new challenges for melanoma detection, while processing performed on the smartphone is subject to computation and memory constraints. To address these challenges, we propose to localize the skin lesion by combining fast skin detection and fusion of two fast segmentation results. We propose new features to capture color variation and border irregularity which are useful for smartphone-captured images. We also propose a new feature selection criterion to select a small set of good features used in the final lightweight system. Our evaluation confirms the effectiveness of proposed algorithms and features. In addition, we present our system prototype which computes selected visual features from a user-captured skin lesion image, and analyzes them to estimate the likelihood of malignance, all on an off-the-shelf smartphone.
A motorized ultrasound system for MRI-ultrasound fusion guided prostatectomy

NASA Astrophysics Data System (ADS)

Seifabadi, Reza; Xu, Sheng; Pinto, Peter; Wood, Bradford J.

2016-03-01

Purpose: This study presents MoTRUS, a motorized transrectal ultrasound system, to enable remote navigation of a transrectal ultrasound (TRUS) probe during da Vinci assisted prostatectomy. MoTRUS not only provides a stable platform to the ultrasound probe, but also allows the physician to navigate it remotely while sitting on the da Vinci console. This study also presents phantom feasibility study with the goal being intraoperative MRI-US image fusion capability to bring preoperative MR images to the operating room for the best visualization of the gland, boundaries, nerves, etc. Method: A two degree-of-freedom probe holder is developed to insert and rotate a bi-plane transrectal ultrasound transducer. A custom joystick is made to enable remote navigation of MoTRUS. Safety features have been considered to avoid inadvertent risks (if any) to the patient. Custom design software has been developed to fuse pre-operative MR images to intraoperative ultrasound images acquired by MoTRUS. Results: Remote TRUS probe navigation was evaluated on a patient after taking required consents during prostatectomy using MoTRUS. It took 10 min to setup the system in OR. MoTRUS provided similar capability in addition to remote navigation and stable imaging. No complications were observed. Image fusion was evaluated on a commercial prostate phantom. Electromagnetic tracking was used for the fusion. Conclusions: Motorized navigation of the TRUS probe during prostatectomy is safe and feasible. Remote navigation provides physician with a more precise and easier control of the ultrasound image while removing the burden of manual manipulation of the probe. Image fusion improved visualization of the prostate and boundaries in a phantom study.
Near infrared and visible face recognition based on decision fusion of LBP and DCT features

NASA Astrophysics Data System (ADS)

Xie, Zhihua; Zhang, Shuai; Liu, Guodong; Xiong, Jinquan

2018-03-01

Visible face recognition systems, being vulnerable to illumination, expression, and pose, can not achieve robust performance in unconstrained situations. Meanwhile, near infrared face images, being light- independent, can avoid or limit the drawbacks of face recognition in visible light, but its main challenges are low resolution and signal noise ratio (SNR). Therefore, near infrared and visible fusion face recognition has become an important direction in the field of unconstrained face recognition research. In order to extract the discriminative complementary features between near infrared and visible images, in this paper, we proposed a novel near infrared and visible face fusion recognition algorithm based on DCT and LBP features. Firstly, the effective features in near-infrared face image are extracted by the low frequency part of DCT coefficients and the partition histograms of LBP operator. Secondly, the LBP features of visible-light face image are extracted to compensate for the lacking detail features of the near-infrared face image. Then, the LBP features of visible-light face image, the DCT and LBP features of near-infrared face image are sent to each classifier for labeling. Finally, decision level fusion strategy is used to obtain the final recognition result. The visible and near infrared face recognition is tested on HITSZ Lab2 visible and near infrared face database. The experiment results show that the proposed method extracts the complementary features of near-infrared and visible face images and improves the robustness of unconstrained face recognition. Especially for the circumstance of small training samples, the recognition rate of proposed method can reach 96.13%, which has improved significantly than 92.75 % of the method based on statistical feature fusion.
Enhancing 18F-FDG-PET/CT analysis in lung cancer patients. Is CT-CT image fusion helpful in predicting pleural involvement? A pilot study.

PubMed

Kapfhammer, A; Winkens, T; Lesser, T; Reissig, A; Steinert, M; Freesmeyer, M

2015-01-01

To retrospectively evaluate the feasibility and value of CT-CT image fusion to assess the shift of peripheral lung cancers with/-out chest wall infiltration, comparing computed tomography acquisitions in shallow-breathing (SB-CT) and deep-inspiration breath-hold (DIBH-CT) in patients undergoing FDG-PET/CT for lung cancer staging. Image fusion of SB-CT and DIBH-CT was performed with a multimodal workstation used for nuclear medicine fusion imaging. The distance of intrathoracic landmarks and the positional shift of tumours were measured using semi-transparent overlay of both CT series. Statistical analyses were adjusted for confounders of tumour infiltration. Cutoff levels were calculated for prediction of no-/infiltration. Lateral pleural recessus and diaphragm showed the largest respiratory excursions. Infiltrating lung cancers showed more limited respiratory shifts than non-infiltrating tumours. A large respiratory tumour-motility accurately predicted non-infiltration. However, the tumour shifts were limited and variable, limiting the accuracy of prediction. This pilot fusion study proved feasible and allowed a simple analysis of the respiratory shifts of peripheral lung tumours using CT-CT image fusion in a PET/CT setting. The calculated cutoffs were useful in predicting the exclusion of chest wall infiltration but did not accurately predict tumour infiltration. This method can provide additional qualitative information in patients with lung cancers with contact to the chest wall but unclear CT evidence of infiltration undergoing PET/CT without the need of additional investigations. Considering the small sample size investigated, further studies are necessary to verify the obtained results.
Fission and activation of uranium by fusion-plasma neutrons

NASA Technical Reports Server (NTRS)

Lee, J. H.; Hohl, F.; Mcfarland, D. R.

1978-01-01

Fusion-fission hybrid reactors are discussed in terms of two main purposes: to breed fissile materials (Pu 233 and Th 233 from U 238 or Th 232) for use in low-reactivity breeders, and to produce tritium from lithium to refuel fusion plasma cores. Neutron flux generation is critical for both processes. Various methods for generating the flux are described, with attention to new geometries for multiple plasma focus arrays, e.g., hypocycloidal pinch and staged plasma focus devices. These methods are evaluated with reference to their applicability to D-D fusion reactors, which will ensure a virtually unlimited energy supply. Accurate observations of the neutron flux from such schemes are obtained by using different target materials in the plasma focus.
Label fusion based brain MR image segmentation via a latent selective model

NASA Astrophysics Data System (ADS)

Liu, Gang; Guo, Xiantang; Zhu, Kai; Liao, Hengxu

2018-04-01

Multi-atlas segmentation is an effective approach and increasingly popular for automatically labeling objects of interest in medical images. Recently, segmentation methods based on generative models and patch-based techniques have become the two principal branches of label fusion. However, these generative models and patch-based techniques are only loosely related, and the requirement for higher accuracy, faster segmentation, and robustness is always a great challenge. In this paper, we propose novel algorithm that combines the two branches using global weighted fusion strategy based on a patch latent selective model to perform segmentation of specific anatomical structures for human brain magnetic resonance (MR) images. In establishing this probabilistic model of label fusion between the target patch and patch dictionary, we explored the Kronecker delta function in the label prior, which is more suitable than other models, and designed a latent selective model as a membership prior to determine from which training patch the intensity and label of the target patch are generated at each spatial location. Because the image background is an equally important factor for segmentation, it is analyzed in label fusion procedure and we regard it as an isolated label to keep the same privilege between the background and the regions of interest. During label fusion with the global weighted fusion scheme, we use Bayesian inference and expectation maximization algorithm to estimate the labels of the target scan to produce the segmentation map. Experimental results indicate that the proposed algorithm is more accurate and robust than the other segmentation methods.
Radiological Determination of Postoperative Cervical Fusion: A Systematic Review.

PubMed

Rhee, John M; Chapman, Jens R; Norvell, Daniel C; Smith, Justin; Sherry, Ned A; Riew, K Daniel

2015-07-01

Systematic review. To determine best criteria for radiological determination of postoperative subaxial cervical fusion to be applied to current clinical practice and ongoing future research assessing fusion to standardize assessment and improve comparability. Despite availability of multiple imaging modalities and criteria, there remains no method of determining cervical fusion with absolute certainty, nor clear consensus on specific criteria to be applied. A systematic search in MEDLINE/Cochrane Collaboration Library (through March 2014). Included studies assessed C2 to C7 via anterior or posterior approach, at 12 weeks or more postoperative, with any graft or implant. Overall body of evidence with respect to 6 posited key questions was determined using Grading of Recommendations Assessment, Development and Evaluation and Agency for Healthcare Research and Quality precepts. Of plain radiographical modalities, there is moderate evidence that the interspinous process motion method (<1 mm) is more accurate than the Cobb angle method for assessing anterior cervical fusion. Of the advanced imaging modalities, there is moderate evidence that computed tomography (CT) is more accurate and reliable than magnetic resonance imaging in assessing anterior cervical fusion. There is insufficient evidence regarding the optimal modality and criteria for assessing posterior cervical fusions and insufficient evidence to support a single time point after surgery as being optimal for determining fusion, although some evidence suggest that reliability of radiography and CT improves with increasing time postoperatively. We recommend using less than 1-mm motion as the initial modality for determining anterior cervical arthrodesis for both clinical and research applications. If further imaging is needed because of indeterminate radiographical evaluation, we recommend CT, which has relatively high accuracy and reliability, but due to greater radiation exposure and cost, it is not routinely suggested. We recommend that plain radiographs also be the initial method of determining posterior cervical fusion but suggest a lower threshold for obtaining CT scans because dynamic radiographs may not be as useful if spinous processes have been removed by laminectomy. 1.
Multi-modality image fusion based on enhanced fuzzy radial basis function neural networks.

PubMed

Chao, Zhen; Kim, Dohyeon; Kim, Hee-Joung

2018-04-01

In clinical applications, single modality images do not provide sufficient diagnostic information. Therefore, it is necessary to combine the advantages or complementarities of different modalities of images. Recently, neural network technique was applied to medical image fusion by many researchers, but there are still many deficiencies. In this study, we propose a novel fusion method to combine multi-modality medical images based on the enhanced fuzzy radial basis function neural network (Fuzzy-RBFNN), which includes five layers: input, fuzzy partition, front combination, inference, and output. Moreover, we propose a hybrid of the gravitational search algorithm (GSA) and error back propagation algorithm (EBPA) to train the network to update the parameters of the network. Two different patterns of images are used as inputs of the neural network, and the output is the fused image. A comparison with the conventional fusion methods and another neural network method through subjective observation and objective evaluation indexes reveals that the proposed method effectively synthesized the information of input images and achieved better results. Meanwhile, we also trained the network by using the EBPA and GSA, individually. The results reveal that the EBPGSA not only outperformed both EBPA and GSA, but also trained the neural network more accurately by analyzing the same evaluation indexes. Copyright © 2018 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.
Application of Virtual Navigation with Multimodality Image Fusion in Foramen Ovale Cannulation.

PubMed

Qiu, Xixiong; Liu, Weizong; Zhang, Mingdong; Lin, Hengzhou; Zhou, Shoujun; Lei, Yi; Xia, Jun

2017-11-01

Idiopathic trigeminal neuralgia (ITN) can be effectively treated with radiofrequency thermocoagulation. However, this procedure requires cannulation of the foramen ovale, and conventional cannulation methods are associated with high failure rates. Multimodality imaging can improve the accuracy of cannulation because each imaging method can compensate for the drawbacks of the other. We aim to determine the feasibility and accuracy of percutaneous foramen ovale cannulation under the guidance of virtual navigation with multimodality image fusion in a self-designed anatomical model of human cadaveric heads. Five cadaveric head specimens were investigated in this study. Spiral computed tomography (CT) scanning clearly displayed the foramen ovale in all five specimens (10 foramina), which could not be visualized using two-dimensional ultrasound alone. The ultrasound and spiral CT images were fused, and percutaneous cannulation of the foramen ovale was performed under virtual navigation. After this, spiral CT scanning was immediately repeated to confirm the accuracy of the cannulation. Postprocedural spiral CT confirmed that the ultrasound and CT images had been successfully fused for all 10 foramina, which were accurately and successfully cannulated. The success rates of both image fusion and cannulation were 100%. Virtual navigation with multimodality image fusion can substantially facilitate foramen ovale cannulation and is worthy of clinical application. © 2017 American Academy of Pain Medicine. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com
An effective content-based image retrieval technique for image visuals representation based on the bag-of-visual-words model

PubMed Central

Jabeen, Safia; Mehmood, Zahid; Mahmood, Toqeer; Saba, Tanzila; Rehman, Amjad; Mahmood, Muhammad Tariq

2018-01-01

For the last three decades, content-based image retrieval (CBIR) has been an active research area, representing a viable solution for retrieving similar images from an image repository. In this article, we propose a novel CBIR technique based on the visual words fusion of speeded-up robust features (SURF) and fast retina keypoint (FREAK) feature descriptors. SURF is a sparse descriptor whereas FREAK is a dense descriptor. Moreover, SURF is a scale and rotation-invariant descriptor that performs better in the case of repeatability, distinctiveness, and robustness. It is robust to noise, detection errors, geometric, and photometric deformations. It also performs better at low illumination within an image as compared to the FREAK descriptor. In contrast, FREAK is a retina-inspired speedy descriptor that performs better for classification-based problems as compared to the SURF descriptor. Experimental results show that the proposed technique based on the visual words fusion of SURF-FREAK descriptors combines the features of both descriptors and resolves the aforementioned issues. The qualitative and quantitative analysis performed on three image collections, namely Corel-1000, Corel-1500, and Caltech-256, shows that proposed technique based on visual words fusion significantly improved the performance of the CBIR as compared to the feature fusion of both descriptors and state-of-the-art image retrieval techniques. PMID:29694429

An effective content-based image retrieval technique for image visuals representation based on the bag-of-visual-words model.

PubMed

Jabeen, Safia; Mehmood, Zahid; Mahmood, Toqeer; Saba, Tanzila; Rehman, Amjad; Mahmood, Muhammad Tariq

2018-01-01

For the last three decades, content-based image retrieval (CBIR) has been an active research area, representing a viable solution for retrieving similar images from an image repository. In this article, we propose a novel CBIR technique based on the visual words fusion of speeded-up robust features (SURF) and fast retina keypoint (FREAK) feature descriptors. SURF is a sparse descriptor whereas FREAK is a dense descriptor. Moreover, SURF is a scale and rotation-invariant descriptor that performs better in the case of repeatability, distinctiveness, and robustness. It is robust to noise, detection errors, geometric, and photometric deformations. It also performs better at low illumination within an image as compared to the FREAK descriptor. In contrast, FREAK is a retina-inspired speedy descriptor that performs better for classification-based problems as compared to the SURF descriptor. Experimental results show that the proposed technique based on the visual words fusion of SURF-FREAK descriptors combines the features of both descriptors and resolves the aforementioned issues. The qualitative and quantitative analysis performed on three image collections, namely Corel-1000, Corel-1500, and Caltech-256, shows that proposed technique based on visual words fusion significantly improved the performance of the CBIR as compared to the feature fusion of both descriptors and state-of-the-art image retrieval techniques.
Microwave and video sensor fusion for the shape extraction of 3D space objects

NASA Technical Reports Server (NTRS)

Shaw, Scott W.; Defigueiredo, Rui J. P.; Krishen, Kumar

1987-01-01

A new system for the fusion of optical image data and polarized radar scattering cross-sections is presented. By considering the scattering data in conjunction with image data, the problem of ambiguity can be reduced. Only a small part of the surface needs to be reconstructed from the radar cross-sections; the remaining portion is constrained by the optical image.
A real-time photogrammetric algorithm for sensor and synthetic image fusion with application to aviation combined vision

NASA Astrophysics Data System (ADS)

Lebedev, M. A.; Stepaniants, D. G.; Komarov, D. V.; Vygolov, O. V.; Vizilter, Yu. V.; Zheltov, S. Yu.

2014-08-01

The paper addresses a promising visualization concept related to combination of sensor and synthetic images in order to enhance situation awareness of a pilot during an aircraft landing. A real-time algorithm for a fusion of a sensor image, acquired by an onboard camera, and a synthetic 3D image of the external view, generated in an onboard computer, is proposed. The pixel correspondence between the sensor and the synthetic images is obtained by an exterior orientation of a "virtual" camera using runway points as a geospatial reference. The runway points are detected by the Projective Hough Transform, which idea is to project the edge map onto a horizontal plane in the object space (the runway plane) and then to calculate intensity projections of edge pixels on different directions of intensity gradient. The performed experiments on simulated images show that on a base glide path the algorithm provides image fusion with pixel accuracy, even in the case of significant navigation errors.
Fast single image dehazing based on image fusion

NASA Astrophysics Data System (ADS)

Liu, Haibo; Yang, Jie; Wu, Zhengping; Zhang, Qingnian

2015-01-01

Images captured in foggy weather conditions often fade the colors and reduce the contrast of the observed objects. An efficient image fusion method is proposed to remove haze from a single input image. First, the initial medium transmission is estimated based on the dark channel prior. Second, the method adopts an assumption that the degradation level affected by haze of each region is the same, which is similar to the Retinex theory, and uses a simple Gaussian filter to get the coarse medium transmission. Then, pixel-level fusion is achieved between the initial medium transmission and coarse medium transmission. The proposed method can recover a high-quality haze-free image based on the physical model, and the complexity of the proposed method is only a linear function of the number of input image pixels. Experimental results demonstrate that the proposed method can allow a very fast implementation and achieve better restoration for visibility and color fidelity compared to some state-of-the-art methods.
Relation between lung perfusion defects and intravascular clots in acute pulmonary thromboembolism: assessment with breath-hold SPECT-CT pulmonary angiography fusion images.

PubMed

Suga, Kazuyoshi; Yasuhiko, Kawakami; Iwanaga, Hideyuki; Tokuda, Osamu; Matsunaga, Naofumi

2008-09-01

The relation between lung perfusion defects and intravascular clots in acute pulmonary thromboembolism (PTE) was comprehensively assessed on deep-inspiratory breath-hold (DIBrH) perfusion SPECT-computed tomographic pulmonary angiography (CTPA) fusion images. Subjects were 34 acute PTE patients, who had successfully performed DIBrH perfusion SPECT using a dual-headed SPECT and a respiratory tracking system. Automated DIBrH SPECT-CTPA fusion images were used to assess the relation between lung perfusion defects and intravascular clots detected by CTPA. DIBrH SPECT visualized 175 lobar/segmental or subsegmental defects in 34 patients, and CTPA visualized 61 intravascular clots at variable locations in 30 (88%) patients, but no clots in four (12%) patients. In 30 patients with clots, the fusion images confirmed that 69 (41%) perfusion defects (20 segmental, 45 subsegmental and 4 lobar defects) of total 166 defects were located in lung territories without clots, although the remaining 97 (58%) defects were located in lung territories with clots. Perfusion defect was absent in lung territories with clots (one lobar branch and three segmental branches) in four (12%) of these patients. In four patients without clots, nine perfusion defects including four segmental ones were present. Because of unexpected dissociation between intravascular clots and lung perfusion defects, the present fusion images will be a useful adjunct to CTPA in the diagnosis of acute PTE.
Infrared and visible fusion face recognition based on NSCT domain

NASA Astrophysics Data System (ADS)

Xie, Zhihua; Zhang, Shuai; Liu, Guodong; Xiong, Jinquan

2018-01-01

Visible face recognition systems, being vulnerable to illumination, expression, and pose, can not achieve robust performance in unconstrained situations. Meanwhile, near infrared face images, being light- independent, can avoid or limit the drawbacks of face recognition in visible light, but its main challenges are low resolution and signal noise ratio (SNR). Therefore, near infrared and visible fusion face recognition has become an important direction in the field of unconstrained face recognition research. In this paper, a novel fusion algorithm in non-subsampled contourlet transform (NSCT) domain is proposed for Infrared and visible face fusion recognition. Firstly, NSCT is used respectively to process the infrared and visible face images, which exploits the image information at multiple scales, orientations, and frequency bands. Then, to exploit the effective discriminant feature and balance the power of high-low frequency band of NSCT coefficients, the local Gabor binary pattern (LGBP) and Local Binary Pattern (LBP) are applied respectively in different frequency parts to obtain the robust representation of infrared and visible face images. Finally, the score-level fusion is used to fuse the all the features for final classification. The visible and near infrared face recognition is tested on HITSZ Lab2 visible and near infrared face database. Experiments results show that the proposed method extracts the complementary features of near-infrared and visible-light images and improves the robustness of unconstrained face recognition.
Assessment of radiofrequency ablation margin by MRI-MRI image fusion in hepatocellular carcinoma.

PubMed

Wang, Xiao-Li; Li, Kai; Su, Zhong-Zhen; Huang, Ze-Ping; Wang, Ping; Zheng, Rong-Qin

2015-05-07

To investigate the feasibility and clinical value of magnetic resonance imaging (MRI)-MRI image fusion in assessing the ablative margin (AM) for hepatocellular carcinoma (HCC). A newly developed ultrasound workstation for MRI-MRI image fusion was used to evaluate the AM of 62 tumors in 52 HCC patients after radiofrequency ablation (RFA). The lesions were divided into two groups: group A, in which the tumor was completely ablated and 5 mm AM was achieved (n = 32); and group B, in which the tumor was completely ablated but 5 mm AM was not achieved (n = 29). To detect local tumor progression (LTP), all patients were followed every two months by contrast-enhanced ultrasound, contrast-enhanced MRI or computed tomography (CT) in the first year after RFA. Then, the follow-up interval was prolonged to every three months after the first year. Of the 62 tumors, MRI-MRI image fusion was successful in 61 (98.4%); the remaining case had significant deformation of the liver and massive ascites after RFA. The time required for creating image fusion and AM evaluation was 15.5 ± 5.5 min (range: 8-22 min) and 9.6 ± 3.2 min (range: 6-14 min), respectively. The follow-up period ranged from 1-23 mo (14.2 ± 5.4 mo). In group A, no LTP was detected in 32 lesions, whereas in group B, LTP was detected in 4 of 29 tumors, which occurred at 2, 7, 9, and 15 mo after RFA. The frequency of LTP in group B (13.8%; 4/29) was significantly higher than that in group A (0/32, P = 0.046). All of the LTPs occurred in the area in which the 5 mm AM was not achieved. The MRI-MRI image fusion using an ultrasound workstation is feasible and useful for evaluating the AM after RFA for HCC.
Assessment of radiofrequency ablation margin by MRI-MRI image fusion in hepatocellular carcinoma

PubMed Central

Wang, Xiao-Li; Li, Kai; Su, Zhong-Zhen; Huang, Ze-Ping; Wang, Ping; Zheng, Rong-Qin

2015-01-01

AIM: To investigate the feasibility and clinical value of magnetic resonance imaging (MRI)-MRI image fusion in assessing the ablative margin (AM) for hepatocellular carcinoma (HCC). METHODS: A newly developed ultrasound workstation for MRI-MRI image fusion was used to evaluate the AM of 62 tumors in 52 HCC patients after radiofrequency ablation (RFA). The lesions were divided into two groups: group A, in which the tumor was completely ablated and 5 mm AM was achieved (n = 32); and group B, in which the tumor was completely ablated but 5 mm AM was not achieved (n = 29). To detect local tumor progression (LTP), all patients were followed every two months by contrast-enhanced ultrasound, contrast-enhanced MRI or computed tomography (CT) in the first year after RFA. Then, the follow-up interval was prolonged to every three months after the first year. RESULTS: Of the 62 tumors, MRI-MRI image fusion was successful in 61 (98.4%); the remaining case had significant deformation of the liver and massive ascites after RFA. The time required for creating image fusion and AM evaluation was 15.5 ± 5.5 min (range: 8-22 min) and 9.6 ± 3.2 min (range: 6-14 min), respectively. The follow-up period ranged from 1-23 mo (14.2 ± 5.4 mo). In group A, no LTP was detected in 32 lesions, whereas in group B, LTP was detected in 4 of 29 tumors, which occurred at 2, 7, 9, and 15 mo after RFA. The frequency of LTP in group B (13.8%; 4/29) was significantly higher than that in group A (0/32, P = 0.046). All of the LTPs occurred in the area in which the 5 mm AM was not achieved. CONCLUSION: The MRI-MRI image fusion using an ultrasound workstation is feasible and useful for evaluating the AM after RFA for HCC. PMID:25954109
Propulsion and Power Generation Capabilities of a Dense Plasma Focus (DPF) Fusion System for Future Military Aerospace Vehicles (POSTPRINT)

DTIC Science & Technology

2005-10-06

The objective of this study was to perform a parametric evaluation of the performance and interface characteristics of a dense plasma focus (DPF...dense plasma focus (DPF) fusion power and propulsion technology, with advanced waverider-like airframe configurations utilizing air-breathing MHD
Fusion of infrared polarization and intensity images based on improved toggle operator

NASA Astrophysics Data System (ADS)

Zhu, Pan; Ding, Lei; Ma, Xiaoqing; Huang, Zhanhua

2018-01-01

Integration of infrared polarization and intensity images has been a new topic in infrared image understanding and interpretation. The abundant infrared details and target from infrared image and the salient edge and shape information from polarization image should be preserved or even enhanced in the fused result. In this paper, a new fusion method is proposed for infrared polarization and intensity images based on the improved multi-scale toggle operator with spatial scale, which can effectively extract the feature information of source images and heavily reduce redundancy among different scale. Firstly, the multi-scale image features of infrared polarization and intensity images are respectively extracted at different scale levels by the improved multi-scale toggle operator. Secondly, the redundancy of the features among different scales is reduced by using spatial scale. Thirdly, the final image features are combined by simply adding all scales of feature images together, and a base image is calculated by performing mean value weighted method on smoothed source images. Finally, the fusion image is obtained by importing the combined image features into the base image with a suitable strategy. Both objective assessment and subjective vision of the experimental results indicate that the proposed method obtains better performance in preserving the details and edge information as well as improving the image contrast.
Color image guided depth image super resolution using fusion filter

NASA Astrophysics Data System (ADS)

He, Jin; Liang, Bin; He, Ying; Yang, Jun

2018-04-01

Depth cameras are currently playing an important role in many areas. However, most of them can only obtain lowresolution (LR) depth images. Color cameras can easily provide high-resolution (HR) color images. Using color image as a guide image is an efficient way to get a HR depth image. In this paper, we propose a depth image super resolution (SR) algorithm, which uses a HR color image as a guide image and a LR depth image as input. We use the fusion filter of guided filter and edge based joint bilateral filter to get HR depth image. Our experimental results on Middlebury 2005 datasets show that our method can provide better quality in HR depth images both numerically and visually.
On the creation of high spatial resolution imaging spectroscopy data from multi-temporal low spatial resolution imagery

NASA Astrophysics Data System (ADS)

Yao, Wei; van Aardt, Jan; Messinger, David

2017-05-01

The Hyperspectral Infrared Imager (HyspIRI) mission aims to provide global imaging spectroscopy data to the benefit of especially ecosystem studies. The onboard spectrometer will collect radiance spectra from the visible to short wave infrared (VSWIR) regions (400-2500 nm). The mission calls for fine spectral resolution (10 nm band width) and as such will enable scientists to perform material characterization, species classification, and even sub-pixel mapping. However, the global coverage requirement results in a relatively low spatial resolution (GSD 30m), which restricts applications to objects of similar scales. We therefore have focused on the assessment of sub-pixel vegetation structure from spectroscopy data in past studies. In this study, we investigate the development or reconstruction of higher spatial resolution imaging spectroscopy data via fusion of multi-temporal data sets to address the drawbacks implicit in low spatial resolution imagery. The projected temporal resolution of the HyspIRI VSWIR instrument is 15 days, which implies that we have access to as many as six data sets for an area over the course of a growth season. Previous studies have shown that select vegetation structural parameters, e.g., leaf area index (LAI) and gross ecosystem production (GEP), are relatively constant in summer and winter for temperate forests; we therefore consider the data sets collected in summer to be from a similar, stable forest structure. The first step, prior to fusion, involves registration of the multi-temporal data. A data fusion algorithm then can be applied to the pre-processed data sets. The approach hinges on an algorithm that has been widely applied to fuse RGB images. Ideally, if we have four images of a scene which all meet the following requirements - i) they are captured with the same camera configurations; ii) the pixel size of each image is x; and iii) at least r2 images are aligned on a grid of x/r - then a high-resolution image, with a pixel size of x/r, can be reconstructed from the multi-temporal set. The algorithm was applied to data from NASA's classic Airborne Visible and Infrared Imaging Spectrometer (AVIRIS-C; GSD 18m), collected between 2013-2015 (summer and fall) over our study area (NEON's Southwest Pacific Domain; Fresno, CA) to generate higher spatial resolution imagery (GSD 9m). The reconstructed data set was validated via comparison to NEON's imaging spectrometer (NIS) data (GSD 1m). The results showed that algorithm worked well with the AVIRIS-C data and could be applied to the HyspIRI data.
A review of potential image fusion methods for remote sensing-based irrigation management: Part II

USDA-ARS?s Scientific Manuscript database

Satellite-based sensors provide data at either greater spectral and coarser spatial resolutions, or lower spectral and finer spatial resolutions due to complementary spectral and spatial characteristics of optical sensor systems. In order to overcome this limitation, image fusion has been suggested ...
Multimodal Neuroimaging: Basic Concepts and Classification of Neuropsychiatric Diseases.

PubMed

Tulay, Emine Elif; Metin, Barış; Tarhan, Nevzat; Arıkan, Mehmet Kemal

2018-06-01

Neuroimaging techniques are widely used in neuroscience to visualize neural activity, to improve our understanding of brain mechanisms, and to identify biomarkers-especially for psychiatric diseases; however, each neuroimaging technique has several limitations. These limitations led to the development of multimodal neuroimaging (MN), which combines data obtained from multiple neuroimaging techniques, such as electroencephalography, functional magnetic resonance imaging, and yields more detailed information about brain dynamics. There are several types of MN, including visual inspection, data integration, and data fusion. This literature review aimed to provide a brief summary and basic information about MN techniques (data fusion approaches in particular) and classification approaches. Data fusion approaches are generally categorized as asymmetric and symmetric. The present review focused exclusively on studies based on symmetric data fusion methods (data-driven methods), such as independent component analysis and principal component analysis. Machine learning techniques have recently been introduced for use in identifying diseases and biomarkers of disease. The machine learning technique most widely used by neuroscientists is classification-especially support vector machine classification. Several studies differentiated patients with psychiatric diseases and healthy controls with using combined datasets. The common conclusion among these studies is that the prediction of diseases increases when combining data via MN techniques; however, there remain a few challenges associated with MN, such as sample size. Perhaps in the future N-way fusion can be used to combine multiple neuroimaging techniques or nonimaging predictors (eg, cognitive ability) to overcome the limitations of MN.
Research on Remote Sensing Image Classification Based on Feature Level Fusion

NASA Astrophysics Data System (ADS)

Yuan, L.; Zhu, G.

2018-04-01

Remote sensing image classification, as an important direction of remote sensing image processing and application, has been widely studied. However, in the process of existing classification algorithms, there still exists the phenomenon of misclassification and missing points, which leads to the final classification accuracy is not high. In this paper, we selected Sentinel-1A and Landsat8 OLI images as data sources, and propose a classification method based on feature level fusion. Compare three kind of feature level fusion algorithms (i.e., Gram-Schmidt spectral sharpening, Principal Component Analysis transform and Brovey transform), and then select the best fused image for the classification experimental. In the classification process, we choose four kinds of image classification algorithms (i.e. Minimum distance, Mahalanobis distance, Support Vector Machine and ISODATA) to do contrast experiment. We use overall classification precision and Kappa coefficient as the classification accuracy evaluation criteria, and the four classification results of fused image are analysed. The experimental results show that the fusion effect of Gram-Schmidt spectral sharpening is better than other methods. In four kinds of classification algorithms, the fused image has the best applicability to Support Vector Machine classification, the overall classification precision is 94.01 % and the Kappa coefficients is 0.91. The fused image with Sentinel-1A and Landsat8 OLI is not only have more spatial information and spectral texture characteristics, but also enhances the distinguishing features of the images. The proposed method is beneficial to improve the accuracy and stability of remote sensing image classification.
Short memory fuzzy fusion image recognition schema employing spatial and Fourier descriptors

NASA Astrophysics Data System (ADS)

Raptis, Sotiris N.; Tzafestas, Spyros G.

2001-03-01

Single images quite often do not bear enough information for precise interpretation due to a variety of reasons. Multiple image fusion and adequate integration recently became the state of the art in the pattern recognition field. In this paper presented here and enhanced multiple observation schema is discussed investigating improvements to the baseline fuzzy- probabilistic image fusion methodology. The first innovation introduced consists in considering only a limited but seemingly ore effective part of the uncertainty information obtained by a certain time restricting older uncertainty dependencies and alleviating computational burden that is now needed for short sequence (stored into memory) of samples. The second innovation essentially grouping them into feature-blind object hypotheses. Experiment settings include a sequence of independent views obtained by camera being moved around the investigated object.
Ontological Issues in Higher Levels of Information Fusion: User Refinement of the Fusion Process

DTIC Science & Technology

2003-01-01

fusion question, the thing that is separates the Greek We explore the higher-level purpose offusion systems by philosophical questions and modem day...the The Greeks focused on both data fusion and the Fusion02 conference there are common fusion questions philosophical questions of an ontology - the...data World of Visible Things Belief (pistis) fusion - user refinement. The rest of the paper is as Appearances follows: Section 2 details the Greek
Improving the recognition of fingerprint biometric system using enhanced image fusion

NASA Astrophysics Data System (ADS)

Alsharif, Salim; El-Saba, Aed; Stripathi, Reshma

2010-04-01

Fingerprints recognition systems have been widely used by financial institutions, law enforcement, border control, visa issuing, just to mention few. Biometric identifiers can be counterfeited, but considered more reliable and secure compared to traditional ID cards or personal passwords methods. Fingerprint pattern fusion improves the performance of a fingerprint recognition system in terms of accuracy and security. This paper presents digital enhancement and fusion approaches that improve the biometric of the fingerprint recognition system. It is a two-step approach. In the first step raw fingerprint images are enhanced using high-frequency-emphasis filtering (HFEF). The second step is a simple linear fusion process between the raw images and the HFEF ones. It is shown that the proposed approach increases the verification and identification of the fingerprint biometric recognition system, where any improvement is justified using the correlation performance metrics of the matching algorithm.
Visualization of endosome dynamics in living nerve terminals with four-dimensional fluorescence imaging.

PubMed

Stewart, Richard S; Kiss, Ilona M; Wilkinson, Robert S

2014-04-16

Four-dimensional (4D) light imaging has been used to study behavior of small structures within motor nerve terminals of the thin transversus abdominis muscle of the garter snake. Raw data comprises time-lapse sequences of 3D z-stacks. Each stack contains 4-20 images acquired with epifluorescence optics at focal planes separated by 400-1,500 nm. Steps in the acquisition of image stacks, such as adjustment of focus, switching of excitation wavelengths, and operation of the digital camera, are automated as much as possible to maximize image rate and minimize tissue damage from light exposure. After acquisition, a set of image stacks is deconvolved to improve spatial resolution, converted to the desired 3D format, and used to create a 4D "movie" that is suitable for variety of computer-based analyses, depending upon the experimental data sought. One application is study of the dynamic behavior of two classes of endosomes found in nerve terminals-macroendosomes (MEs) and acidic endosomes (AEs)-whose sizes (200-800 nm for both types) are at or near the diffraction limit. Access to 3D information at each time point provides several advantages over conventional time-lapse imaging. In particular, size and velocity of movement of structures can be quantified over time without loss of sharp focus. Examples of data from 4D imaging reveal that MEs approach the plasma membrane and disappear, suggesting that they are exocytosed rather than simply moving vertically away from a single plane of focus. Also revealed is putative fusion of MEs and AEs, by visualization of overlap between the two dye-containing structures as viewed in each three orthogonal projections.
Noise temperature improvement for magnetic fusion plasma millimeter wave imaging systems.

PubMed

Lai, J; Domier, C W; Luhmann, N C

2014-03-01

Significant progress has been made in the imaging and visualization of magnetohydrodynamic and microturbulence phenomena in magnetic fusion plasmas [B. Tobias et al., Plasma Fusion Res. 6, 2106042 (2011)]. Of particular importance have been microwave electron cyclotron emission imaging and microwave imaging reflectometry systems for imaging T(e) and n(e) fluctuations. These instruments have employed heterodyne receiver arrays with Schottky diode mixer elements directly connected to individual antennas. Consequently, the noise temperature has been strongly determined by the conversion loss with typical noise temperatures of ~60,000 K. However, this can be significantly improved by making use of recent advances in Monolithic Microwave Integrated Circuit chip low noise amplifiers to insert a pre-amplifier in front of the Schottky diode mixer element. In a proof-of-principle design at V-Band (50-75 GHz), significant improvement of noise temperature from the current 60,000 K to measured 4000 K has been obtained.

Preoperative magnetic resonance and intraoperative ultrasound fusion imaging for real-time neuronavigation in brain tumor surgery.

PubMed

Prada, F; Del Bene, M; Mattei, L; Lodigiani, L; DeBeni, S; Kolev, V; Vetrano, I; Solbiati, L; Sakas, G; DiMeco, F

2015-04-01

Brain shift and tissue deformation during surgery for intracranial lesions are the main actual limitations of neuro-navigation (NN), which currently relies mainly on preoperative imaging. Ultrasound (US), being a real-time imaging modality, is becoming progressively more widespread during neurosurgical procedures, but most neurosurgeons, trained on axial computed tomography (CT) and magnetic resonance imaging (MRI) slices, lack specific US training and have difficulties recognizing anatomic structures with the same confidence as in preoperative imaging. Therefore real-time intraoperative fusion imaging (FI) between preoperative imaging and intraoperative ultrasound (ioUS) for virtual navigation (VN) is highly desirable. We describe our procedure for real-time navigation during surgery for different cerebral lesions. We performed fusion imaging with virtual navigation for patients undergoing surgery for brain lesion removal using an ultrasound-based real-time neuro-navigation system that fuses intraoperative cerebral ultrasound with preoperative MRI and simultaneously displays an MRI slice coplanar to an ioUS image. 58 patients underwent surgery at our institution for intracranial lesion removal with image guidance using a US system equipped with fusion imaging for neuro-navigation. In all cases the initial (external) registration error obtained by the corresponding anatomical landmark procedure was below 2 mm and the craniotomy was correctly placed. The transdural window gave satisfactory US image quality and the lesion was always detectable and measurable on both axes. Brain shift/deformation correction has been successfully employed in 42 cases to restore the co-registration during surgery. The accuracy of ioUS/MRI fusion/overlapping was confirmed intraoperatively under direct visualization of anatomic landmarks and the error was < 3 mm in all cases (100 %). Neuro-navigation using intraoperative US integrated with preoperative MRI is reliable, accurate and user-friendly. Moreover, the adjustments are very helpful in correcting brain shift and tissue distortion. This integrated system allows true real-time feedback during surgery and is less expensive and time-consuming than other intraoperative imaging techniques, offering high precision and orientation. © Georg Thieme Verlag KG Stuttgart · New York.
Spectral CT imaging in patients with Budd-Chiari syndrome: investigation of image quality.

PubMed

Su, Lei; Dong, Junqiang; Sun, Qiang; Liu, Jie; Lv, Peijie; Hu, Lili; Yan, Liangliang; Gao, Jianbo

2014-11-01

To assess the image quality of monochromatic imaging from spectral CT in patients with Budd-Chiari syndrome (BCS), fifty patients with BCS underwent spectral CT to generate conventional 140 kVp polychromatic images (group A) and monochromatic images, with energy levels from 40 to 80, 40 + 70, and 50 + 70 keV fusion images (group B) during the portal venous phase (PVP) and the hepatic venous phase (HVP). Two-sample t tests compared vessel-to-liver contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) for the portal vein (PV), hepatic vein (HV), inferior vena cava. Readers' subjective evaluations of the image quality were recorded. The highest SNR values in group B were distributed at 50 keV; the highest CNR values in group B were distributed at 40 keV. The higher CNR values and SNR values were obtained though PVP of PV (SNR 18.39 ± 6.13 vs. 10.56 ± 3.31, CNR 7.81 ± 3.40 vs. 3.58 ± 1.31) and HVP of HV (3.89 ± 2.08 vs. 1.27 ± 1.55) in the group B; the lower image noise for group B was at 70 keV and 50 + 70 keV (15.54 ± 8.39 vs. 18.40 ± 4.97, P = 0.0004 and 18.97 ± 7.61 vs. 18.40 ± 4.97, P = 0.0691); the results show that the 50 + 70 keV fusion image quality was better than that in group A. Monochromatic energy levels of 40-70, 40 + 70, and 50 + 70 keV fusion image can increase vascular contrast and that will be helpful for the diagnosis of BCS, we select the 50 + 70 keV fusion image to acquire the best BCS images.
The 3D Recognition, Generation, Fusion, Update and Refinement (RG4) Concept

NASA Technical Reports Server (NTRS)

Maluf, David A.; Cheeseman, Peter; Smelyanskyi, Vadim N.; Kuehnel, Frank; Morris, Robin D.; Norvig, Peter (Technical Monitor)

2001-01-01

This paper describes an active (real time) recognition strategy whereby information is inferred iteratively across several viewpoints in descent imagery. We will show how we use inverse theory within the context of parametric model generation, namely height and spectral reflection functions, to generate model assertions. Using this strategy in an active context implies that, from every viewpoint, the proposed system must refine its hypotheses taking into account the image and the effect of uncertainties as well. The proposed system employs probabilistic solutions to the problem of iteratively merging information (images) from several viewpoints. This involves feeding the posterior distribution from all previous images as a prior for the next view. Novel approaches will be developed to accelerate the inversion search using novel statistic implementations and reducing the model complexity using foveated vision. Foveated vision refers to imagery where the resolution varies across the image. In this paper, we allow the model to be foveated where the highest resolution region is called the foveation region. Typically, the images will have dynamic control of the location of the foveation region. For descent imagery in the Entry, Descent, and Landing (EDL) process, it is possible to have more than one foveation region. This research initiative is directed towards descent imagery in connection with NASA's EDL applications. Three-Dimensional Model Recognition, Generation, Fusion, Update, and Refinement (RGFUR or RG4) for height and the spectral reflection characteristics are in focus for various reasons, one of which is the prospect that their interpretation will provide for real time active vision for automated EDL.
Novel System for Real-Time Integration of 3-D Echocardiography and Fluoroscopy for Image-Guided Cardiac Interventions: Preclinical Validation and Clinical Feasibility Evaluation.

PubMed

Arujuna, Aruna V; Housden, R James; Ma, Yingliang; Rajani, Ronak; Gao, Gang; Nijhof, Niels; Cathier, Pascal; Bullens, Roland; Gijsbers, Geert; Parish, Victoria; Kapetanakis, Stamatis; Hancock, Jane; Rinaldi, C Aldo; Cooklin, Michael; Gill, Jaswinder; Thomas, Martyn; O'neill, Mark D; Razavi, Reza; Rhode, Kawal S

2014-01-01

Real-time imaging is required to guide minimally invasive catheter-based cardiac interventions. While transesophageal echocardiography allows for high-quality visualization of cardiac anatomy, X-ray fluoroscopy provides excellent visualization of devices. We have developed a novel image fusion system that allows real-time integration of 3-D echocardiography and the X-ray fluoroscopy. The system was validated in the following two stages: 1) preclinical to determine function and validate accuracy; and 2) in the clinical setting to assess clinical workflow feasibility and determine overall system accuracy. In the preclinical phase, the system was assessed using both phantom and porcine experimental studies. Median 2-D projection errors of 4.5 and 3.3 mm were found for the phantom and porcine studies, respectively. The clinical phase focused on extending the use of the system to interventions in patients undergoing either atrial fibrillation catheter ablation (CA) or transcatheter aortic valve implantation (TAVI). Eleven patients were studied with nine in the CA group and two in the TAVI group. Successful real-time view synchronization was achieved in all cases with a calculated median distance error of 2.2 mm in the CA group and 3.4 mm in the TAVI group. A standard clinical workflow was established using the image fusion system. These pilot data confirm the technical feasibility of accurate real-time echo-fluoroscopic image overlay in clinical practice, which may be a useful adjunct for real-time guidance during interventional cardiac procedures.
Group-sparse representation with dictionary learning for medical image denoising and fusion.

PubMed

Li, Shutao; Yin, Haitao; Fang, Leyuan

2012-12-01

Recently, sparse representation has attracted a lot of interest in various areas. However, the standard sparse representation does not consider the intrinsic structure, i.e., the nonzero elements occur in clusters, called group sparsity. Furthermore, there is no dictionary learning method for group sparse representation considering the geometrical structure of space spanned by atoms. In this paper, we propose a novel dictionary learning method, called Dictionary Learning with Group Sparsity and Graph Regularization (DL-GSGR). First, the geometrical structure of atoms is modeled as the graph regularization. Then, combining group sparsity and graph regularization, the DL-GSGR is presented, which is solved by alternating the group sparse coding and dictionary updating. In this way, the group coherence of learned dictionary can be enforced small enough such that any signal can be group sparse coded effectively. Finally, group sparse representation with DL-GSGR is applied to 3-D medical image denoising and image fusion. Specifically, in 3-D medical image denoising, a 3-D processing mechanism (using the similarity among nearby slices) and temporal regularization (to perverse the correlations across nearby slices) are exploited. The experimental results on 3-D image denoising and image fusion demonstrate the superiority of our proposed denoising and fusion approaches.
Turning eating psychopathology risk factors into action. The pervasive effect of body image-related cognitive fusion.

PubMed

Ferreira, Cláudia; Palmeira, Lara; Trindade, Inês A

2014-09-01

Body image dissatisfaction and unfavourable social comparisons are significant risk factors to eating psychopathology. Nevertheless, the impact of these negative experiences depends on the cognitive and emotional processes involved. Previous research has shown that cognitive fusion is a nuclear process linked to psychological inflexibility, but its role on body image and eating difficulties remains unclear. This study aims to explore a model of the mediational role of body image-related cognitive fusion (CF-BI) on the relationship between body dissatisfaction, unfavourable social comparisons, and eating psychopathology in a sample of 345 female students. Results from path analyses show that the impact of unfavourable social comparisons on eating psychopathology is fully mediated by CF-BI. Moreover, CF-BI also revealed a mediational effect on the relationship between body image dissatisfaction and the severity of eating symptoms, in spite of the fact that a direct effect of body dissatisfaction still exists. The tested model highlights the crucial role that cognitive fusion, in the specific domain of body image, plays in the relationship between risk factors and the severity of disordered eating attitudes and behaviours. Furthermore, these findings present empirical support for the relevance of addressing acceptance and cognitive defusion techniques to prevent and treat eating disorders. Copyright © 2014 Elsevier Ltd. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Y.; Tobias, B.; Chang, Y. -T.

Electron cyclotron emission (ECE) imaging is a passive radiometric technique that measures electron temperature fluctuations; and microwave imaging reflectometry (MIR) is an active radar imaging technique that measures electron density fluctuations. The microwave imaging diagnostic instruments employing these techniques have made important contributions to fusion science and have been adopted at major fusion facilities worldwide including DIII-D, EAST, ASDEX Upgrade, HL-2A, KSTAR, LHD, and J-TEXT. In this paper, we describe the development status of three major technological advancements: custom mm-wave integrated circuits (ICs), digital beamforming (DBF), and synthetic diagnostic modeling (SDM). These also have the potential to greatly advance microwavemore » fusion plasma imaging, enabling compact and low-noise transceiver systems with real-time, fast tracking ability to address critical fusion physics issues, including ELM suppression and disruptions in the ITER baseline scenario, naturally ELM-free states such as QH-mode, and energetic particle confinement (i.e. Alfven eigenmode stability) in high-performance regimes that include steady-state and advanced tokamak scenarios. Furthermore, these systems are fully compatible with today's most challenging non-inductive heating and current drive systems and capable of operating in harsh environments, making them the ideal approach for diagnosing long-pulse and steady-state tokamaks.« less
Multifocus watermarking approach based on discrete cosine transform.

PubMed

Waheed, Safa Riyadh; Alkawaz, Mohammed Hazim; Rehman, Amjad; Almazyad, Abdulaziz S; Saba, Tanzila

2016-05-01

Image fusion process consolidates data and information from various images of same sight into a solitary image. Each of the source images might speak to a fractional perspective of the scene, and contains both "pertinent" and "immaterial" information. In this study, a new image fusion method is proposed utilizing the Discrete Cosine Transform (DCT) to join the source image into a solitary minimized image containing more exact depiction of the sight than any of the individual source images. In addition, the fused image comes out with most ideal quality image without bending appearance or loss of data. DCT algorithm is considered efficient in image fusion. The proposed scheme is performed in five steps: (1) RGB colour image (input image) is split into three channels R, G, and B for source images. (2) DCT algorithm is applied to each channel (R, G, and B). (3) The variance values are computed for the corresponding 8 × 8 blocks of each channel. (4) Each block of R of source images is compared with each other based on the variance value and then the block with maximum variance value is selected to be the block in the new image. This process is repeated for all channels of source images. (5) Inverse discrete cosine transform is applied on each fused channel to convert coefficient values to pixel values, and then combined all the channels to generate the fused image. The proposed technique can potentially solve the problem of unwanted side effects such as blurring or blocking artifacts by reducing the quality of the subsequent image in image fusion process. The proposed approach is evaluated using three measurement units: the average of Q(abf), standard deviation, and peak Signal Noise Rate. The experimental results of this proposed technique have shown good results as compared with older techniques. © 2016 Wiley Periodicals, Inc.
The fusion of large scale classified side-scan sonar image mosaics.

PubMed

Reed, Scott; Tena, Ruiz Ioseba; Capus, Chris; Petillot, Yvan

2006-07-01

This paper presents a unified framework for the creation of classified maps of the seafloor from sonar imagery. Significant challenges in photometric correction, classification, navigation and registration, and image fusion are addressed. The techniques described are directly applicable to a range of remote sensing problems. Recent advances in side-scan data correction are incorporated to compensate for the sonar beam pattern and motion of the acquisition platform. The corrected images are segmented using pixel-based textural features and standard classifiers. In parallel, the navigation of the sonar device is processed using Kalman filtering techniques. A simultaneous localization and mapping framework is adopted to improve the navigation accuracy and produce georeferenced mosaics of the segmented side-scan data. These are fused within a Markovian framework and two fusion models are presented. The first uses a voting scheme regularized by an isotropic Markov random field and is applicable when the reliability of each information source is unknown. The Markov model is also used to inpaint regions where no final classification decision can be reached using pixel level fusion. The second model formally introduces the reliability of each information source into a probabilistic model. Evaluation of the two models using both synthetic images and real data from a large scale survey shows significant quantitative and qualitative improvement using the fusion approach.
Formulation of image fusion as a constrained least squares optimization problem

PubMed Central

Dwork, Nicholas; Lasry, Eric M.; Pauly, John M.; Balbás, Jorge

2017-01-01

Abstract. Fusing a lower resolution color image with a higher resolution monochrome image is a common practice in medical imaging. By incorporating spatial context and/or improving the signal-to-noise ratio, it provides clinicians with a single frame of the most complete information for diagnosis. In this paper, image fusion is formulated as a convex optimization problem that avoids image decomposition and permits operations at the pixel level. This results in a highly efficient and embarrassingly parallelizable algorithm based on widely available robust and simple numerical methods that realizes the fused image as the global minimizer of the convex optimization problem. PMID:28331885
A prospective comparison between auto-registration and manual registration of real-time ultrasound with MR images for percutaneous ablation or biopsy of hepatic lesions.

PubMed

Cha, Dong Ik; Lee, Min Woo; Song, Kyoung Doo; Oh, Young-Taek; Jeong, Ja-Yeon; Chang, Jung-Woo; Ryu, Jiwon; Lee, Kyong Joon; Kim, Jaeil; Bang, Won-Chul; Shin, Dong Kuk; Choi, Sung Jin; Koh, Dalkwon; Seo, Bong Koo; Kim, Kyunga

2017-06-01

To compare the accuracy and required time for image fusion of real-time ultrasound (US) with pre-procedural magnetic resonance (MR) images between positioning auto-registration and manual registration for percutaneous radiofrequency ablation or biopsy of hepatic lesions. This prospective study was approved by the institutional review board, and all patients gave written informed consent. Twenty-two patients (male/female, n = 18/n = 4; age, 61.0 ± 7.7 years) who were referred for planning US to assess the feasibility of radiofrequency ablation (n = 21) or biopsy (n = 1) for focal hepatic lesions were included. One experienced radiologist performed the two types of image fusion methods in each patient. The performance of auto-registration and manual registration was evaluated. The accuracy of the two methods, based on measuring registration error, and the time required for image fusion for both methods were recorded using in-house software and respectively compared using the Wilcoxon signed rank test. Image fusion was successful in all patients. The registration error was not significantly different between the two methods (auto-registration: median, 3.75 mm; range, 1.0-15.8 mm vs. manual registration: median, 2.95 mm; range, 1.2-12.5 mm, p = 0.242). The time required for image fusion was significantly shorter with auto-registration than with manual registration (median, 28.5 s; range, 18-47 s, vs. median, 36.5 s; range, 14-105 s, p = 0.026). Positioning auto-registration showed promising results compared with manual registration, with similar accuracy and even shorter registration time.
Introduction to Nuclear Fusion Power and the Design of Fusion Reactors. An Issue-Oriented Module.

ERIC Educational Resources Information Center

Fillo, J. A.

This three-part module focuses on the principles of nuclear fusion and on the likely nature and components of a controlled-fusion power reactor. The physical conditions for a net energy release from fusion and two approaches (magnetic and inertial confinement) which are being developed to achieve this goal are described. Safety issues associated…
Conceptual design study of Fusion Experimental Reactor (FY86 FER): Safety

NASA Astrophysics Data System (ADS)

Seki, Yasushi; Iida, Hiromasa; Honda, Tsutomu

1987-08-01

This report describes the study on safety for FER (Fusion Experimental Reactor) which has been designed as a next step machine to the JT-60. Though the final purpose of this study is to have an image of design base accident, maximum credible accident and to assess their risk or probability, etc., as FER plant system, the emphasis of this years study is placed on fuel-gas circulation system where the tritium inventory is maximum. The report consists of two chapters. The first chapter summarizes the FER system and describes FMEA (Failure Mode and Effect Analysis) and related accident progression sequence for FER plant system as a whole. The second chapter of this report is focused on fuel-gas circulation system including purification, isotope separation and storage. Probability of risk is assessed by the probabilistic risk analysis (PRA) procedure based on FMEA, ETA and FTA.
Caught in the struggle with food craving: Development and validation of a new cognitive fusion measure.

PubMed

Duarte, Cristiana; Pinto-Gouveia, José; Ferreira, Cláudia; Silva, Bárbara

2016-06-01

Cognitive fusion has been related to the development and maintenance of a series of mental health difficulties. Specifically, growing research on eating psychopathology has been demonstrating the important role of cognitive fusion related to body image in these disorders. Nonetheless, cognitive fusion specifically focused on eating remained to be investigated. The current study aimed at developing and validating the Cognitive Fusion Questionnaire-Food Craving, a measure assessing the extent to which an individual is fused with food-craving undesirable and disturbing thoughts and urges. This study was conducted with distinct samples comprising men and women from the student and general population. A principal component analysis was conducted to assess the scale's structure, which was further examined in a confirmatory factor analysis. The scale's reliability and validities were also analysed. Results indicated that the CFQ-FC presented a one-dimensional structure with 7 items, accounting for 66.14% of the variance. A CFA confirmed the plausibility of the measurement model, which was found to be invariant in both sexes. The CFQ-FC also revealed very good internal consistency, construct reliability, temporal stability, and convergent and divergent validity, being positively associated with similar constructs and with indicators of eating and general psychopathology. CFQ-FC also discriminated individuals with clinically significant symptoms of binge eating from participants with no symptoms. Finally, the CFQ-FC presents incremental validity over a global measure of cognitive fusion in predicting eating psychopathology, namely binge eating. The CFQ-FC is a psychometrically sound measure that allows for a brief and reliable assessment of eating-related cognitive fusion. This is a novel measure that may significantly contribute for the assessment of this specific dimension of cognitive fusion and for the understanding of its role in eating psychopathology. Copyright © 2016 Elsevier Ltd. All rights reserved.
An acceleration system for Laplacian image fusion based on SoC

NASA Astrophysics Data System (ADS)

Gao, Liwen; Zhao, Hongtu; Qu, Xiujie; Wei, Tianbo; Du, Peng

2018-04-01

Based on the analysis of Laplacian image fusion algorithm, this paper proposes a partial pipelining and modular processing architecture, and a SoC based acceleration system is implemented accordingly. Full pipelining method is used for the design of each module, and modules in series form the partial pipelining with unified data formation, which is easy for management and reuse. Integrated with ARM processor, DMA and embedded bare-mental program, this system achieves 4 layers of Laplacian pyramid on the Zynq-7000 board. Experiments show that, with small resources consumption, a couple of 256×256 images can be fused within 1ms, maintaining a fine fusion effect at the same time.
A joint FED watermarking system using spatial fusion for verifying the security issues of teleradiology.

PubMed

Viswanathan, P; Krishna, P Venkata

2014-05-01

Teleradiology allows transmission of medical images for clinical data interpretation to provide improved e-health care access, delivery, and standards. The remote transmission raises various ethical and legal issues like image retention, fraud, privacy, malpractice liability, etc. A joint FED watermarking system means a joint fingerprint/encryption/dual watermarking system is proposed for addressing these issues. The system combines a region based substitution dual watermarking algorithm using spatial fusion, stream cipher algorithm using symmetric key, and fingerprint verification algorithm using invariants. This paper aims to give access to the outcomes of medical images with confidentiality, availability, integrity, and its origin. The watermarking, encryption, and fingerprint enrollment are conducted jointly in protection stage such that the extraction, decryption, and verification can be applied independently. The dual watermarking system, introducing two different embedding schemes, one used for patient data and other for fingerprint features, reduces the difficulty in maintenance of multiple documents like authentication data, personnel and diagnosis data, and medical images. The spatial fusion algorithm, which determines the region of embedding using threshold from the image to embed the encrypted patient data, follows the exact rules of fusion resulting in better quality than other fusion techniques. The four step stream cipher algorithm using symmetric key for encrypting the patient data with fingerprint verification system using algebraic invariants improves the robustness of the medical information. The experiment result of proposed scheme is evaluated for security and quality analysis in DICOM medical images resulted well in terms of attacks, quality index, and imperceptibility.
Usefulness of Single Photon Emission Computed Tomography/Computed Tomography Fusion-Hybrid Imaging to Evaluate Coronary Artery Disorders in Patients with a History of Kawasaki Disease.

PubMed

Abe, Masanori; Fukazawa, Ryuji; Ogawa, Shunichi; Watanabe, Makoto; Fukushima, Yoshimitsu; Kiriyama, Tomonari; Hayashi, Hiromitsu; Itoh, Yasuhiko

2016-01-01

The coronary arterial lesions of Kawasaki disease are mainly dilative lesions, aneurysms, and stenotic lesions formed before, after, and between aneurysms; these lesions develop in multiple branches resulting in complex coronary hemodynamics. Diagnosis of myocardial ischemia and infarction and evaluation of the culprit coronary arteries and regions is critical to evaluating the treatment and prognosis of patients. This study used hybrid imaging, in which multidetector computed tomographic (CT) images for coronary CT angiography (CCTA) and stress myocardial perfusion single-photon emission CT (SPECT) images were fused. We investigated the diagnosis of blood vessels and regions responsible for myocardial ischemia and infarction in patients with complex coronary arterial lesions; in addition, we evaluated myocardial lesions that developed directly under giant coronary artery aneurysms. The subjects were 17 patients with Kawasaki disease with multiple coronary arterial lesions (median age, 18.0 years; 16 male). Both CCTA using 64-row CT and adenosine-loading myocardial SPECT were performed. Three branches, the right coronary artery (RCA), left anterior descending branch (LAD), and left circumflex branch, were evaluated with the conventional side-by-side interpretation, in which the images were lined up for diagnosis, and hybrid imaging, in which the CCTA and SPECT images were fused with computer processing. In addition, the myocardial lesions directly under giant coronary artery aneurysms were investigated with fusion imaging. Images sufficient for evaluation were acquired in all 17 patients. In the RCA, coronary arterial lesions were detected with CCTA in 16 patients. The evaluations were consistent between the side-by-side and fusion interpretation in 14 patients, and the blood vessel responsible for the myocardial ischemic region was identified in 2 patients. In the left circumflex branch, coronary arterial lesions were confirmed with 3-dimensional CT in 5 patients, and the the culprit coronary arteries for myocardial ischemia/infarction were confirmed with the fusion interpretation but not with the side-by-side interpretation. In the LAD, coronary arterial lesions were present in all patients, and the diagnosis was made with the fusion interpretation in 10 patients. In the LAD, small-range infarct lesions were detected directly under the giant coronary artery aneurysm in 8 patients, but were not confirmed with the side-by-side interpretation. Fusion imaging was capable of accurately evaluating myocardial ischemia/infarction as cardiovascular sequelae of Kawasaki disease and confirming the culprit coronary arteries. In addition, analysis of fusion images confirmed that small-range infarct lesions were concomitantly present directly under giant coronary artery aneurysms in the anterior descending coronary artery.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Krishnan, Kalpagam; Liu, Jeff; Kohli, Kirpal

Purpose: Fusion of electrical impedance tomography (EIT) with computed tomography (CT) can be useful as a clinical tool for providing additional physiological information about tissues, but requires suitable fusion algorithms and validation procedures. This work explores the feasibility of fusing EIT and CT images using an algorithm for coregistration. The imaging performance is validated through feature space assessment on phantom contrast targets. Methods: EIT data were acquired by scanning a phantom using a circuit, configured for injecting current through 16 electrodes, placed around the phantom. A conductivity image of the phantom was obtained from the data using electrical impedance andmore » diffuse optical tomography reconstruction software (EIDORS). A CT image of the phantom was also acquired. The EIT and CT images were fused using a region of interest (ROI) coregistration fusion algorithm. Phantom imaging experiments were carried out on objects of different contrasts, sizes, and positions. The conductive medium of the phantoms was made of a tissue-mimicking bolus material that is routinely used in clinical radiation therapy settings. To validate the imaging performance in detecting different contrasts, the ROI of the phantom was filled with distilled water and normal saline. Spatially separated cylindrical objects of different sizes were used for validating the imaging performance in multiple target detection. Analyses of the CT, EIT and the EIT/CT phantom images were carried out based on the variations of contrast, correlation, energy, and homogeneity, using a gray level co-occurrence matrix (GLCM). A reference image of the phantom was simulated using EIDORS, and the performances of the CT and EIT imaging systems were evaluated and compared against the performance of the EIT/CT system using various feature metrics, detectability, and structural similarity index measures. Results: In detecting distilled and normal saline water in bolus medium, EIT as a stand-alone imaging system showed contrast discrimination of 47%, while the CT imaging system showed a discrimination of only 1.5%. The structural similarity index measure showed a drop of 24% with EIT imaging compared to CT imaging. The average detectability measure for CT imaging was found to be 2.375 ± 0.19 before fusion. After complementing with EIT information, the detectability measure increased to 11.06 ± 2.04. Based on the feature metrics, the functional imaging quality of CT and EIT were found to be 2.29% and 86%, respectively, before fusion. Structural imaging quality was found to be 66% for CT and 16% for EIT. After fusion, functional imaging quality improved in CT imaging from 2.29% to 42% and the structural imaging quality of EIT imaging changed from 16% to 66%. The improvement in image quality was also observed in detecting objects of different sizes. Conclusions: The authors found a significant improvement in the contrast detectability performance of CT imaging when complemented with functional imaging information from EIT. Along with the feature assessment metrics, the concept of complementing CT with EIT imaging can lead to an EIT/CT imaging modality which might fully utilize the functional imaging abilities of EIT imaging, thereby enhancing the quality of care in the areas of cancer diagnosis and radiotherapy treatment planning.« less
Sensor fusion V; Proceedings of the Meeting, Boston, MA, Nov. 15-17, 1992

NASA Technical Reports Server (NTRS)

Schenker, Paul S. (Editor)

1992-01-01

Topics addressed include 3D object perception, human-machine interface in multisensor systems, sensor fusion architecture, fusion of multiple and distributed sensors, interface and decision models for sensor fusion, computational networks, simple sensing for complex action, multisensor-based control, and metrology and calibration of multisensor systems. Particular attention is given to controlling 3D objects by sketching 2D views, the graphical simulation and animation environment for flexible structure robots, designing robotic systems from sensorimotor modules, cylindrical object reconstruction from a sequence of images, an accurate estimation of surface properties by integrating information using Bayesian networks, an adaptive fusion model for a distributed detection system, multiple concurrent object descriptions in support of autonomous navigation, robot control with multiple sensors and heuristic knowledge, and optical array detectors for image sensors calibration. (No individual items are abstracted in this volume)
Generating description with multi-feature fusion and saliency maps of image

NASA Astrophysics Data System (ADS)

Liu, Lisha; Ding, Yuxuan; Tian, Chunna; Yuan, Bo

2018-04-01

Generating description for an image can be regard as visual understanding. It is across artificial intelligence, machine learning, natural language processing and many other areas. In this paper, we present a model that generates description for images based on RNN (recurrent neural network) with object attention and multi-feature of images. The deep recurrent neural networks have excellent performance in machine translation, so we use it to generate natural sentence description for images. The proposed method uses single CNN (convolution neural network) that is trained on ImageNet to extract image features. But we think it can not adequately contain the content in images, it may only focus on the object area of image. So we add scene information to image feature using CNN which is trained on Places205. Experiments show that model with multi-feature extracted by two CNNs perform better than which with a single feature. In addition, we make saliency weights on images to emphasize the salient objects in images. We evaluate our model on MSCOCO based on public metrics, and the results show that our model performs better than several state-of-the-art methods.

Some links on this page may take you to non-federal websites. Their policies may differ from this site.