Enhancement method for rendered images of home decoration based on SLIC superpixels

NASA Astrophysics Data System (ADS)

Dai, Yutong; Jiang, Xiaotong

2018-04-01

Rendering technology has been widely used in the home decoration industry in recent years for images of home decoration design. However, due to the fact that rendered images of home decoration design rely heavily on the parameters of renderer and the lights of scenes, most rendered images in this industry require further optimization afterwards. To reduce workload and enhance rendered images automatically, an algorithm utilizing neural networks is proposed in this manuscript. In addition, considering few extreme conditions such as strong sunlight and lights, SLIC superpixels based segmentation is used to choose out these bright areas of an image and enhance them independently. Finally, these chosen areas are merged with the entire image. Experimental results show that the proposed method effectively enhances the rendered images when compared with some existing algorithms. Besides, the proposed strategy is proven to be adaptable especially to those images with obvious bright parts.

Visual performance-based image enhancement methodology: an investigation of contrast enhancement algorithms

NASA Astrophysics Data System (ADS)

Neriani, Kelly E.; Herbranson, Travis J.; Reis, George A.; Pinkus, Alan R.; Goodyear, Charles D.

2006-05-01

While vast numbers of image enhancing algorithms have already been developed, the majority of these algorithms have not been assessed in terms of their visual performance-enhancing effects using militarily relevant scenarios. The goal of this research was to apply a visual performance-based assessment methodology to evaluate six algorithms that were specifically designed to enhance the contrast of digital images. The image enhancing algorithms used in this study included three different histogram equalization algorithms, the Autolevels function, the Recursive Rational Filter technique described in Marsi, Ramponi, and Carrato1 and the multiscale Retinex algorithm described in Rahman, Jobson and Woodell2. The methodology used in the assessment has been developed to acquire objective human visual performance data as a means of evaluating the contrast enhancement algorithms. Objective performance metrics, response time and error rate, were used to compare algorithm enhanced images versus two baseline conditions, original non-enhanced images and contrast-degraded images. Observers completed a visual search task using a spatial-forcedchoice paradigm. Observers searched images for a target (a military vehicle) hidden among foliage and then indicated in which quadrant of the screen the target was located. Response time and percent correct were measured for each observer. Results of the study and future directions are discussed.

Enhancement of brain tumor MR images based on intuitionistic fuzzy sets

NASA Astrophysics Data System (ADS)

Deng, Wankai; Deng, He; Cheng, Lifang

2015-12-01

Brain tumor is one of the most fatal cancers, especially high-grade gliomas are among the most deadly. However, brain tumor MR images usually have the disadvantages of low resolution and contrast when compared with the optical images. Consequently, we present a novel adaptive intuitionistic fuzzy enhancement scheme by combining a nonlinear fuzzy filtering operation with fusion operators, for the enhancement of brain tumor MR images in this paper. The presented scheme consists of the following six steps: Firstly, the image is divided into several sub-images. Secondly, for each sub-image, object and background areas are separated by a simple threshold. Thirdly, respective intuitionistic fuzzy generators of object and background areas are constructed based on the modified restricted equivalence function. Fourthly, different suitable operations are performed on respective membership functions of object and background areas. Fifthly, the membership plane is inversely transformed into the image plane. Finally, an enhanced image is obtained through fusion operators. The comparison and evaluation of enhancement performance demonstrate that the presented scheme is helpful to determine the abnormal functional areas, guide the operation, judge the prognosis, and plan the radiotherapy by enhancing the fine detail of MR images.

Large depth of focus dynamic micro integral imaging for optical see-through augmented reality display using a focus-tunable lens.

PubMed

Shen, Xin; Javidi, Bahram

2018-03-01

We have developed a three-dimensional (3D) dynamic integral-imaging (InIm)-system-based optical see-through augmented reality display with enhanced depth range of a 3D augmented image. A focus-tunable lens is adopted in the 3D display unit to relay the elemental images with various positions to the micro lens array. Based on resolution priority integral imaging, multiple lenslet image planes are generated to enhance the depth range of the 3D image. The depth range is further increased by utilizing both the real and virtual 3D imaging fields. The 3D reconstructed image and the real-world scene are overlaid using an optical see-through display for augmented reality. The proposed system can significantly enhance the depth range of a 3D reconstructed image with high image quality in the micro InIm unit. This approach provides enhanced functionality for augmented information and adjusts the vergence-accommodation conflict of a traditional augmented reality display.

Multi-sparse dictionary colorization algorithm based on the feature classification and detail enhancement

NASA Astrophysics Data System (ADS)

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

2018-02-01

For the problems of missing details and performance of the colorization based on sparse representation, we propose a conceptual model framework for colorizing gray-scale images, and then a multi-sparse dictionary colorization algorithm based on the feature classification and detail enhancement (CEMDC) is proposed based on this framework. The algorithm can achieve a natural colorized effect for a gray-scale image, and it is consistent with the human vision. First, the algorithm establishes a multi-sparse dictionary classification colorization model. Then, to improve the accuracy rate of the classification, the corresponding local constraint algorithm is proposed. Finally, we propose a detail enhancement based on Laplacian Pyramid, which is effective in solving the problem of missing details and improving the speed of image colorization. In addition, the algorithm not only realizes the colorization of the visual gray-scale image, but also can be applied to the other areas, such as color transfer between color images, colorizing gray fusion images, and infrared images.

Feature and contrast enhancement of mammographic image based on multiscale analysis and morphology.

PubMed

Wu, Shibin; Yu, Shaode; Yang, Yuhan; Xie, Yaoqin

2013-01-01

A new algorithm for feature and contrast enhancement of mammographic images is proposed in this paper. The approach bases on multiscale transform and mathematical morphology. First of all, the Laplacian Gaussian pyramid operator is applied to transform the mammography into different scale subband images. In addition, the detail or high frequency subimages are equalized by contrast limited adaptive histogram equalization (CLAHE) and low-pass subimages are processed by mathematical morphology. Finally, the enhanced image of feature and contrast is reconstructed from the Laplacian Gaussian pyramid coefficients modified at one or more levels by contrast limited adaptive histogram equalization and mathematical morphology, respectively. The enhanced image is processed by global nonlinear operator. The experimental results show that the presented algorithm is effective for feature and contrast enhancement of mammogram. The performance evaluation of the proposed algorithm is measured by contrast evaluation criterion for image, signal-noise-ratio (SNR), and contrast improvement index (CII).

Feature and Contrast Enhancement of Mammographic Image Based on Multiscale Analysis and Morphology

PubMed Central

Wu, Shibin; Xie, Yaoqin

2013-01-01

A new algorithm for feature and contrast enhancement of mammographic images is proposed in this paper. The approach bases on multiscale transform and mathematical morphology. First of all, the Laplacian Gaussian pyramid operator is applied to transform the mammography into different scale subband images. In addition, the detail or high frequency subimages are equalized by contrast limited adaptive histogram equalization (CLAHE) and low-pass subimages are processed by mathematical morphology. Finally, the enhanced image of feature and contrast is reconstructed from the Laplacian Gaussian pyramid coefficients modified at one or more levels by contrast limited adaptive histogram equalization and mathematical morphology, respectively. The enhanced image is processed by global nonlinear operator. The experimental results show that the presented algorithm is effective for feature and contrast enhancement of mammogram. The performance evaluation of the proposed algorithm is measured by contrast evaluation criterion for image, signal-noise-ratio (SNR), and contrast improvement index (CII). PMID:24416072

Probabilistic retinal vessel segmentation

NASA Astrophysics Data System (ADS)

Wu, Chang-Hua; Agam, Gady

2007-03-01

Optic fundus assessment is widely used for diagnosing vascular and non-vascular pathology. Inspection of the retinal vasculature may reveal hypertension, diabetes, arteriosclerosis, cardiovascular disease and stroke. Due to various imaging conditions retinal images may be degraded. Consequently, the enhancement of such images and vessels in them is an important task with direct clinical applications. We propose a novel technique for vessel enhancement in retinal images that is capable of enhancing vessel junctions in addition to linear vessel segments. This is an extension of vessel filters we have previously developed for vessel enhancement in thoracic CT scans. The proposed approach is based on probabilistic models which can discern vessels and junctions. Evaluation shows the proposed filter is better than several known techniques and is comparable to the state of the art when evaluated on a standard dataset. A ridge-based vessel tracking process is applied on the enhanced image to demonstrate the effectiveness of the enhancement filter.

An analytical optimization model for infrared image enhancement via local context

NASA Astrophysics Data System (ADS)

Xu, Yongjian; Liang, Kun; Xiong, Yiru; Wang, Hui

2017-12-01

The requirement for high-quality infrared images is constantly increasing in both military and civilian areas, and it is always associated with little distortion and appropriate contrast, while infrared images commonly have some shortcomings such as low contrast. In this paper, we propose a novel infrared image histogram enhancement algorithm based on local context. By constraining the enhanced image to have high local contrast, a regularized analytical optimization model is proposed to enhance infrared images. The local contrast is determined by evaluating whether two intensities are neighbors and calculating their differences. The comparison on 8-bit images shows that the proposed method can enhance the infrared images with more details and lower noise.

Advanced Image Enhancement Method for Distant Vessels and Structures in Capsule Endoscopy

PubMed Central

Pedersen, Marius

2017-01-01

This paper proposes an advanced method for contrast enhancement of capsule endoscopic images, with the main objective to obtain sufficient information about the vessels and structures in more distant (or darker) parts of capsule endoscopic images. The proposed method (PM) combines two algorithms for the enhancement of darker and brighter areas of capsule endoscopic images, respectively. The half-unit weighted-bilinear algorithm (HWB) proposed in our previous work is used to enhance darker areas according to the darker map content of its HSV's component V. Enhancement of brighter areas is achieved thanks to the novel threshold weighted-bilinear algorithm (TWB) developed to avoid overexposure and enlargement of specular highlight spots while preserving the hue, in such areas. The TWB performs enhancement operations following a gradual increment of the brightness of the brighter map content of its HSV's component V. In other words, the TWB decreases its averaged weights as the intensity content of the component V increases. Extensive experimental demonstrations were conducted, and, based on evaluation of the reference and PM enhanced images, a gastroenterologist (Ø.H.) concluded that the PM enhanced images were the best ones based on the information about the vessels, contrast in the images, and the view or visibility of the structures in more distant parts of the capsule endoscopy images. PMID:29225668

Half-unit weighted bilinear algorithm for image contrast enhancement in capsule endoscopy

NASA Astrophysics Data System (ADS)

Rukundo, Olivier

2018-04-01

This paper proposes a novel enhancement method based exclusively on the bilinear interpolation algorithm for capsule endoscopy images. The proposed method does not convert the original RBG image components to HSV or any other color space or model; instead, it processes directly RGB components. In each component, a group of four adjacent pixels and half-unit weight in the bilinear weighting function are used to calculate the average pixel value, identical for each pixel in that particular group. After calculations, groups of identical pixels are overlapped successively in horizontal and vertical directions to achieve a preliminary-enhanced image. The final-enhanced image is achieved by halving the sum of the original and preliminary-enhanced image pixels. Quantitative and qualitative experiments were conducted focusing on pairwise comparisons between original and enhanced images. Final-enhanced images have generally the best diagnostic quality and gave more details about the visibility of vessels and structures in capsule endoscopy images.

Microscopy mineral image enhancement based on improved adaptive threshold in nonsubsampled shearlet transform domain

NASA Astrophysics Data System (ADS)

Li, Liangliang; Si, Yujuan; Jia, Zhenhong

2018-03-01

In this paper, a novel microscopy mineral image enhancement method based on adaptive threshold in non-subsampled shearlet transform (NSST) domain is proposed. First, the image is decomposed into one low-frequency sub-band and several high-frequency sub-bands. Second, the gamma correction is applied to process the low-frequency sub-band coefficients, and the improved adaptive threshold is adopted to suppress the noise of the high-frequency sub-bands coefficients. Third, the processed coefficients are reconstructed with the inverse NSST. Finally, the unsharp filter is used to enhance the details of the reconstructed image. Experimental results on various microscopy mineral images demonstrated that the proposed approach has a better enhancement effect in terms of objective metric and subjective metric.

Color image enhancement based on particle swarm optimization with Gaussian mixture

NASA Astrophysics Data System (ADS)

Kattakkalil Subhashdas, Shibudas; Choi, Bong-Seok; Yoo, Ji-Hoon; Ha, Yeong-Ho

2015-01-01

This paper proposes a Gaussian mixture based image enhancement method which uses particle swarm optimization (PSO) to have an edge over other contemporary methods. The proposed method uses the guassian mixture model to model the lightness histogram of the input image in CIEL*a*b* space. The intersection points of the guassian components in the model are used to partition the lightness histogram. . The enhanced lightness image is generated by transforming the lightness value in each interval to appropriate output interval according to the transformation function that depends on PSO optimized parameters, weight and standard deviation of Gaussian component and cumulative distribution of the input histogram interval. In addition, chroma compensation is applied to the resulting image to reduce washout appearance. Experimental results show that the proposed method produces a better enhanced image compared to the traditional methods. Moreover, the enhanced image is free from several side effects such as washout appearance, information loss and gradation artifacts.

Enhancement of panoramic image resolution based on swift interpolation of Bezier surface

NASA Astrophysics Data System (ADS)

Xiao, Xiao; Yang, Guo-guang; Bai, Jian

2007-01-01

Panoramic annular lens project the view of the entire 360 degrees around the optical axis onto an annular plane based on the way of flat cylinder perspective. Due to the infinite depth of field and the linear mapping relationship between an object and an image, the panoramic imaging system plays important roles in the applications of robot vision, surveillance and virtual reality. An annular image needs to be unwrapped to conventional rectangular image without distortion, in which interpolation algorithm is necessary. Although cubic splines interpolation can enhance the resolution of unwrapped image, it occupies too much time to be applied in practices. This paper adopts interpolation method based on Bezier surface and proposes a swift interpolation algorithm for panoramic image, considering the characteristic of panoramic image. The result indicates that the resolution of the image is well enhanced compared with the image by cubic splines and bilinear interpolation. Meanwhile the time consumed is shortened up by 78% than the time consumed cubic interpolation.

Contrast-enhanced photoacoustic tomography of human joints

NASA Astrophysics Data System (ADS)

Tian, Chao; Keswani, Rahul K.; Gandikota, Girish; Rosania, Gus R.; Wang, Xueding

2016-03-01

Photoacoustic tomography (PAT) provides a unique tool to diagnose inflammatory arthritis. However, the specificity and sensitivity of PAT based on endogenous contrasts is limited. The development of contrast enhanced PAT imaging modalities in combination with small molecule contrast agents could lead to improvements in diagnosis and treatment of joint disease. Accordingly, we adapted and tested a PAT clinical imaging system for imaging the human joints, in combination with a novel PAT contrast agent derived from an FDA-approved small molecule drug. Imaging results based on a photoacoustic and ultrasound (PA/US) dual-modality system revealed that this contrast-enhanced PAT imaging system may offer additional information beyond single-modality PA or US imaging system, for the imaging, diagnosis and assessment of inflammatory arthritis.

Investigation on improved infrared image detail enhancement algorithm based on adaptive histogram statistical stretching and gradient filtering

NASA Astrophysics Data System (ADS)

Zeng, Bangze; Zhu, Youpan; Li, Zemin; Hu, Dechao; Luo, Lin; Zhao, Deli; Huang, Juan

2014-11-01

Duo to infrared image with low contrast, big noise and unclear visual effect, target is very difficult to observed and identified. This paper presents an improved infrared image detail enhancement algorithm based on adaptive histogram statistical stretching and gradient filtering (AHSS-GF). Based on the fact that the human eyes are very sensitive to the edges and lines, the author proposed to extract the details and textures by using the gradient filtering. New histogram could be acquired by calculating the sum of original histogram based on fixed window. With the minimum value for cut-off point, author carried on histogram statistical stretching. After the proper weights given to the details and background, the detail-enhanced results could be acquired finally. The results indicate image contrast could be improved and the details and textures could be enhanced effectively as well.

Usefulness of the advanced neuroimaging protocol based on plain and gadolinium-enhanced constructive interference in steady state images for gamma knife radiosurgery and planning microsurgical procedures for skull base tumors.

PubMed

Hayashi, Motohiro; Chernov, Mikhail F; Tamura, Noriko; Yomo, Shoji; Tamura, Manabu; Horiba, Ayako; Izawa, Masahiro; Muragaki, Yoshihiro; Iseki, Hiroshi; Okada, Yoshikazu; Ivanov, Pavel; Régis, Jean; Takakura, Kintomo

2013-01-01

Gamma Knife radiosurgery (GKS) is currently performed with 0.1 mm preciseness, which can be designated microradiosurgery. It requires advanced methods for visualizing the target, which can be effectively attained by a neuroimaging protocol based on plain and gadolinium-enhanced constructive interference in steady state (CISS) images. Since 2003, the following thin-sliced images are routinely obtained before GKS of skull base lesions in our practice: axial CISS, gadolinium-enhanced axial CISS, gadolinium-enhanced axial modified time-of-flight (TOF), and axial computed tomography (CT). Fusion of "bone window" CT and magnetic resonance imaging (MRI), and detailed three-dimensional (3D) delineation of the anatomical structures are performed with the Leksell GammaPlan (Elekta Instruments AB). Recently, a similar technique has been also applied to evaluate neuroanatomy before open microsurgical procedures. Plain CISS images permit clear visualization of the cranial nerves in the subarachnoid space. Gadolinium-enhanced CISS images make the tumor "lucid" but do not affect the signal intensity of the cranial nerves, so they can be clearly delineated in the vicinity to the lesion. Gadolinium-enhanced TOF images are useful for 3D evaluation of the interrelations between the neoplasm and adjacent vessels. Fusion of "bone window" CT and MRI scans permits simultaneous assessment of both soft tissue and bone structures and allows 3D estimation and correction of MRI distortion artifacts. Detailed understanding of the neuroanatomy based on application of the advanced neuroimaging protocol permits performance of highly conformal and selective radiosurgical treatment. It also allows precise planning of the microsurgical procedures for skull base tumors.

A detail enhancement and dynamic range adjustment algorithm for high dynamic range images

NASA Astrophysics Data System (ADS)

Xu, Bo; Wang, Huachuang; Liang, Mingtao; Yu, Cong; Hu, Jinlong; Cheng, Hua

2014-08-01

Although high dynamic range (HDR) images contain large amounts of information, they have weak texture and low contrast. What's more, these images are difficult to be reproduced on low dynamic range displaying mediums. If much more information is to be acquired when these images are displayed on PCs, some specific transforms, such as compressing the dynamic range, enhancing the portions of little difference in original contrast and highlighting the texture details on the premise of keeping the parts of large contrast, are needed. To this ends, a multi-scale guided filter enhancement algorithm which derives from the single-scale guided filter based on the analysis of non-physical model is proposed in this paper. Firstly, this algorithm decomposes the original HDR images into base image and detail images of different scales, and then it adaptively selects a transform function which acts on the enhanced detail images and original images. By comparing the treatment effects of HDR images and low dynamic range (LDR) images of different scene features, it proves that this algorithm, on the basis of maintaining the hierarchy and texture details of images, not only improves the contrast and enhances the details of images, but also adjusts the dynamic range well. Thus, it is much suitable for human observation or analytical processing of machines.

Contrast-enhanced optical coherence microangiography with acoustic-actuated microbubbles

NASA Astrophysics Data System (ADS)

Liu, Yu-Hsuan; Zhang, Jia-Wei; Yeh, Chih-Kuang; Wei, Kuo-Chen; Liu, Hao-Li; Tsai, Meng-Tsan

2017-04-01

In this study, we propose to use gas-filled microbubbles (MBs) simultaneously actuated by the acoustic wave to enhance the imaging contrast of optical coherence tomography (OCT)-based angiography. In the phantom experiments, MBs can result in stronger backscattered intensity, enabling to enhance the contrast of OCT intensity image. Moreover, simultaneous application of low-intensity acoustic wave enables to temporally induce local vibration of particles and MBs in the vessels, resulting in time-variant OCT intensity which can be used for enhancing the contrast of OCT intensitybased angiography. Additionally, different acoustic modes and different acoustic powers to actuate MBs are performed and compared to investigate the feasibility of contrast enhancement. Finally, animal experiments are performed. The findings suggest that acoustic-actuated MBs can effectively enhance the imaging contrast of OCT-based angiography and the imaging depth of OCT angiography is also extended.

Infrared image enhancement based on the edge detection and mathematical morphology

NASA Astrophysics Data System (ADS)

Zhang, Linlin; Zhao, Yuejin; Dong, Liquan; Liu, Xiaohua; Yu, Xiaomei; Hui, Mei; Chu, Xuhong; Gong, Cheng

2010-11-01

The development of the un-cooled infrared imaging technology from military necessity. At present, It is widely applied in industrial, medicine, scientific and technological research and so on. The infrared radiation temperature distribution of the measured object's surface can be observed visually. The collection of infrared images from our laboratory has following characteristics: Strong spatial correlation, Low contrast , Poor visual effect; Without color or shadows because of gray image , and has low resolution; Low definition compare to the visible light image; Many kinds of noise are brought by the random disturbances of the external environment. Digital image processing are widely applied in many areas, it can now be studied up close and in detail in many research field. It has become one kind of important means of the human visual continuation. Traditional methods for image enhancement cannot capture the geometric information of images and tend to amplify noise. In order to remove noise and improve visual effect. Meanwhile, To overcome the above enhancement issues. The mathematical model of FPA unit was constructed based on matrix transformation theory. According to characteristics of FPA, Image enhancement algorithm which combined with mathematical morphology and edge detection are established. First of all, Image profile is obtained by using the edge detection combine with mathematical morphological operators. And then, through filling the template profile by original image to get the ideal background image, The image noise can be removed on the base of the above method. The experiments show that utilizing the proposed algorithm can enhance image detail and the signal to noise ratio.

Enhancement of multispectral thermal infrared images - Decorrelation contrast stretching

NASA Technical Reports Server (NTRS)

Gillespie, Alan R.

1992-01-01

Decorrelation contrast stretching is an effective method for displaying information from multispectral thermal infrared (TIR) images. The technique involves transformation of the data to principle components ('decorrelation'), independent contrast 'stretching' of data from the new 'decorrelated' image bands, and retransformation of the stretched data back to the approximate original axes, based on the inverse of the principle component rotation. The enhancement is robust in that colors of the same scene components are similar in enhanced images of similar scenes, or the same scene imaged at different times. Decorrelation contrast stretching is reviewed in the context of other enhancements applied to TIR images.

Infrared image enhancement using H(infinity) bounds for surveillance applications.

PubMed

Qidwai, Uvais

2008-08-01

In this paper, two algorithms have been presented to enhance the infrared (IR) images. Using the autoregressive moving average model structure and H(infinity) optimal bounds, the image pixels are mapped from the IR pixel space into normal optical image space, thus enhancing the IR image for improved visual quality. Although H(infinity)-based system identification algorithms are very common now, they are not quite suitable for real-time applications owing to their complexity. However, many variants of such algorithms are possible that can overcome this constraint. Two such algorithms have been developed and implemented in this paper. Theoretical and algorithmic results show remarkable enhancement in the acquired images. This will help in enhancing the visual quality of IR images for surveillance applications.

CINCH (confocal incoherent correlation holography) super resolution fluorescence microscopy based upon FINCH (Fresnel incoherent correlation holography).

PubMed

Siegel, Nisan; Storrie, Brian; Bruce, Marc; Brooker, Gary

2015-02-07

FINCH holographic fluorescence microscopy creates high resolution super-resolved images with enhanced depth of focus. The simple addition of a real-time Nipkow disk confocal image scanner in a conjugate plane of this incoherent holographic system is shown to reduce the depth of focus, and the combination of both techniques provides a simple way to enhance the axial resolution of FINCH in a combined method called "CINCH". An important feature of the combined system allows for the simultaneous real-time image capture of widefield and holographic images or confocal and confocal holographic images for ready comparison of each method on the exact same field of view. Additional GPU based complex deconvolution processing of the images further enhances resolution.

A comparative study on preprocessing techniques in diabetic retinopathy retinal images: illumination correction and contrast enhancement.

PubMed

Rasta, Seyed Hossein; Partovi, Mahsa Eisazadeh; Seyedarabi, Hadi; Javadzadeh, Alireza

2015-01-01

To investigate the effect of preprocessing techniques including contrast enhancement and illumination correction on retinal image quality, a comparative study was carried out. We studied and implemented a few illumination correction and contrast enhancement techniques on color retinal images to find out the best technique for optimum image enhancement. To compare and choose the best illumination correction technique we analyzed the corrected red and green components of color retinal images statistically and visually. The two contrast enhancement techniques were analyzed using a vessel segmentation algorithm by calculating the sensitivity and specificity. The statistical evaluation of the illumination correction techniques were carried out by calculating the coefficients of variation. The dividing method using the median filter to estimate background illumination showed the lowest Coefficients of variations in the red component. The quotient and homomorphic filtering methods after the dividing method presented good results based on their low Coefficients of variations. The contrast limited adaptive histogram equalization increased the sensitivity of the vessel segmentation algorithm up to 5% in the same amount of accuracy. The contrast limited adaptive histogram equalization technique has a higher sensitivity than the polynomial transformation operator as a contrast enhancement technique for vessel segmentation. Three techniques including the dividing method using the median filter to estimate background, quotient based and homomorphic filtering were found as the effective illumination correction techniques based on a statistical evaluation. Applying the local contrast enhancement technique, such as CLAHE, for fundus images presented good potentials in enhancing the vasculature segmentation.

A New Feature-Enhanced Speckle Reduction Method Based on Multiscale Analysis for Ultrasound B-Mode Imaging.

PubMed

Kang, Jinbum; Lee, Jae Young; Yoo, Yangmo

2016-06-01

Effective speckle reduction in ultrasound B-mode imaging is important for enhancing the image quality and improving the accuracy in image analysis and interpretation. In this paper, a new feature-enhanced speckle reduction (FESR) method based on multiscale analysis and feature enhancement filtering is proposed for ultrasound B-mode imaging. In FESR, clinical features (e.g., boundaries and borders of lesions) are selectively emphasized by edge, coherence, and contrast enhancement filtering from fine to coarse scales while simultaneously suppressing speckle development via robust diffusion filtering. In the simulation study, the proposed FESR method showed statistically significant improvements in edge preservation, mean structure similarity, speckle signal-to-noise ratio, and contrast-to-noise ratio (CNR) compared with other speckle reduction methods, e.g., oriented speckle reducing anisotropic diffusion (OSRAD), nonlinear multiscale wavelet diffusion (NMWD), the Laplacian pyramid-based nonlinear diffusion and shock filter (LPNDSF), and the Bayesian nonlocal means filter (OBNLM). Similarly, the FESR method outperformed the OSRAD, NMWD, LPNDSF, and OBNLM methods in terms of CNR, i.e., 10.70 ± 0.06 versus 9.00 ± 0.06, 9.78 ± 0.06, 8.67 ± 0.04, and 9.22 ± 0.06 in the phantom study, respectively. Reconstructed B-mode images that were developed using the five speckle reduction methods were reviewed by three radiologists for evaluation based on each radiologist's diagnostic preferences. All three radiologists showed a significant preference for the abdominal liver images obtained using the FESR methods in terms of conspicuity, margin sharpness, artificiality, and contrast, p<0.0001. For the kidney and thyroid images, the FESR method showed similar improvement over other methods. However, the FESR method did not show statistically significant improvement compared with the OBNLM method in margin sharpness for the kidney and thyroid images. These results demonstrate that the proposed FESR method can improve the image quality of ultrasound B-mode imaging by enhancing the visualization of lesion features while effectively suppressing speckle noise.

Efficient image enhancement using sparse source separation in the Retinex theory

NASA Astrophysics Data System (ADS)

Yoon, Jongsu; Choi, Jangwon; Choe, Yoonsik

2017-11-01

Color constancy is the feature of the human vision system (HVS) that ensures the relative constancy of the perceived color of objects under varying illumination conditions. The Retinex theory of machine vision systems is based on the HVS. Among Retinex algorithms, the physics-based algorithms are efficient; however, they generally do not satisfy the local characteristics of the original Retinex theory because they eliminate global illumination from their optimization. We apply the sparse source separation technique to the Retinex theory to present a physics-based algorithm that satisfies the locality characteristic of the original Retinex theory. Previous Retinex algorithms have limited use in image enhancement because the total variation Retinex results in an overly enhanced image and the sparse source separation Retinex cannot completely restore the original image. In contrast, our proposed method preserves the image edge and can very nearly replicate the original image without any special operation.

Comparison of SPECT/CT, MRI and CT in diagnosis of skull base bone invasion in nasopharyngeal carcinoma.

PubMed

Zhang, Shu-xu; Han, Peng-hui; Zhang, Guo-qian; Wang, Rui-hao; Ge, Yong-bin; Ren, Zhi-gang; Li, Jian-sheng; Fu, Wen-hai

2014-01-01

Early detection of skull base invasion in nasopharyngeal carcinoma (NPC) is crucial for correct staging, assessing treatment response and contouring the tumor target in radiotherapy planning, as well as improving the patient's prognosis. To compare the diagnostic efficacy of single photon emission computed tomography/computed tomography (SPECT/CT) imaging, magnetic resonance imaging (MRI) and computed tomography (CT) for the detection of skull base invasion in NPC. Sixty untreated patients with histologically proven NPC underwent SPECT/CT imaging, contrast-enhanced MRI and CT. Of the 60 patients, 30 had skull base invasion confirmed by the final results of contrast-enhanced MRI, CT and six-month follow-up imaging (MRI and CT). The diagnostic efficacy of the three imaging modalities in detecting skull base invasion was evaluated. The rates of positive findings of skull base invasion for SPECT/CT, MRI and CT were 53.3%, 48.3% and 33.3%, respectively. The sensitivity, specificity and accuracy were 93.3%, 86.7% and 90.0% for SPECT/CT fusion imaging, 96.7%, 100.0% and 98.3% for contrast-enhanced MRI, and 66.7%, 100.0% and 83.3% for contrast-enhanced CT. MRI showed the best performance for the diagnosis of skull base invasion in nasopharyngeal carcinoma, followed closely by SPECT/CT. SPECT/CT had poorer specificity than that of both MRI and CT, while CT had the lowest sensitivity.

Image enhancement of optical images for binary system of melanocytes and keratinocytes

NASA Astrophysics Data System (ADS)

Takanezawa, S.; Baba, A.; Sako, Y.; Ozaki, Y.; Date, A.; Toyama, K.; Morita, S.

2013-05-01

Automatic determination of the cell shapes of large numbers of melanocytes based on optical images of human skin models have been largely unsuccessful (the complexities introduced by dendrites and the melanin pigmentation over the keratinocytes to give unclear outlines). Here, we present an image enhancement procedure for enhancing the contrast of images with removing the non-uniformity of background. The brightness is normalized also for the non-uniform population density of melanocytes.

Color reproduction and processing algorithm based on real-time mapping for endoscopic images.

PubMed

Khan, Tareq H; Mohammed, Shahed K; Imtiaz, Mohammad S; Wahid, Khan A

2016-01-01

In this paper, we present a real-time preprocessing algorithm for image enhancement for endoscopic images. A novel dictionary based color mapping algorithm is used for reproducing the color information from a theme image. The theme image is selected from a nearby anatomical location. A database of color endoscopy image for different location is prepared for this purpose. The color map is dynamic as its contents change with the change of the theme image. This method is used on low contrast grayscale white light images and raw narrow band images to highlight the vascular and mucosa structures and to colorize the images. It can also be applied to enhance the tone of color images. The statistic visual representation and universal image quality measures show that the proposed method can highlight the mucosa structure compared to other methods. The color similarity has been verified using Delta E color difference, structure similarity index, mean structure similarity index and structure and hue similarity. The color enhancement was measured using color enhancement factor that shows considerable improvements. The proposed algorithm has low and linear time complexity, which results in higher execution speed than other related works.

Color Retinal Image Enhancement Based on Luminosity and Contrast Adjustment.

PubMed

Zhou, Mei; Jin, Kai; Wang, Shaoze; Ye, Juan; Qian, Dahong

2018-03-01

Many common eye diseases and cardiovascular diseases can be diagnosed through retinal imaging. However, due to uneven illumination, image blurring, and low contrast, retinal images with poor quality are not useful for diagnosis, especially in automated image analyzing systems. Here, we propose a new image enhancement method to improve color retinal image luminosity and contrast. A luminance gain matrix, which is obtained by gamma correction of the value channel in the HSV (hue, saturation, and value) color space, is used to enhance the R, G, and B (red, green and blue) channels, respectively. Contrast is then enhanced in the luminosity channel of L * a * b * color space by CLAHE (contrast-limited adaptive histogram equalization). Image enhancement by the proposed method is compared to other methods by evaluating quality scores of the enhanced images. The performance of the method is mainly validated on a dataset of 961 poor-quality retinal images. Quality assessment (range 0-1) of image enhancement of this poor dataset indicated that our method improved color retinal image quality from an average of 0.0404 (standard deviation 0.0291) up to an average of 0.4565 (standard deviation 0.1000). The proposed method is shown to achieve superior image enhancement compared to contrast enhancement in other color spaces or by other related methods, while simultaneously preserving image naturalness. This method of color retinal image enhancement may be employed to assist ophthalmologists in more efficient screening of retinal diseases and in development of improved automated image analysis for clinical diagnosis.

A review on brightness preserving contrast enhancement methods for digital image

NASA Astrophysics Data System (ADS)

Rahman, Md Arifur; Liu, Shilong; Li, Ruowei; Wu, Hongkun; Liu, San Chi; Jahan, Mahmuda Rawnak; Kwok, Ngaiming

2018-04-01

Image enhancement is an imperative step for many vision based applications. For image contrast enhancement, popular methods adopt the principle of spreading the captured intensities throughout the allowed dynamic range according to predefined distributions. However, these algorithms take little or no consideration into account of maintaining the mean brightness of the original scene, which is of paramount importance to carry the true scene illumination characteristics to the viewer. Though there have been significant amount of reviews on contrast enhancement methods published, updated review on overall brightness preserving image enhancement methods is still scarce. In this paper, a detailed survey is performed on those particular methods that specifically aims to maintain the overall scene illumination characteristics while enhancing the digital image.

Image enhancement using MCNP5 code and MATLAB in neutron radiography.

PubMed

Tharwat, Montaser; Mohamed, Nader; Mongy, T

2014-07-01

This work presents a method that can be used to enhance the neutron radiography (NR) image for objects with high scattering materials like hydrogen, carbon and other light materials. This method used Monte Carlo code, MCNP5, to simulate the NR process and get the flux distribution for each pixel of the image and determines the scattered neutron distribution that caused image blur, and then uses MATLAB to subtract this scattered neutron distribution from the initial image to improve its quality. This work was performed before the commissioning of digital NR system in Jan. 2013. The MATLAB enhancement method is quite a good technique in the case of static based film neutron radiography, while in neutron imaging (NI) technique, image enhancement and quantitative measurement were efficient by using ImageJ software. The enhanced image quality and quantitative measurements were presented in this work. Copyright © 2014 Elsevier Ltd. All rights reserved.

CINCH (confocal incoherent correlation holography) super resolution fluorescence microscopy based upon FINCH (Fresnel incoherent correlation holography)

PubMed Central

Siegel, Nisan; Storrie, Brian; Bruce, Marc

2016-01-01

FINCH holographic fluorescence microscopy creates high resolution super-resolved images with enhanced depth of focus. The simple addition of a real-time Nipkow disk confocal image scanner in a conjugate plane of this incoherent holographic system is shown to reduce the depth of focus, and the combination of both techniques provides a simple way to enhance the axial resolution of FINCH in a combined method called “CINCH”. An important feature of the combined system allows for the simultaneous real-time image capture of widefield and holographic images or confocal and confocal holographic images for ready comparison of each method on the exact same field of view. Additional GPU based complex deconvolution processing of the images further enhances resolution. PMID:26839443

Image smoothing and enhancement via min/max curvature flow

NASA Astrophysics Data System (ADS)

Malladi, Ravikanth; Sethian, James A.

1996-03-01

We present a class of PDE-based algorithms suitable for a wide range of image processing applications. The techniques are applicable to both salt-and-pepper gray-scale noise and full- image continuous noise present in black and white images, gray-scale images, texture images and color images. At the core, the techniques rely on a level set formulation of evolving curves and surfaces and the viscosity in profile evolution. Essentially, the method consists of moving the isointensity contours in an image under curvature dependent speed laws to achieve enhancement. Compared to existing techniques, our approach has several distinct advantages. First, it contains only one enhancement parameter, which in most cases is automatically chosen. Second, the scheme automatically stops smoothing at some optimal point; continued application of the scheme produces no further change. Third, the method is one of the fastest possible schemes based on a curvature-controlled approach.

Image contrast enhancement with brightness preservation using an optimal gamma correction and weighted sum approach

NASA Astrophysics Data System (ADS)

Jiang, G.; Wong, C. Y.; Lin, S. C. F.; Rahman, M. A.; Ren, T. R.; Kwok, Ngaiming; Shi, Haiyan; Yu, Ying-Hao; Wu, Tonghai

2015-04-01

The enhancement of image contrast and preservation of image brightness are two important but conflicting objectives in image restoration. Previous attempts based on linear histogram equalization had achieved contrast enhancement, but exact preservation of brightness was not accomplished. A new perspective is taken here to provide balanced performance of contrast enhancement and brightness preservation simultaneously by casting the quest of such solution to an optimization problem. Specifically, the non-linear gamma correction method is adopted to enhance the contrast, while a weighted sum approach is employed for brightness preservation. In addition, the efficient golden search algorithm is exploited to determine the required optimal parameters to produce the enhanced images. Experiments are conducted on natural colour images captured under various indoor, outdoor and illumination conditions. Results have shown that the proposed method outperforms currently available methods in contrast to enhancement and brightness preservation.

Noise reduction and image enhancement using a hardware implementation of artificial neural networks

NASA Astrophysics Data System (ADS)

David, Robert; Williams, Erin; de Tremiolles, Ghislain; Tannhof, Pascal

1999-03-01

In this paper, we present a neural based solution developed for noise reduction and image enhancement using the ZISC, an IBM hardware processor which implements the Restricted Coulomb Energy algorithm and the K-Nearest Neighbor algorithm. Artificial neural networks present the advantages of processing time reduction in comparison with classical models, adaptability, and the weighted property of pattern learning. The goal of the developed application is image enhancement in order to restore old movies (noise reduction, focus correction, etc.), to improve digital television images, or to treat images which require adaptive processing (medical images, spatial images, special effects, etc.). Image results show a quantitative improvement over the noisy image as well as the efficiency of this system. Further enhancements are being examined to improve the output of the system.

A Comparative Study on Preprocessing Techniques in Diabetic Retinopathy Retinal Images: Illumination Correction and Contrast Enhancement

PubMed Central

Rasta, Seyed Hossein; Partovi, Mahsa Eisazadeh; Seyedarabi, Hadi; Javadzadeh, Alireza

2015-01-01

To investigate the effect of preprocessing techniques including contrast enhancement and illumination correction on retinal image quality, a comparative study was carried out. We studied and implemented a few illumination correction and contrast enhancement techniques on color retinal images to find out the best technique for optimum image enhancement. To compare and choose the best illumination correction technique we analyzed the corrected red and green components of color retinal images statistically and visually. The two contrast enhancement techniques were analyzed using a vessel segmentation algorithm by calculating the sensitivity and specificity. The statistical evaluation of the illumination correction techniques were carried out by calculating the coefficients of variation. The dividing method using the median filter to estimate background illumination showed the lowest Coefficients of variations in the red component. The quotient and homomorphic filtering methods after the dividing method presented good results based on their low Coefficients of variations. The contrast limited adaptive histogram equalization increased the sensitivity of the vessel segmentation algorithm up to 5% in the same amount of accuracy. The contrast limited adaptive histogram equalization technique has a higher sensitivity than the polynomial transformation operator as a contrast enhancement technique for vessel segmentation. Three techniques including the dividing method using the median filter to estimate background, quotient based and homomorphic filtering were found as the effective illumination correction techniques based on a statistical evaluation. Applying the local contrast enhancement technique, such as CLAHE, for fundus images presented good potentials in enhancing the vasculature segmentation. PMID:25709940

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.

Visual enhancement of unmixed multispectral imagery using adaptive smoothing

USGS Publications Warehouse

Lemeshewsky, G.P.; Rahman, Z.-U.; Schowengerdt, R.A.; Reichenbach, S.E.

2004-01-01

Adaptive smoothing (AS) has been previously proposed as a method to smooth uniform regions of an image, retain contrast edges, and enhance edge boundaries. The method is an implementation of the anisotropic diffusion process which results in a gray scale image. This paper discusses modifications to the AS method for application to multi-band data which results in a color segmented image. The process was used to visually enhance the three most distinct abundance fraction images produced by the Lagrange constraint neural network learning-based unmixing of Landsat 7 Enhanced Thematic Mapper Plus multispectral sensor data. A mutual information-based method was applied to select the three most distinct fraction images for subsequent visualization as a red, green, and blue composite. A reported image restoration technique (partial restoration) was applied to the multispectral data to reduce unmixing error, although evaluation of the performance of this technique was beyond the scope of this paper. The modified smoothing process resulted in a color segmented image with homogeneous regions separated by sharpened, coregistered multiband edges. There was improved class separation with the segmented image, which has importance to subsequent operations involving data classification.

Image enhancement for on-site X-ray nondestructive inspection of reinforced concrete structures.

PubMed

Pei, Cuixiang; Wu, Wenjing; Ueaska, Mitsuru

2016-11-22

The use of portable and high-energy X-ray system can provide a very promising approach for on-site nondestructive inspection of inner steel reinforcement of concrete structures. However, the noise properties and contrast of the radiographic images for thick concrete structures do often not meet the demands. To enhance the images, we present a simple and effective method for noise reduction based on a combined curvelet-wavelet transform and local contrast enhancement based on neighborhood operation. To investigate the performance of this method for our X-ray system, we have performed several experiments with using simulated and experimental data. With comparing to other traditional methods, it shows that the proposed image enhancement method has a better performance and can significantly improve the inspection performance for reinforced concrete structures.

Spatio-Temporal Super-Resolution Reconstruction of Remote-Sensing Images Based on Adaptive Multi-Scale Detail Enhancement

PubMed Central

Zhu, Hong; Tang, Xinming; Xie, Junfeng; Song, Weidong; Mo, Fan; Gao, Xiaoming

2018-01-01

There are many problems in existing reconstruction-based super-resolution algorithms, such as the lack of texture-feature representation and of high-frequency details. Multi-scale detail enhancement can produce more texture information and high-frequency information. Therefore, super-resolution reconstruction of remote-sensing images based on adaptive multi-scale detail enhancement (AMDE-SR) is proposed in this paper. First, the information entropy of each remote-sensing image is calculated, and the image with the maximum entropy value is regarded as the reference image. Subsequently, spatio-temporal remote-sensing images are processed using phase normalization, which is to reduce the time phase difference of image data and enhance the complementarity of information. The multi-scale image information is then decomposed using the L0 gradient minimization model, and the non-redundant information is processed by difference calculation and expanding non-redundant layers and the redundant layer by the iterative back-projection (IBP) technique. The different-scale non-redundant information is adaptive-weighted and fused using cross-entropy. Finally, a nonlinear texture-detail-enhancement function is built to improve the scope of small details, and the peak signal-to-noise ratio (PSNR) is used as an iterative constraint. Ultimately, high-resolution remote-sensing images with abundant texture information are obtained by iterative optimization. Real results show an average gain in entropy of up to 0.42 dB for an up-scaling of 2 and a significant promotion gain in enhancement measure evaluation for an up-scaling of 2. The experimental results show that the performance of the AMED-SR method is better than existing super-resolution reconstruction methods in terms of visual and accuracy improvements. PMID:29414893

Spatio-Temporal Super-Resolution Reconstruction of Remote-Sensing Images Based on Adaptive Multi-Scale Detail Enhancement.

PubMed

Zhu, Hong; Tang, Xinming; Xie, Junfeng; Song, Weidong; Mo, Fan; Gao, Xiaoming

2018-02-07

There are many problems in existing reconstruction-based super-resolution algorithms, such as the lack of texture-feature representation and of high-frequency details. Multi-scale detail enhancement can produce more texture information and high-frequency information. Therefore, super-resolution reconstruction of remote-sensing images based on adaptive multi-scale detail enhancement (AMDE-SR) is proposed in this paper. First, the information entropy of each remote-sensing image is calculated, and the image with the maximum entropy value is regarded as the reference image. Subsequently, spatio-temporal remote-sensing images are processed using phase normalization, which is to reduce the time phase difference of image data and enhance the complementarity of information. The multi-scale image information is then decomposed using the L ₀ gradient minimization model, and the non-redundant information is processed by difference calculation and expanding non-redundant layers and the redundant layer by the iterative back-projection (IBP) technique. The different-scale non-redundant information is adaptive-weighted and fused using cross-entropy. Finally, a nonlinear texture-detail-enhancement function is built to improve the scope of small details, and the peak signal-to-noise ratio (PSNR) is used as an iterative constraint. Ultimately, high-resolution remote-sensing images with abundant texture information are obtained by iterative optimization. Real results show an average gain in entropy of up to 0.42 dB for an up-scaling of 2 and a significant promotion gain in enhancement measure evaluation for an up-scaling of 2. The experimental results show that the performance of the AMED-SR method is better than existing super-resolution reconstruction methods in terms of visual and accuracy improvements.

Adaptive Markov Random Fields for Example-Based Super-resolution of Faces

NASA Astrophysics Data System (ADS)

Stephenson, Todd A.; Chen, Tsuhan

2006-12-01

Image enhancement of low-resolution images can be done through methods such as interpolation, super-resolution using multiple video frames, and example-based super-resolution. Example-based super-resolution, in particular, is suited to images that have a strong prior (for those frameworks that work on only a single image, it is more like image restoration than traditional, multiframe super-resolution). For example, hallucination and Markov random field (MRF) methods use examples drawn from the same domain as the image being enhanced to determine what the missing high-frequency information is likely to be. We propose to use even stronger prior information by extending MRF-based super-resolution to use adaptive observation and transition functions, that is, to make these functions region-dependent. We show with face images how we can adapt the modeling for each image patch so as to improve the resolution.

Wavelength-adaptive dehazing using histogram merging-based classification for UAV images.

PubMed

Yoon, Inhye; Jeong, Seokhwa; Jeong, Jaeheon; Seo, Doochun; Paik, Joonki

2015-03-19

Since incoming light to an unmanned aerial vehicle (UAV) platform can be scattered by haze and dust in the atmosphere, the acquired image loses the original color and brightness of the subject. Enhancement of hazy images is an important task in improving the visibility of various UAV images. This paper presents a spatially-adaptive dehazing algorithm that merges color histograms with consideration of the wavelength-dependent atmospheric turbidity. Based on the wavelength-adaptive hazy image acquisition model, the proposed dehazing algorithm consists of three steps: (i) image segmentation based on geometric classes; (ii) generation of the context-adaptive transmission map; and (iii) intensity transformation for enhancing a hazy UAV image. The major contribution of the research is a novel hazy UAV image degradation model by considering the wavelength of light sources. In addition, the proposed transmission map provides a theoretical basis to differentiate visually important regions from others based on the turbidity and merged classification results.

Adaptive pseudo-color enhancement method of weld radiographic images based on HSI color space and self-transformation of pixels.

PubMed

Jiang, Hongquan; Zhao, Yalin; Gao, Jianmin; Gao, Zhiyong

2017-06-01

The radiographic testing (RT) image of a steam turbine manufacturing enterprise has the characteristics of low gray level, low contrast, and blurriness, which lead to a substandard image quality. Moreover, it is not conducive for human eyes to detect and evaluate defects. This study proposes an adaptive pseudo-color enhancement method for weld radiographic images based on the hue, saturation, and intensity (HSI) color space and the self-transformation of pixels to solve these problems. First, the pixel's self-transformation is performed to the pixel value of the original RT image. The function value after the pixel's self-transformation is assigned to the HSI components in the HSI color space. Thereafter, the average intensity of the enhanced image is adaptively adjusted to 0.5 according to the intensity of the original image. Moreover, the hue range and interval can be adjusted according to personal habits. Finally, the HSI components after the adaptive adjustment can be transformed to display in the red, green, and blue color space. Numerous weld radiographic images from a steam turbine manufacturing enterprise are used to validate the proposed method. The experimental results show that the proposed pseudo-color enhancement method can improve image definition and make the target and background areas distinct in weld radiographic images. The enhanced images will be more conducive for defect recognition. Moreover, the image enhanced using the proposed method conforms to the human eye visual properties, and the effectiveness of defect recognition and evaluation can be ensured.

Adaptive pseudo-color enhancement method of weld radiographic images based on HSI color space and self-transformation of pixels

NASA Astrophysics Data System (ADS)

Jiang, Hongquan; Zhao, Yalin; Gao, Jianmin; Gao, Zhiyong

2017-06-01

The radiographic testing (RT) image of a steam turbine manufacturing enterprise has the characteristics of low gray level, low contrast, and blurriness, which lead to a substandard image quality. Moreover, it is not conducive for human eyes to detect and evaluate defects. This study proposes an adaptive pseudo-color enhancement method for weld radiographic images based on the hue, saturation, and intensity (HSI) color space and the self-transformation of pixels to solve these problems. First, the pixel's self-transformation is performed to the pixel value of the original RT image. The function value after the pixel's self-transformation is assigned to the HSI components in the HSI color space. Thereafter, the average intensity of the enhanced image is adaptively adjusted to 0.5 according to the intensity of the original image. Moreover, the hue range and interval can be adjusted according to personal habits. Finally, the HSI components after the adaptive adjustment can be transformed to display in the red, green, and blue color space. Numerous weld radiographic images from a steam turbine manufacturing enterprise are used to validate the proposed method. The experimental results show that the proposed pseudo-color enhancement method can improve image definition and make the target and background areas distinct in weld radiographic images. The enhanced images will be more conducive for defect recognition. Moreover, the image enhanced using the proposed method conforms to the human eye visual properties, and the effectiveness of defect recognition and evaluation can be ensured.

Lower-upper-threshold correlation for underwater range-gated imaging self-adaptive enhancement.

PubMed

Sun, Liang; Wang, Xinwei; Liu, Xiaoquan; Ren, Pengdao; Lei, Pingshun; He, Jun; Fan, Songtao; Zhou, Yan; Liu, Yuliang

2016-10-10

In underwater range-gated imaging (URGI), enhancement of low-brightness and low-contrast images is critical for human observation. Traditional histogram equalizations over-enhance images, with the result of details being lost. To compress over-enhancement, a lower-upper-threshold correlation method is proposed for underwater range-gated imaging self-adaptive enhancement based on double-plateau histogram equalization. The lower threshold determines image details and compresses over-enhancement. It is correlated with the upper threshold. First, the upper threshold is updated by searching for the local maximum in real time, and then the lower threshold is calculated by the upper threshold and the number of nonzero units selected from a filtered histogram. With this method, the backgrounds of underwater images are constrained with enhanced details. Finally, the proof experiments are performed. Peak signal-to-noise-ratio, variance, contrast, and human visual properties are used to evaluate the objective quality of the global and regions of interest images. The evaluation results demonstrate that the proposed method adaptively selects the proper upper and lower thresholds under different conditions. The proposed method contributes to URGI with effective image enhancement for human eyes.

Gabor filter based fingerprint image enhancement

NASA Astrophysics Data System (ADS)

Wang, Jin-Xiang

2013-03-01

Fingerprint recognition technology has become the most reliable biometric technology due to its uniqueness and invariance, which has been most convenient and most reliable technique for personal authentication. The development of Automated Fingerprint Identification System is an urgent need for modern information security. Meanwhile, fingerprint preprocessing algorithm of fingerprint recognition technology has played an important part in Automatic Fingerprint Identification System. This article introduces the general steps in the fingerprint recognition technology, namely the image input, preprocessing, feature recognition, and fingerprint image enhancement. As the key to fingerprint identification technology, fingerprint image enhancement affects the accuracy of the system. It focuses on the characteristics of the fingerprint image, Gabor filters algorithm for fingerprint image enhancement, the theoretical basis of Gabor filters, and demonstration of the filter. The enhancement algorithm for fingerprint image is in the windows XP platform with matlab.65 as a development tool for the demonstration. The result shows that the Gabor filter is effective in fingerprint image enhancement technology.

Cuckoo search algorithm based satellite image contrast and brightness enhancement using DWT-SVD.

PubMed

Bhandari, A K; Soni, V; Kumar, A; Singh, G K

2014-07-01

This paper presents a new contrast enhancement approach which is based on Cuckoo Search (CS) algorithm and DWT-SVD for quality improvement of the low contrast satellite images. The input image is decomposed into the four frequency subbands through Discrete Wavelet Transform (DWT), and CS algorithm used to optimize each subband of DWT and then obtains the singular value matrix of the low-low thresholded subband image and finally, it reconstructs the enhanced image by applying IDWT. The singular value matrix employed intensity information of the particular image, and any modification in the singular values changes the intensity of the given image. The experimental results show superiority of the proposed method performance in terms of PSNR, MSE, Mean and Standard Deviation over conventional and state-of-the-art techniques. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Research on respiratory motion correction method based on liver contrast-enhanced ultrasound images of single mode

NASA Astrophysics Data System (ADS)

Zhang, Ji; Li, Tao; Zheng, Shiqiang; Li, Yiyong

2015-03-01

To reduce the effects of respiratory motion in the quantitative analysis based on liver contrast-enhanced ultrasound (CEUS) image sequencesof single mode. The image gating method and the iterative registration method using model image were adopted to register liver contrast-enhanced ultrasound image sequences of single mode. The feasibility of the proposed respiratory motion correction method was explored preliminarily using 10 hepatocellular carcinomas CEUS cases. The positions of the lesions in the time series of 2D ultrasound images after correction were visually evaluated. Before and after correction, the quality of the weighted sum of transit time (WSTT) parametric images were also compared, in terms of the accuracy and spatial resolution. For the corrected and uncorrected sequences, their mean deviation values (mDVs) of time-intensity curve (TIC) fitting derived from CEUS sequences were measured. After the correction, the positions of the lesions in the time series of 2D ultrasound images were almost invariant. In contrast, the lesions in the uncorrected images all shifted noticeably. The quality of the WSTT parametric maps derived from liver CEUS image sequences were improved more greatly. Moreover, the mDVs of TIC fitting derived from CEUS sequences after the correction decreased by an average of 48.48+/-42.15. The proposed correction method could improve the accuracy of quantitative analysis based on liver CEUS image sequences of single mode, which would help in enhancing the differential diagnosis efficiency of liver tumors.

Naturalness preservation image contrast enhancement via histogram modification

NASA Astrophysics Data System (ADS)

Tian, Qi-Chong; Cohen, Laurent D.

2018-04-01

Contrast enhancement is a technique for enhancing image contrast to obtain better visual quality. Since many existing contrast enhancement algorithms usually produce over-enhanced results, the naturalness preservation is needed to be considered in the framework of image contrast enhancement. This paper proposes a naturalness preservation contrast enhancement method, which adopts the histogram matching to improve the contrast and uses the image quality assessment to automatically select the optimal target histogram. The contrast improvement and the naturalness preservation are both considered in the target histogram, so this method can avoid the over-enhancement problem. In the proposed method, the optimal target histogram is a weighted sum of the original histogram, the uniform histogram, and the Gaussian-shaped histogram. Then the structural metric and the statistical naturalness metric are used to determine the weights of corresponding histograms. At last, the contrast-enhanced image is obtained via matching the optimal target histogram. The experiments demonstrate the proposed method outperforms the compared histogram-based contrast enhancement algorithms.

Resolution enhancement in deep-tissue nanoparticle imaging based on plasmonic saturated excitation microscopy

NASA Astrophysics Data System (ADS)

Deka, Gitanjal; Nishida, Kentaro; Mochizuki, Kentaro; Ding, Hou-Xian; Fujita, Katsumasa; Chu, Shi-Wei

2018-03-01

Recently, many resolution enhancing techniques are demonstrated, but most of them are severely limited for deep tissue applications. For example, wide-field based localization techniques lack the ability of optical sectioning, and structured light based techniques are susceptible to beam distortion due to scattering/aberration. Saturated excitation (SAX) microscopy, which relies on temporal modulation that is less affected when penetrating into tissues, should be the best candidate for deep-tissue resolution enhancement. Nevertheless, although fluorescence saturation has been successfully adopted in SAX, it is limited by photobleaching, and its practical resolution enhancement is less than two-fold. Recently, we demonstrated plasmonic SAX which provides bleaching-free imaging with three-fold resolution enhancement. Here we show that the three-fold resolution enhancement is sustained throughout the whole working distance of an objective, i.e., 200 μm, which is the deepest super-resolution record to our knowledge, and is expected to extend into deeper tissues. In addition, SAX offers the advantage of background-free imaging by rejecting unwanted scattering background from biological tissues. This study provides an inspirational direction toward deep-tissue super-resolution imaging and has the potential in tumor monitoring and beyond.

Image contrast enhancement based on a local standard deviation model

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

Chang, Dah-Chung; Wu, Wen-Rong

1996-12-31

The adaptive contrast enhancement (ACE) algorithm is a widely used image enhancement method, which needs a contrast gain to adjust high frequency components of an image. In the literature, the gain is usually inversely proportional to the local standard deviation (LSD) or is a constant. But these cause two problems in practical applications, i.e., noise overenhancement and ringing artifact. In this paper a new gain is developed based on Hunt`s Gaussian image model to prevent the two defects. The new gain is a nonlinear function of LSD and has the desired characteristic emphasizing the LSD regions in which details aremore » concentrated. We have applied the new ACE algorithm to chest x-ray images and the simulations show the effectiveness of the proposed algorithm.« less

An Adaptive Image Enhancement Technique by Combining Cuckoo Search and Particle Swarm Optimization Algorithm

PubMed Central

Ye, Zhiwei; Wang, Mingwei; Hu, Zhengbing; Liu, Wei

2015-01-01

Image enhancement is an important procedure of image processing and analysis. This paper presents a new technique using a modified measure and blending of cuckoo search and particle swarm optimization (CS-PSO) for low contrast images to enhance image adaptively. In this way, contrast enhancement is obtained by global transformation of the input intensities; it employs incomplete Beta function as the transformation function and a novel criterion for measuring image quality considering three factors which are threshold, entropy value, and gray-level probability density of the image. The enhancement process is a nonlinear optimization problem with several constraints. CS-PSO is utilized to maximize the objective fitness criterion in order to enhance the contrast and detail in an image by adapting the parameters of a novel extension to a local enhancement technique. The performance of the proposed method has been compared with other existing techniques such as linear contrast stretching, histogram equalization, and evolutionary computing based image enhancement methods like backtracking search algorithm, differential search algorithm, genetic algorithm, and particle swarm optimization in terms of processing time and image quality. Experimental results demonstrate that the proposed method is robust and adaptive and exhibits the better performance than other methods involved in the paper. PMID:25784928

An adaptive image enhancement technique by combining cuckoo search and particle swarm optimization algorithm.

PubMed

Ye, Zhiwei; Wang, Mingwei; Hu, Zhengbing; Liu, Wei

2015-01-01

Image enhancement is an important procedure of image processing and analysis. This paper presents a new technique using a modified measure and blending of cuckoo search and particle swarm optimization (CS-PSO) for low contrast images to enhance image adaptively. In this way, contrast enhancement is obtained by global transformation of the input intensities; it employs incomplete Beta function as the transformation function and a novel criterion for measuring image quality considering three factors which are threshold, entropy value, and gray-level probability density of the image. The enhancement process is a nonlinear optimization problem with several constraints. CS-PSO is utilized to maximize the objective fitness criterion in order to enhance the contrast and detail in an image by adapting the parameters of a novel extension to a local enhancement technique. The performance of the proposed method has been compared with other existing techniques such as linear contrast stretching, histogram equalization, and evolutionary computing based image enhancement methods like backtracking search algorithm, differential search algorithm, genetic algorithm, and particle swarm optimization in terms of processing time and image quality. Experimental results demonstrate that the proposed method is robust and adaptive and exhibits the better performance than other methods involved in the paper.

Automated framework for estimation of lung tumor locations in kV-CBCT images for tumor-based patient positioning in stereotactic lung body radiotherapy

NASA Astrophysics Data System (ADS)

Yoshidome, Satoshi; Arimura, Hidetaka; Terashima, Koutarou; Hirakawa, Masakazu; Hirose, Taka-aki; Fukunaga, Junichi; Nakamura, Yasuhiko

2017-03-01

Recently, image-guided radiotherapy (IGRT) systems using kilovolt cone-beam computed tomography (kV-CBCT) images have become more common for highly accurate patient positioning in stereotactic lung body radiotherapy (SLBRT). However, current IGRT procedures are based on bone structures and subjective correction. Therefore, the aim of this study was to evaluate the proposed framework for automated estimation of lung tumor locations in kV-CBCT images for tumor-based patient positioning in SLBRT. Twenty clinical cases are considered, involving solid, pure ground-glass opacity (GGO), mixed GGO, solitary, and non-solitary tumor types. The proposed framework consists of four steps: (1) determination of a search region for tumor location detection in a kV-CBCT image; (2) extraction of a tumor template from a planning CT image; (3) preprocessing for tumor region enhancement (edge and tumor enhancement using a Sobel filter and a blob structure enhancement (BSE) filter, respectively); and (4) tumor location estimation based on a template-matching technique. The location errors in the original, edge-, and tumor-enhanced images were found to be 1.2 ± 0.7 mm, 4.2 ± 8.0 mm, and 2.7 ± 4.6 mm, respectively. The location errors in the original images of solid, pure GGO, mixed GGO, solitary, and non-solitary types of tumors were 1.2 ± 0.7 mm, 1.3 ± 0.9 mm, 0.4 ± 0.6 mm, 1.1 ± 0.8 mm and 1.0 ± 0.7 mm, respectively. These results suggest that the proposed framework is robust as regards automatic estimation of several types of tumor locations in kV-CBCT images for tumor-based patient positioning in SLBRT.

Particle swarm optimization-based local entropy weighted histogram equalization for infrared image enhancement

NASA Astrophysics Data System (ADS)

Wan, Minjie; Gu, Guohua; Qian, Weixian; Ren, Kan; Chen, Qian; Maldague, Xavier

2018-06-01

Infrared image enhancement plays a significant role in intelligent urban surveillance systems for smart city applications. Unlike existing methods only exaggerating the global contrast, we propose a particle swam optimization-based local entropy weighted histogram equalization which involves the enhancement of both local details and fore-and background contrast. First of all, a novel local entropy weighted histogram depicting the distribution of detail information is calculated based on a modified hyperbolic tangent function. Then, the histogram is divided into two parts via a threshold maximizing the inter-class variance in order to improve the contrasts of foreground and background, respectively. To avoid over-enhancement and noise amplification, double plateau thresholds of the presented histogram are formulated by means of particle swarm optimization algorithm. Lastly, each sub-image is equalized independently according to the constrained sub-local entropy weighted histogram. Comparative experiments implemented on real infrared images prove that our algorithm outperforms other state-of-the-art methods in terms of both visual and quantized evaluations.

The Past, Present, and Future of Image-Enhanced Endoscopy

PubMed Central

Jang, Jae-Young

2015-01-01

Despite the remarkable progress recently made to enhance the resolution of white-light endoscopy, detection, and diagnosis of premalignant lesions, such as adenomas and subtle early-stage cancers, remains a great challenge. As for example, although chromoendoscopy, such as endoscopy using indigo carmine, is useful for the early diagnosis of subtle lesions, the technique presents various disadvantages ranging from the time required for spray application of the dye and suctioning of excess dye to the increased difficulty in identifying lesions in the presence of severe inflammation and obstruction of visual field due to the pooling of solution in depressed-type lesions. To overcome these diagnostic problems associated with chromoendoscopy, research has focused on the development of endoscopes based on new optical technologies. Several types of image-enhanced endoscopy methods have recently been presented. In particular, image-enhanced endoscopy has emerged as a new paradigm for the diagnosis of gastrointestinal disorders. Image-enhanced endoscopes provide high-contrast images of lesions by means of optical or electronic technologies, including the contrast enhancement of the mucosal surface and of blood vessels. Chromoendoscopy, narrow-band imaging, i-SCAN, and flexible spectral imaging color enhancement are representative examples of image-enhanced endoscopy discussed in this paper. PMID:26668791

Fuzzy entropy thresholding and multi-scale morphological approach for microscopic image enhancement

NASA Astrophysics Data System (ADS)

Zhou, Jiancan; Li, Yuexiang; Shen, Linlin

2017-07-01

Microscopic images provide lots of useful information for modern diagnosis and biological research. However, due to the unstable lighting condition during image capturing, two main problems, i.e., high-level noises and low image contrast, occurred in the generated cell images. In this paper, a simple but efficient enhancement framework is proposed to address the problems. The framework removes image noises using a hybrid method based on wavelet transform and fuzzy-entropy, and enhances the image contrast with an adaptive morphological approach. Experiments on real cell dataset were made to assess the performance of proposed framework. The experimental results demonstrate that our proposed enhancement framework increases the cell tracking accuracy to an average of 74.49%, which outperforms the benchmark algorithm, i.e., 46.18%.

Human body region enhancement method based on Kinect infrared imaging

NASA Astrophysics Data System (ADS)

Yang, Lei; Fan, Yubo; Song, Xiaowei; Cai, Wenjing

2016-10-01

To effectively improve the low contrast of human body region in the infrared images, a combing method of several enhancement methods is utilized to enhance the human body region. Firstly, for the infrared images acquired by Kinect, in order to improve the overall contrast of the infrared images, an Optimal Contrast-Tone Mapping (OCTM) method with multi-iterations is applied to balance the contrast of low-luminosity infrared images. Secondly, to enhance the human body region better, a Level Set algorithm is employed to improve the contour edges of human body region. Finally, to further improve the human body region in infrared images, Laplacian Pyramid decomposition is adopted to enhance the contour-improved human body region. Meanwhile, the background area without human body region is processed by bilateral filtering to improve the overall effect. With theoretical analysis and experimental verification, the results show that the proposed method could effectively enhance the human body region of such infrared images.

Image processing based detection of lung cancer on CT scan images

NASA Astrophysics Data System (ADS)

Abdillah, Bariqi; Bustamam, Alhadi; Sarwinda, Devvi

2017-10-01

In this paper, we implement and analyze the image processing method for detection of lung cancer. Image processing techniques are widely used in several medical problems for picture enhancement in the detection phase to support the early medical treatment. In this research we proposed a detection method of lung cancer based on image segmentation. Image segmentation is one of intermediate level in image processing. Marker control watershed and region growing approach are used to segment of CT scan image. Detection phases are followed by image enhancement using Gabor filter, image segmentation, and features extraction. From the experimental results, we found the effectiveness of our approach. The results show that the best approach for main features detection is watershed with masking method which has high accuracy and robust.

Rapid and sensitive phenotypic marker detection on breast cancer cells using surface-enhanced Raman scattering (SERS) imaging.

PubMed

Lee, Sangyeop; Chon, Hyangah; Lee, Jiyoung; Ko, Juhui; Chung, Bong Hyun; Lim, Dong Woo; Choo, Jaebum

2014-01-15

We report a surface-enhanced Raman scattering (SERS)-based cellular imaging technique to detect and quantify breast cancer phenotypic markers expressed on cell surfaces. This technique involves the synthesis of SERS nano tags consisting of silica-encapsulated hollow gold nanospheres (SEHGNs) conjugated with specific antibodies. Hollow gold nanospheres (HGNs) enhance SERS signal intensity of individual particles by localizing surface electromagnetic fields through pinholes in the hollow particle structures. This capacity to enhance imaging at the level of single molecules permits the use of HGNs to detect specific biological markers expressed in living cancer cells. In addition, silica encapsulation greatly enhances the stability of nanoparticles. Here we applied a SERS-based imaging technique using SEHGNs in the multiplex imaging of three breast cancer cell phenotypes. Expression of epidermal growth factor (EGF), ErbB2, and insulin-like growth factor-1 (IGF-1) receptors were assessed in the MDA-MB-468, KPL4 and SK-BR-3 human breast cancer cell lines. SERS imaging technology described here can be used to test the phenotype of a cancer cell and quantify proteins expressed on the cell surface simultaneously. Based on results, this technique may enable an earlier diagnosis of breast cancer than is currently possible and offer guidance in treatment. © 2013 Elsevier B.V. All rights reserved.

Novel methods for parameter-based analysis of myocardial tissue in MR images

NASA Astrophysics Data System (ADS)

Hennemuth, A.; Behrens, S.; Kuehnel, C.; Oeltze, S.; Konrad, O.; Peitgen, H.-O.

2007-03-01

The analysis of myocardial tissue with contrast-enhanced MR yields multiple parameters, which can be used to classify the examined tissue. Perfusion images are often distorted by motion, while late enhancement images are acquired with a different size and resolution. Therefore, it is common to reduce the analysis to a visual inspection, or to the examination of parameters related to the 17-segment-model proposed by the American Heart Association (AHA). As this simplification comes along with a considerable loss of information, our purpose is to provide methods for a more accurate analysis regarding topological and functional tissue features. In order to achieve this, we implemented registration methods for the motion correction of the perfusion sequence and the matching of the late enhancement information onto the perfusion image and vice versa. For the motion corrected perfusion sequence, vector images containing the voxel enhancement curves' semi-quantitative parameters are derived. The resulting vector images are combined with the late enhancement information and form the basis for the tissue examination. For the exploration of data we propose different modes: the inspection of the enhancement curves and parameter distribution in areas automatically segmented using the late enhancement information, the inspection of regions segmented in parameter space by user defined threshold intervals and the topological comparison of regions segmented with different settings. Results showed a more accurate detection of distorted regions in comparison to the AHA-model-based evaluation.

Edge enhancement and noise suppression for infrared image based on feature analysis

NASA Astrophysics Data System (ADS)

Jiang, Meng

2018-06-01

Infrared images are often suffering from background noise, blurred edges, few details and low signal-to-noise ratios. To improve infrared image quality, it is essential to suppress noise and enhance edges simultaneously. To realize it in this paper, we propose a novel algorithm based on feature analysis in shearlet domain. Firstly, as one of multi-scale geometric analysis (MGA), we introduce the theory and superiority of shearlet transform. Secondly, after analyzing the defects of traditional thresholding technique to suppress noise, we propose a novel feature extraction distinguishing image structures from noise well and use it to improve the traditional thresholding technique. Thirdly, with computing the correlations between neighboring shearlet coefficients, the feature attribute maps identifying the weak detail and strong edges are completed to improve the generalized unsharped masking (GUM). At last, experiment results with infrared images captured in different scenes demonstrate that the proposed algorithm suppresses noise efficiently and enhances image edges adaptively.

Retinex based low-light image enhancement using guided filtering and variational framework

NASA Astrophysics Data System (ADS)

Zhang, Shi; Tang, Gui-jin; Liu, Xiao-hua; Luo, Su-huai; Wang, Da-dong

2018-03-01

A new image enhancement algorithm based on Retinex theory is proposed to solve the problem of bad visual effect of an image in low-light conditions. First, an image is converted from the RGB color space to the HSV color space to get the V channel. Next, the illuminations are respectively estimated by the guided filtering and the variational framework on the V channel and combined into a new illumination by average gradient. The new reflectance is calculated using V channel and the new illumination. Then a new V channel obtained by multiplying the new illumination and reflectance is processed with contrast limited adaptive histogram equalization (CLAHE). Finally, the new image in HSV space is converted back to RGB space to obtain the enhanced image. Experimental results show that the proposed method has better subjective quality and objective quality than existing methods.

Acceleration of integral imaging based incoherent Fourier hologram capture using graphic processing unit.

PubMed

Jeong, Kyeong-Min; Kim, Hee-Seung; Hong, Sung-In; Lee, Sung-Keun; Jo, Na-Young; Kim, Yong-Soo; Lim, Hong-Gi; Park, Jae-Hyeung

2012-10-08

Speed enhancement of integral imaging based incoherent Fourier hologram capture using a graphic processing unit is reported. Integral imaging based method enables exact hologram capture of real-existing three-dimensional objects under regular incoherent illumination. In our implementation, we apply parallel computation scheme using the graphic processing unit, accelerating the processing speed. Using enhanced speed of hologram capture, we also implement a pseudo real-time hologram capture and optical reconstruction system. The overall operation speed is measured to be 1 frame per second.

Investigation of self-adaptive LED surgical lighting based on entropy contrast enhancing method

NASA Astrophysics Data System (ADS)

Liu, Peng; Wang, Huihui; Zhang, Yaqin; Shen, Junfei; Wu, Rengmao; Zheng, Zhenrong; Li, Haifeng; Liu, Xu

2014-05-01

Investigation was performed to explore the possibility of enhancing contrast by varying the spectral distribution (SPD) of the surgical lighting. The illumination scenes with different SPDs were generated by the combination of a self-adaptive white light optimization method and the LED ceiling system, the images of biological sample are taken by a CCD camera and then processed by an 'Entropy' based contrast evaluation model which is proposed specific for surgery occasion. Compared with the neutral white LED based and traditional algorithm based image enhancing methods, the illumination based enhancing method turns out a better performance in contrast enhancing and improves the average contrast value about 9% and 6%, respectively. This low cost method is simple, practicable, and thus may provide an alternative solution for the expensive visual facility medical instruments.

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.

Underwater image enhancement through depth estimation based on random forest

NASA Astrophysics Data System (ADS)

Tai, Shen-Chuan; Tsai, Ting-Chou; Huang, Jyun-Han

2017-11-01

Light absorption and scattering in underwater environments can result in low-contrast images with a distinct color cast. This paper proposes a systematic framework for the enhancement of underwater images. Light transmission is estimated using the random forest algorithm. RGB values, luminance, color difference, blurriness, and the dark channel are treated as features in training and estimation. Transmission is calculated using an ensemble machine learning algorithm to deal with a variety of conditions encountered in underwater environments. A color compensation and contrast enhancement algorithm based on depth information was also developed with the aim of improving the visual quality of underwater images. Experimental results demonstrate that the proposed scheme outperforms existing methods with regard to subjective visual quality as well as objective measurements.

Bone surface enhancement in ultrasound images using a new Doppler-based acquisition/processing method.

PubMed

Yang, Xu; Tang, Songyuan; Tasciotti, Ennio; Righetti, Raffaella

2018-01-17

Ultrasound (US) imaging has long been considered as a potential aid in orthopedic surgeries. US technologies are safe, portable and do not use radiations. This would make them a desirable tool for real-time assessment of fractures and to monitor fracture healing. However, image quality of US imaging methods in bone applications is limited by speckle, attenuation, shadow, multiple reflections and other imaging artifacts. While bone surfaces typically appear in US images as somewhat 'brighter' than soft tissue, they are often not easily distinguishable from the surrounding tissue. Therefore, US imaging methods aimed at segmenting bone surfaces need enhancement in image contrast prior to segmentation to improve the quality of the detected bone surface. In this paper, we present a novel acquisition/processing technique for bone surface enhancement in US images. Inspired by elastography and Doppler imaging methods, this technique takes advantage of the difference between the mechanical and acoustic properties of bones and those of soft tissues to make the bone surface more easily distinguishable in US images. The objective of this technique is to facilitate US-based bone segmentation methods and improve the accuracy of their outcomes. The newly proposed technique is tested both in in vitro and in vivo experiments. The results of these preliminary experiments suggest that the use of the proposed technique has the potential to significantly enhance the detectability of bone surfaces in noisy ultrasound images.

Bone surface enhancement in ultrasound images using a new Doppler-based acquisition/processing method

NASA Astrophysics Data System (ADS)

Yang, Xu; Tang, Songyuan; Tasciotti, Ennio; Righetti, Raffaella

2018-01-01

Ultrasound (US) imaging has long been considered as a potential aid in orthopedic surgeries. US technologies are safe, portable and do not use radiations. This would make them a desirable tool for real-time assessment of fractures and to monitor fracture healing. However, image quality of US imaging methods in bone applications is limited by speckle, attenuation, shadow, multiple reflections and other imaging artifacts. While bone surfaces typically appear in US images as somewhat ‘brighter’ than soft tissue, they are often not easily distinguishable from the surrounding tissue. Therefore, US imaging methods aimed at segmenting bone surfaces need enhancement in image contrast prior to segmentation to improve the quality of the detected bone surface. In this paper, we present a novel acquisition/processing technique for bone surface enhancement in US images. Inspired by elastography and Doppler imaging methods, this technique takes advantage of the difference between the mechanical and acoustic properties of bones and those of soft tissues to make the bone surface more easily distinguishable in US images. The objective of this technique is to facilitate US-based bone segmentation methods and improve the accuracy of their outcomes. The newly proposed technique is tested both in in vitro and in vivo experiments. The results of these preliminary experiments suggest that the use of the proposed technique has the potential to significantly enhance the detectability of bone surfaces in noisy ultrasound images.

Image processing via level set curvature flow

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

Malladi, R.; Sethian, J.A.

We present a controlled image smoothing and enhancement method based on a curvature flow interpretation of the geometric heat equation. Compared to existing techniques, the model has several distinct advantages. (i) It contains just one enhancement parameter. (ii) The scheme naturally inherits a stopping criterion from the image; continued application of the scheme produces no further change. (iii) The method is one of the fastest possible schemes based on a curvature-controlled approach. 15 ref., 6 figs.

Wavelength-Adaptive Dehazing Using Histogram Merging-Based Classification for UAV Images

PubMed Central

Yoon, Inhye; Jeong, Seokhwa; Jeong, Jaeheon; Seo, Doochun; Paik, Joonki

2015-01-01

Since incoming light to an unmanned aerial vehicle (UAV) platform can be scattered by haze and dust in the atmosphere, the acquired image loses the original color and brightness of the subject. Enhancement of hazy images is an important task in improving the visibility of various UAV images. This paper presents a spatially-adaptive dehazing algorithm that merges color histograms with consideration of the wavelength-dependent atmospheric turbidity. Based on the wavelength-adaptive hazy image acquisition model, the proposed dehazing algorithm consists of three steps: (i) image segmentation based on geometric classes; (ii) generation of the context-adaptive transmission map; and (iii) intensity transformation for enhancing a hazy UAV image. The major contribution of the research is a novel hazy UAV image degradation model by considering the wavelength of light sources. In addition, the proposed transmission map provides a theoretical basis to differentiate visually important regions from others based on the turbidity and merged classification results. PMID:25808767

A novel image enhancement algorithm based on stationary wavelet transform for infrared thermography to the de-bonding defect in solid rocket motors

NASA Astrophysics Data System (ADS)

Liu, Tao; Zhang, Wei; Yan, Shaoze

2015-10-01

In this paper, a multi-scale image enhancement algorithm based on low-passing filtering and nonlinear transformation is proposed for infrared testing image of the de-bonding defect in solid propellant rocket motors. Infrared testing images with high-level noise and low contrast are foundations for identifying defects and calculating the defects size. In order to improve quality of the infrared image, according to distribution properties of the detection image, within framework of stationary wavelet transform, the approximation coefficients at suitable decomposition level is processed by index low-passing filtering by using Fourier transform, after that, the nonlinear transformation is applied to further process the figure to improve the picture contrast. To verify validity of the algorithm, the image enhancement algorithm is applied to infrared testing pictures of two specimens with de-bonding defect. Therein, one specimen is made of a type of high-strength steel, and the other is a type of carbon fiber composite. As the result shown, in the images processed by the image enhancement algorithm presented in the paper, most of noises are eliminated, and contrast between defect areas and normal area is improved greatly; in addition, by using the binary picture of the processed figure, the continuous defect edges can be extracted, all of which show the validity of the algorithm. The paper provides a well-performing image enhancement algorithm for the infrared thermography.

Image Quality Improvement in Adaptive Optics Scanning Laser Ophthalmoscopy Assisted Capillary Visualization Using B-spline-based Elastic Image Registration

PubMed Central

Uji, Akihito; Ooto, Sotaro; Hangai, Masanori; Arichika, Shigeta; Yoshimura, Nagahisa

2013-01-01

Purpose To investigate the effect of B-spline-based elastic image registration on adaptive optics scanning laser ophthalmoscopy (AO-SLO)-assisted capillary visualization. Methods AO-SLO videos were acquired from parafoveal areas in the eyes of healthy subjects and patients with various diseases. After nonlinear image registration, the image quality of capillary images constructed from AO-SLO videos using motion contrast enhancement was compared before and after B-spline-based elastic (nonlinear) image registration performed using ImageJ. For objective comparison of image quality, contrast-to-noise ratios (CNRS) for vessel images were calculated. For subjective comparison, experienced ophthalmologists ranked images on a 5-point scale. Results All AO-SLO videos were successfully stabilized by elastic image registration. CNR was significantly higher in capillary images stabilized by elastic image registration than in those stabilized without registration. The average ratio of CNR in images with elastic image registration to CNR in images without elastic image registration was 2.10 ± 1.73, with no significant difference in the ratio between patients and healthy subjects. Improvement of image quality was also supported by expert comparison. Conclusions Use of B-spline-based elastic image registration in AO-SLO-assisted capillary visualization was effective for enhancing image quality both objectively and subjectively. PMID:24265796

Adaptive Intuitionistic Fuzzy Enhancement of Brain Tumor MR Images

NASA Astrophysics Data System (ADS)

Deng, He; Deng, Wankai; Sun, Xianping; Ye, Chaohui; Zhou, Xin

2016-10-01

Image enhancement techniques are able to improve the contrast and visual quality of magnetic resonance (MR) images. However, conventional methods cannot make up some deficiencies encountered by respective brain tumor MR imaging modes. In this paper, we propose an adaptive intuitionistic fuzzy sets-based scheme, called as AIFE, which takes information provided from different MR acquisitions and tries to enhance the normal and abnormal structural regions of the brain while displaying the enhanced results as a single image. The AIFE scheme firstly separates an input image into several sub images, then divides each sub image into object and background areas. After that, different novel fuzzification, hyperbolization and defuzzification operations are implemented on each object/background area, and finally an enhanced result is achieved via nonlinear fusion operators. The fuzzy implementations can be processed in parallel. Real data experiments demonstrate that the AIFE scheme is not only effectively useful to have information from images acquired with different MR sequences fused in a single image, but also has better enhancement performance when compared to conventional baseline algorithms. This indicates that the proposed AIFE scheme has potential for improving the detection and diagnosis of brain tumors.

An Approach to Improve the Quality of Infrared Images of Vein-Patterns

PubMed Central

Lin, Chih-Lung

2011-01-01

This study develops an approach to improve the quality of infrared (IR) images of vein-patterns, which usually have noise, low contrast, low brightness and small objects of interest, thus requiring preprocessing to improve their quality. The main characteristics of the proposed approach are that no prior knowledge about the IR image is necessary and no parameters must be preset. Two main goals are sought: impulse noise reduction and adaptive contrast enhancement technologies. In our study, a fast median-based filter (FMBF) is developed as a noise reduction method. It is based on an IR imaging mechanism to detect the noisy pixels and on a modified median-based filter to remove the noisy pixels in IR images. FMBF has the advantage of a low computation load. In addition, FMBF can retain reasonably good edges and texture information when the size of the filter window increases. The most important advantage is that the peak signal-to-noise ratio (PSNR) caused by FMBF is higher than the PSNR caused by the median filter. A hybrid cumulative histogram equalization (HCHE) is proposed for adaptive contrast enhancement. HCHE can automatically generate a hybrid cumulative histogram (HCH) based on two different pieces of information about the image histogram. HCHE can improve the enhancement effect on hot objects rather than background. The experimental results are addressed and demonstrate that the proposed approach is feasible for use as an effective and adaptive process for enhancing the quality of IR vein-pattern images. PMID:22247674

An approach to improve the quality of infrared images of vein-patterns.

PubMed

Lin, Chih-Lung

2011-01-01

This study develops an approach to improve the quality of infrared (IR) images of vein-patterns, which usually have noise, low contrast, low brightness and small objects of interest, thus requiring preprocessing to improve their quality. The main characteristics of the proposed approach are that no prior knowledge about the IR image is necessary and no parameters must be preset. Two main goals are sought: impulse noise reduction and adaptive contrast enhancement technologies. In our study, a fast median-based filter (FMBF) is developed as a noise reduction method. It is based on an IR imaging mechanism to detect the noisy pixels and on a modified median-based filter to remove the noisy pixels in IR images. FMBF has the advantage of a low computation load. In addition, FMBF can retain reasonably good edges and texture information when the size of the filter window increases. The most important advantage is that the peak signal-to-noise ratio (PSNR) caused by FMBF is higher than the PSNR caused by the median filter. A hybrid cumulative histogram equalization (HCHE) is proposed for adaptive contrast enhancement. HCHE can automatically generate a hybrid cumulative histogram (HCH) based on two different pieces of information about the image histogram. HCHE can improve the enhancement effect on hot objects rather than background. The experimental results are addressed and demonstrate that the proposed approach is feasible for use as an effective and adaptive process for enhancing the quality of IR vein-pattern images.

Image Processing for Binarization Enhancement via Fuzzy Reasoning

NASA Technical Reports Server (NTRS)

Dominguez, Jesus A. (Inventor)

2009-01-01

A technique for enhancing a gray-scale image to improve conversions of the image to binary employs fuzzy reasoning. In the technique, pixels in the image are analyzed by comparing the pixel's gray scale value, which is indicative of its relative brightness, to the values of pixels immediately surrounding the selected pixel. The degree to which each pixel in the image differs in value from the values of surrounding pixels is employed as the variable in a fuzzy reasoning-based analysis that determines an appropriate amount by which the selected pixel's value should be adjusted to reduce vagueness and ambiguity in the image and improve retention of information during binarization of the enhanced gray-scale image.

Application of Fuzzy Reasoning for Filtering and Enhancement of Ultrasonic Images

NASA Technical Reports Server (NTRS)

Sacha, J. P.; Cios, K. J.; Roth, D. J.; Berke, L.; Vary, A.

1994-01-01

This paper presents a new type of an adaptive fuzzy operator for detection of isolated abnormalities, and enhancement of raw ultrasonic images. Fuzzy sets used in decision rules are defined for each image based on empirical statistics of the color intensities. Examples of the method are also presented in the paper.

Generalized image contrast enhancement technique based on the Heinemann contrast discrimination model

NASA Astrophysics Data System (ADS)

Liu, Hong; Nodine, Calvin F.

1996-07-01

This paper presents a generalized image contrast enhancement technique, which equalizes the perceived brightness distribution based on the Heinemann contrast discrimination model. It is based on the mathematically proven existence of a unique solution to a nonlinear equation, and is formulated with easily tunable parameters. The model uses a two-step log-log representation of luminance contrast between targets and surround in a luminous background setting. The algorithm consists of two nonlinear gray scale mapping functions that have seven parameters, two of which are adjustable Heinemann constants. Another parameter is the background gray level. The remaining four parameters are nonlinear functions of the gray-level distribution of the given image, and can be uniquely determined once the previous three are set. Tests have been carried out to demonstrate the effectiveness of the algorithm for increasing the overall contrast of radiology images. The traditional histogram equalization can be reinterpreted as an image enhancement technique based on the knowledge of human contrast perception. In fact, it is a special case of the proposed algorithm.

Regularized Reconstruction of Dynamic Contrast-Enhanced MR Images for Evaluation of Breast Lesions

DTIC Science & Technology

2011-01-01

Magnetic resonance imaging contrast-enhanced relaxometry of breast tumors: an MRI multicenter investigation concerning 100 patients,” Mag. Res. Im., vol...The overall goal of this project was to develop, implement, and evaluate methods for im- proving image quality in dynamic magnetic resonance imaging ...Olafsson, H. R. Shi, and D. C. Noll, “Toeplitz-based iterative image reconstruction for MRI with correction for magnetic field inhomogeneity,” IEEE

Content dependent selection of image enhancement parameters for mobile displays

NASA Astrophysics Data System (ADS)

Lee, Yoon-Gyoo; Kang, Yoo-Jin; Kim, Han-Eol; Kim, Ka-Hee; Kim, Choon-Woo

2011-01-01

Mobile devices such as cellular phones and portable multimedia player with capability of playing terrestrial digital multimedia broadcasting (T-DMB) contents have been introduced into consumer market. In this paper, content dependent image quality enhancement method for sharpness and colorfulness and noise reduction is presented to improve perceived image quality on mobile displays. Human visual experiments are performed to analyze viewers' preference. Relationship between the objective measures and the optimal values of image control parameters are modeled by simple lookup tables based on the results of human visual experiments. Content dependent values of image control parameters are determined based on the calculated measures and predetermined lookup tables. Experimental results indicate that dynamic selection of image control parameters yields better image quality.

Preliminary studies of enhanced contrast radiography in anatomy and embryology of insects with Elettra synchrotron light

NASA Astrophysics Data System (ADS)

Hönnicke, M. G.; Foerster, L. A.; Navarro-Silva, M. A.; Menk, R.-H.; Rigon, L.; Cusatis, C.

2005-08-01

Enhanced contrast X-ray imaging is achieved by exploiting the real part of the refraction index, which is responsible for the phase shifts, in addition to the imaginary part, which is responsible for the absorption. Such techniques are called X-ray phase contrast imaging. An analyzer-based X-ray phase contrast imaging set-up with Diffraction Enhanced Imaging processing (DEI) were used for preliminary studies in anatomy and embryology of insects. Parasitized stinkbug and moth eggs used as control agents of pests in vegetables and adult stinkbugs and mosquitoes ( Aedes aegypti) were used as samples. The experimental setup was mounted in the SYRMEP beamline at ELETTRA. Images were obtained using a high spatial resolution CCD detector (pixel size 14×14 μm 2) coupled with magnifying optics. Analyzer-based X-ray phase contrast images (PCI) and edge detection images show contrast and details not observed with conventional synchrotron radiography and open the possibility for future study in the embryonic development of insects.

Image enhancement and color constancy for a vehicle-mounted change detection system

NASA Astrophysics Data System (ADS)

Tektonidis, Marco; Monnin, David

2016-10-01

Vehicle-mounted change detection systems allow to improve situational awareness on outdoor itineraries of inter- est. Since the visibility of acquired images is often affected by illumination effects (e.g., shadows) it is important to enhance local contrast. For the analysis and comparison of color images depicting the same scene at different time points it is required to compensate color and lightness inconsistencies caused by the different illumination conditions. We have developed an approach for image enhancement and color constancy based on the center/surround Retinex model and the Gray World hypothesis. The combination of the two methods using a color processing function improves color rendition, compared to both methods. The use of stacked integral images (SII) allows to efficiently perform local image processing. Our combined Retinex/Gray World approach has been successfully applied to image sequences acquired on outdoor itineraries at different time points and a comparison with previous Retinex-based approaches has been carried out.

Scene-based nonuniformity correction and enhancement: pixel statistics and subpixel motion.

PubMed

Zhao, Wenyi; Zhang, Chao

2008-07-01

We propose a framework for scene-based nonuniformity correction (NUC) and nonuniformity correction and enhancement (NUCE) that is required for focal-plane array-like sensors to obtain clean and enhanced-quality images. The core of the proposed framework is a novel registration-based nonuniformity correction super-resolution (NUCSR) method that is bootstrapped by statistical scene-based NUC methods. Based on a comprehensive imaging model and an accurate parametric motion estimation, we are able to remove severe/structured nonuniformity and in the presence of subpixel motion to simultaneously improve image resolution. One important feature of our NUCSR method is the adoption of a parametric motion model that allows us to (1) handle many practical scenarios where parametric motions are present and (2) carry out perfect super-resolution in principle by exploring available subpixel motions. Experiments with real data demonstrate the efficiency of the proposed NUCE framework and the effectiveness of the NUCSR method.

Three-photon tissue imaging using moxifloxacin.

PubMed

Lee, Seunghun; Lee, Jun Ho; Wang, Taejun; Jang, Won Hyuk; Yoon, Yeoreum; Kim, Bumju; Jun, Yong Woong; Kim, Myoung Joon; Kim, Ki Hean

2018-06-20

Moxifloxacin is an antibiotic used in clinics and has recently been used as a clinically compatible cell-labeling agent for two-photon (2P) imaging. Although 2P imaging with moxifloxacin labeling visualized cells inside tissues using enhanced fluorescence, the imaging depth was quite limited because of the relatively short excitation wavelength (<800 nm) used. In this study, the feasibility of three-photon (3P) excitation of moxifloxacin using a longer excitation wavelength and moxifloxacin-based 3P imaging were tested to increase the imaging depth. Moxifloxacin fluorescence via 3P excitation was detected at a >1000 nm excitation wavelength. After obtaining the excitation and emission spectra of moxifloxacin, moxifloxacin-based 3P imaging was applied to ex vivo mouse bladder and ex vivo mouse small intestine tissues and compared with moxifloxacin-based 2P imaging by switching the excitation wavelength of a Ti:sapphire oscillator between near 1030 and 780 nm. Both moxifloxacin-based 2P and 3P imaging visualized cellular structures in the tissues via moxifloxacin labeling, but the image contrast was better with 3P imaging than with 2P imaging at the same imaging depths. The imaging speed and imaging depth of moxifloxacin-based 3P imaging using a Ti:sapphire oscillator were limited by insufficient excitation power. Therefore, we constructed a new system for moxifloxacin-based 3P imaging using a high-energy Yb fiber laser at 1030 nm and used it for in vivo deep tissue imaging of a mouse small intestine. Moxifloxacin-based 3P imaging could be useful for clinical applications with enhanced imaging depth.

Enhancement of multimodality texture-based prediction models via optimization of PET and MR image acquisition protocols: a proof of concept

NASA Astrophysics Data System (ADS)

Vallières, Martin; Laberge, Sébastien; Diamant, André; El Naqa, Issam

2017-11-01

Texture-based radiomic models constructed from medical images have the potential to support cancer treatment management via personalized assessment of tumour aggressiveness. While the identification of stable texture features under varying imaging settings is crucial for the translation of radiomics analysis into routine clinical practice, we hypothesize in this work that a complementary optimization of image acquisition parameters prior to texture feature extraction could enhance the predictive performance of texture-based radiomic models. As a proof of concept, we evaluated the possibility of enhancing a model constructed for the early prediction of lung metastases in soft-tissue sarcomas by optimizing PET and MR image acquisition protocols via computerized simulations of image acquisitions with varying parameters. Simulated PET images from 30 STS patients were acquired by varying the extent of axial data combined per slice (‘span’). Simulated T 1-weighted and T 2-weighted MR images were acquired by varying the repetition time and echo time in a spin-echo pulse sequence, respectively. We analyzed the impact of the variations of PET and MR image acquisition parameters on individual textures, and we investigated how these variations could enhance the global response and the predictive properties of a texture-based model. Our results suggest that it is feasible to identify an optimal set of image acquisition parameters to improve prediction performance. The model constructed with textures extracted from simulated images acquired with a standard clinical set of acquisition parameters reached an average AUC of 0.84 +/- 0.01 in bootstrap testing experiments. In comparison, the model performance significantly increased using an optimal set of image acquisition parameters (p = 0.04 ), with an average AUC of 0.89 +/- 0.01 . Ultimately, specific acquisition protocols optimized to generate superior radiomics measurements for a given clinical problem could be developed and standardized via dedicated computer simulations and thereafter validated using clinical scanners.

Noninvasive enhanced mid-IR imaging of breast cancer development in vivo

NASA Astrophysics Data System (ADS)

Case, Jason R.; Young, Madison A.; Dréau, D.; Trammell, Susan R.

2015-11-01

Lumpectomy coupled with radiation therapy and/or chemotherapy is commonly used to treat breast cancer patients. We are developing an enhanced thermal IR imaging technique that has the potential to provide real-time imaging to guide tissue excision during a lumpectomy by delineating tumor margins. This enhanced thermal imaging method is a combination of IR imaging (8 to 10 μm) and selective heating of blood (˜0.5°C) relative to surrounding water-rich tissue using LED sources at low powers. Postacquisition processing of these images highlights temporal changes in temperature and the presence of vascular structures. In this study, fluorescent, standard thermal, and enhanced thermal imaging modalities, as well as physical caliper measurements, were used to monitor breast cancer tumor volumes over a 30-day study period in 19 mice implanted with 4T1-RFP tumor cells. Tumor volumes calculated from fluorescent imaging follow an exponential growth curve for the first 22 days of the study. Cell necrosis affected the tumor volume estimates based on the fluorescent images after day 22. The tumor volumes estimated from enhanced thermal imaging, standard thermal imaging, and caliper measurements all show exponential growth over the entire study period. A strong correlation was found between tumor volumes estimated using fluorescent imaging, standard IR imaging, and caliper measurements with enhanced thermal imaging, indicating that enhanced thermal imaging monitors tumor growth. Further, the enhanced IR images reveal a corona of bright emission along the edges of the tumor masses associated with the tumor margin. In the future, this IR technique might be used to estimate tumor margins in real time during surgical procedures.

An enhanced multi-view vertical line locus matching algorithm of object space ground primitives based on positioning consistency for aerial and space images

NASA Astrophysics Data System (ADS)

Zhang, Ka; Sheng, Yehua; Wang, Meizhen; Fu, Suxia

2018-05-01

The traditional multi-view vertical line locus (TMVLL) matching method is an object-space-based method that is commonly used to directly acquire spatial 3D coordinates of ground objects in photogrammetry. However, the TMVLL method can only obtain one elevation and lacks an accurate means of validating the matching results. In this paper, we propose an enhanced multi-view vertical line locus (EMVLL) matching algorithm based on positioning consistency for aerial or space images. The algorithm involves three components: confirming candidate pixels of the ground primitive in the base image, multi-view image matching based on the object space constraints for all candidate pixels, and validating the consistency of the object space coordinates with the multi-view matching result. The proposed algorithm was tested using actual aerial images and space images. Experimental results show that the EMVLL method successfully solves the problems associated with the TMVLL method, and has greater reliability, accuracy and computing efficiency.

Integral imaging based light field display with enhanced viewing resolution using holographic diffuser

NASA Astrophysics Data System (ADS)

Yan, Zhiqiang; Yan, Xingpeng; Jiang, Xiaoyu; Gao, Hui; Wen, Jun

2017-11-01

An integral imaging based light field display method is proposed by use of holographic diffuser, and enhanced viewing resolution is gained over conventional integral imaging systems. The holographic diffuser is fabricated with controlled diffusion characteristics, which interpolates the discrete light field of the reconstructed points to approximate the original light field. The viewing resolution can thus be improved and independent of the limitation imposed by Nyquist sampling frequency. An integral imaging system with low Nyquist sampling frequency is constructed, and reconstructed scenes of high viewing resolution using holographic diffuser are demonstrated, verifying the feasibility of the method.

Color Image Enhancement Using Multiscale Retinex Based on Particle Swarm Optimization Method

NASA Astrophysics Data System (ADS)

Matin, F.; Jeong, Y.; Kim, K.; Park, K.

2018-01-01

This paper introduces, a novel method for the image enhancement using multiscale retinex and practical swarm optimization. Multiscale retinex is widely used image enhancement technique which intemperately pertains on parameters such as Gaussian scales, gain and offset, etc. To achieve the privileged effect, the parameters need to be tuned manually according to the image. In order to handle this matter, a developed retinex algorithm based on PSO has been used. The PSO method adjusted the parameters for multiscale retinex with chromaticity preservation (MSRCP) attains better outcome to compare with other existing methods. The experimental result indicates that the proposed algorithm is an efficient one and not only provides true color loyalty in low light conditions but also avoid color distortion at the same time.

Effects of empty bins on image upscaling in capsule endoscopy

NASA Astrophysics Data System (ADS)

Rukundo, Olivier

2017-07-01

This paper presents a preliminary study of the effect of empty bins on image upscaling in capsule endoscopy. The presented study was conducted based on results of existing contrast enhancement and interpolation methods. A low contrast enhancement method based on pixels consecutiveness and modified bilinear weighting scheme has been developed to distinguish between necessary empty bins and unnecessary empty bins in the effort to minimize the number of empty bins in the input image, before further processing. Linear interpolation methods have been used for upscaling input images with stretched histograms. Upscaling error differences and similarity indices between pairs of interpolation methods have been quantified using the mean squared error and feature similarity index techniques. Simulation results demonstrated more promising effects using the developed method than other contrast enhancement methods mentioned.

Color enhancement and image defogging in HSI based on Retinex model

NASA Astrophysics Data System (ADS)

Gao, Han; Wei, Ping; Ke, Jun

2015-08-01

Retinex is a luminance perceptual algorithm based on color consistency. It has a good performance in color enhancement. But in some cases, the traditional Retinex algorithms, both Single-Scale Retinex(SSR) and Multi-Scale Retinex(MSR) in RGB color space, do not work well and will cause color deviation. To solve this problem, we present improved SSR and MSR algorithms. Compared to other Retinex algorithms, we implement Retinex algorithms in HSI(Hue, Saturation, Intensity) color space, and use a parameter αto improve quality of the image. Moreover, the algorithms presented in this paper has a good performance in image defogging. Contrasted with traditional Retinex algorithms, we use intensity channel to obtain reflection information of an image. The intensity channel is processed using a Gaussian center-surround image filter to get light information, which should be removed from intensity channel. After that, we subtract the light information from intensity channel to obtain the reflection image, which only includes the attribute of the objects in image. Using the reflection image and a parameter α, which is an arbitrary scale factor set manually, we improve the intensity channel, and complete the color enhancement. Our experiments show that this approach works well compared with existing methods for color enhancement. Besides a better performance in color deviation problem and image defogging, a visible improvement in the image quality for human contrast perception is also observed.

Exemplar-Based Image and Video Stylization Using Fully Convolutional Semantic Features.

PubMed

Zhu, Feida; Yan, Zhicheng; Bu, Jiajun; Yu, Yizhou

2017-05-10

Color and tone stylization in images and videos strives to enhance unique themes with artistic color and tone adjustments. It has a broad range of applications from professional image postprocessing to photo sharing over social networks. Mainstream photo enhancement softwares, such as Adobe Lightroom and Instagram, provide users with predefined styles, which are often hand-crafted through a trial-and-error process. Such photo adjustment tools lack a semantic understanding of image contents and the resulting global color transform limits the range of artistic styles it can represent. On the other hand, stylistic enhancement needs to apply distinct adjustments to various semantic regions. Such an ability enables a broader range of visual styles. In this paper, we first propose a novel deep learning architecture for exemplar-based image stylization, which learns local enhancement styles from image pairs. Our deep learning architecture consists of fully convolutional networks (FCNs) for automatic semantics-aware feature extraction and fully connected neural layers for adjustment prediction. Image stylization can be efficiently accomplished with a single forward pass through our deep network. To extend our deep network from image stylization to video stylization, we exploit temporal superpixels (TSPs) to facilitate the transfer of artistic styles from image exemplars to videos. Experiments on a number of datasets for image stylization as well as a diverse set of video clips demonstrate the effectiveness of our deep learning architecture.

3D Gabor wavelet based vessel filtering of photoacoustic images.

PubMed

Haq, Israr Ul; Nagoaka, Ryo; Makino, Takahiro; Tabata, Takuya; Saijo, Yoshifumi

2016-08-01

Filtering and segmentation of vasculature is an important issue in medical imaging. The visualization of vasculature is crucial for the early diagnosis and therapy in numerous medical applications. This paper investigates the use of Gabor wavelet to enhance the effect of vasculature while eliminating the noise due to size, sensitivity and aperture of the detector in 3D Optical Resolution Photoacoustic Microscopy (OR-PAM). A detailed multi-scale analysis of wavelet filtering and Hessian based method is analyzed for extracting vessels of different sizes since the blood vessels usually vary with in a range of radii. The proposed algorithm first enhances the vasculature in the image and then tubular structures are classified by eigenvalue decomposition of the local Hessian matrix at each voxel in the image. The algorithm is tested on non-invasive experiments, which shows appreciable results to enhance vasculature in photo-acoustic images.

Resolution enhancement of wide-field interferometric microscopy by coupled deep autoencoders.

PubMed

Işil, Çağatay; Yorulmaz, Mustafa; Solmaz, Berkan; Turhan, Adil Burak; Yurdakul, Celalettin; Ünlü, Selim; Ozbay, Ekmel; Koç, Aykut

2018-04-01

Wide-field interferometric microscopy is a highly sensitive, label-free, and low-cost biosensing imaging technique capable of visualizing individual biological nanoparticles such as viral pathogens and exosomes. However, further resolution enhancement is necessary to increase detection and classification accuracy of subdiffraction-limited nanoparticles. In this study, we propose a deep-learning approach, based on coupled deep autoencoders, to improve resolution of images of L-shaped nanostructures. During training, our method utilizes microscope image patches and their corresponding manual truth image patches in order to learn the transformation between them. Following training, the designed network reconstructs denoised and resolution-enhanced image patches for unseen input.

Finger Vein Segmentation from Infrared Images Based on a Modified Separable Mumford Shah Model and Local Entropy Thresholding

PubMed Central

Dermatas, Evangelos

2015-01-01

A novel method for finger vein pattern extraction from infrared images is presented. This method involves four steps: preprocessing which performs local normalization of the image intensity, image enhancement, image segmentation, and finally postprocessing for image cleaning. In the image enhancement step, an image which will be both smooth and similar to the original is sought. The enhanced image is obtained by minimizing the objective function of a modified separable Mumford Shah Model. Since, this minimization procedure is computationally intensive for large images, a local application of the Mumford Shah Model in small window neighborhoods is proposed. The finger veins are located in concave nonsmooth regions and, so, in order to distinct them from the other tissue parts, all the differences between the smooth neighborhoods, obtained by the local application of the model, and the corresponding windows of the original image are added. After that, veins in the enhanced image have been sufficiently emphasized. Thus, after image enhancement, an accurate segmentation can be obtained readily by a local entropy thresholding method. Finally, the resulted binary image may suffer from some misclassifications and, so, a postprocessing step is performed in order to extract a robust finger vein pattern. PMID:26120357

A novel ship CFAR detection algorithm based on adaptive parameter enhancement and wake-aided detection in SAR images

NASA Astrophysics Data System (ADS)

Meng, Siqi; Ren, Kan; Lu, Dongming; Gu, Guohua; Chen, Qian; Lu, Guojun

2018-03-01

Synthetic aperture radar (SAR) is an indispensable and useful method for marine monitoring. With the increase of SAR sensors, high resolution images can be acquired and contain more target structure information, such as more spatial details etc. This paper presents a novel adaptive parameter transform (APT) domain constant false alarm rate (CFAR) to highlight targets. The whole method is based on the APT domain value. Firstly, the image is mapped to the new transform domain by the algorithm. Secondly, the false candidate target pixels are screened out by the CFAR detector to highlight the target ships. Thirdly, the ship pixels are replaced by the homogeneous sea pixels. And then, the enhanced image is processed by Niblack algorithm to obtain the wake binary image. Finally, normalized Hough transform (NHT) is used to detect wakes in the binary image, as a verification of the presence of the ships. Experiments on real SAR images validate that the proposed transform does enhance the target structure and improve the contrast of the image. The algorithm has a good performance in the ship and ship wake detection.

Non-invasive thermal IR detection of breast tumor development in vivo

NASA Astrophysics Data System (ADS)

Case, Jason R.; Young, Madison A.; Dréau, D.; Trammell, Susan R.

2015-03-01

Lumpectomy coupled with radiation therapy and/or chemotherapy comprises the treatment of breast cancer for many patients. We are developing an enhanced thermal IR imaging technique that can be used in real-time to guide tissue excision during a lumpectomy. This novel enhanced thermal imaging method is a combination of IR imaging (8- 10 μm) and selective heating of blood (~0.5 °C) relative to surrounding water-rich tissue using LED sources at low powers. Post-acquisition processing of these images highlights temporal changes in temperature and is sensitive to the presence of vascular structures. In this study, fluorescent and enhanced thermal imaging modalities were used to estimate breast cancer tumor volumes as a function of time in 19 murine subjects over a 30-day study period. Tumor volumes calculated from fluorescent imaging follow an exponential growth curve for the first 22 days of the study. Cell necrosis affected the tumor volume estimates based on the fluorescent images after Day 22. The tumor volumes estimated from enhanced thermal imaging show exponential growth over the entire study period. A strong correlation was found between tumor volumes estimated using fluorescent imaging and the enhanced IR images, indicating that enhanced thermal imaging is capable monitoring tumor growth. Further, the enhanced IR images reveal a corona of bright emission along the edges of the tumor masses. This novel IR technique could be used to estimate tumor margins in real-time during surgical procedures.

Applying Amide Proton Transfer MR Imaging to Hybrid Brain PET/MR: Concordance with Gadolinium Enhancement and Added Value to [18F]FDG PET.

PubMed

Sun, Hongzan; Xin, Jun; Zhou, Jinyuan; Lu, Zaiming; Guo, Qiyong

2018-06-01

The purpose of this study is to evaluate the diagnostic concordance and metric correlations of amide proton transfer (APT) imaging with gadolinium-enhanced magnetic resonance imaging (MRI) and 2-deoxy-2-[ 18 F-]fluoro-D-glucose ([ 18 F]FDG) positron emission tomography (PET), using hybrid brain PET/MRI. Twenty-one subjects underwent brain gadolinium-enhanced [ 18 F]FDG PET/MRI prospectively. Imaging accuracy was compared between unenhanced MRI, MRI with enhancement, APT-weighted (APTW) images, and PET based on six diagnostic criteria. Among tumors, the McNemar test was further used for concordance assessment between gadolinium-enhanced imaging, APT imaging, and [ 18 F]FDG PET. As well, the relation of metrics between APT imaging and PET was analyzed by the Pearson correlation analysis. APT imaging and gadolinium-enhanced MRI showed superior and similar diagnostic accuracy. APTW signal intensity and gadolinium enhancement were concordant in 19 tumors (100 %), while high [ 18 F]FDG avidity was shown in only 12 (63.2 %). For the metrics from APT imaging and PET, there was significant correlation for 13 hypermetabolic tumors (P < 0.05) and no correlation for the remaining six [ 18 F]FDG-avid tumors. APT imaging can be used to increase diagnostic accuracy with no need to administer gadolinium chelates. APT imaging may provide an added value to [ 18 F]FDG PET in the evaluation of tumor metabolic activity during brain PET/MR studies.

Bas-relief map using texture analysis with application to live enhancement of ultrasound images.

PubMed

Du, Huarui; Ma, Rui; Wang, Xiaoying; Zhang, Jue; Fang, Jing

2015-05-01

For ultrasound imaging, speckle is one of the most important factors in the degradation of contrast resolution because it masks meaningful texture and has the potential to interfere with diagnosis. It is expected that researchers would explore appropriate ways to reduce the speckle noise, to find the edges of structures and enhance weak borders between different organs in ultrasound imaging. Inspired by the principle of differential interference contrast microscopy, a "bas-relief map" is proposed that depicts the texture structure of ultrasound images. Based on a bas-relief map, an adaptive bas-relief filter was developed for ultrafast despeckling. Subsequently, an edge map was introduced to enhance the edges of images in real time. The holistic bas-relief map approach has been used experimentally with synthetic phantoms and digital ultrasound B-scan images of liver, kidney and gallbladder. Based on the visual inspection and the performance metrics of the despeckled images, it was found that the bas-relief map approach is capable of effectively reducing the speckle while significantly enhancing contrast and tissue boundaries for ultrasonic images, and its speckle reduction ability is comparable to that of Kuan, Lee and Frost filters. Meanwhile, the proposed technique could preserve more intra-region details compared with the popular speckle reducing anisotropic diffusion technique and more effectively enhance edges. In addition, the adaptive bas-relief filter was much less time consuming than the Kuan, Lee and Frost filter and speckle reducing anisotropic diffusion techniques. The bas-relief map strategy is effective for speckle reduction and live enhancement of ultrasound images, and can provide a valuable tool for clinical diagnosis. Copyright © 2015 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Limitations of contrast enhancement for infrared target identification

NASA Astrophysics Data System (ADS)

Du Bosq, Todd W.; Fanning, Jonathan D.

2009-05-01

Contrast enhancement and dynamic range compression are currently being used to improve the performance of infrared imagers by increasing the contrast between the target and the scene content. Automatic contrast enhancement techniques do not always achieve this improvement. In some cases, the contrast can increase to a level of target saturation. This paper assesses the range-performance effects of contrast enhancement for target identification as a function of image saturation. Human perception experiments were performed to determine field performance using contrast enhancement on the U.S. Army RDECOM CERDEC NVESD standard military eight target set using an un-cooled LWIR camera. The experiments compare the identification performance of observers viewing contrast enhancement processed images at various levels of saturation. Contrast enhancement is modeled in the U.S. Army thermal target acquisition model (NVThermIP) by changing the scene contrast temperature. The model predicts improved performance based on any improved target contrast, regardless of specific feature saturation or enhancement. The measured results follow the predicted performance based on the target task difficulty metric used in NVThermIP for the non-saturated cases. The saturated images reduce the information contained in the target and performance suffers. The model treats the contrast of the target as uniform over spatial frequency. As the contrast is enhanced, the model assumes that the contrast is enhanced uniformly over the spatial frequencies. After saturation, the spatial cues that differentiate one tank from another are located in a limited band of spatial frequencies. A frequency dependent treatment of target contrast is needed to predict performance of over-processed images.

Modeling the effects of contrast enhancement on target acquisition performance

NASA Astrophysics Data System (ADS)

Du Bosq, Todd W.; Fanning, Jonathan D.

2008-04-01

Contrast enhancement and dynamic range compression are currently being used to improve the performance of infrared imagers by increasing the contrast between the target and the scene content, by better utilizing the available gray levels either globally or locally. This paper assesses the range-performance effects of various contrast enhancement algorithms for target identification with well contrasted vehicles. Human perception experiments were performed to determine field performance using contrast enhancement on the U.S. Army RDECOM CERDEC NVESD standard military eight target set using an un-cooled LWIR camera. The experiments compare the identification performance of observers viewing linearly scaled images and various contrast enhancement processed images. Contrast enhancement is modeled in the US Army thermal target acquisition model (NVThermIP) by changing the scene contrast temperature. The model predicts improved performance based on any improved target contrast, regardless of feature saturation or enhancement. To account for the equivalent blur associated with each contrast enhancement algorithm, an additional effective MTF was calculated and added to the model. The measured results are compared with the predicted performance based on the target task difficulty metric used in NVThermIP.

Fast and robust wavelet-based dynamic range compression and contrast enhancement model with color restoration

NASA Astrophysics Data System (ADS)

Unaldi, Numan; Asari, Vijayan K.; Rahman, Zia-ur

2009-05-01

Recently we proposed a wavelet-based dynamic range compression algorithm to improve the visual quality of digital images captured from high dynamic range scenes with non-uniform lighting conditions. The fast image enhancement algorithm that provides dynamic range compression, while preserving the local contrast and tonal rendition, is also a good candidate for real time video processing applications. Although the colors of the enhanced images produced by the proposed algorithm are consistent with the colors of the original image, the proposed algorithm fails to produce color constant results for some "pathological" scenes that have very strong spectral characteristics in a single band. The linear color restoration process is the main reason for this drawback. Hence, a different approach is required for the final color restoration process. In this paper the latest version of the proposed algorithm, which deals with this issue is presented. The results obtained by applying the algorithm to numerous natural images show strong robustness and high image quality.

An enhanced MMW and SMMW/THz imaging system performance prediction and analysis tool for concealed weapon detection and pilotage obstacle avoidance

NASA Astrophysics Data System (ADS)

Murrill, Steven R.; Jacobs, Eddie L.; Franck, Charmaine C.; Petkie, Douglas T.; De Lucia, Frank C.

2015-10-01

The U.S. Army Research Laboratory (ARL) has continued to develop and enhance a millimeter-wave (MMW) and submillimeter- wave (SMMW)/terahertz (THz)-band imaging system performance prediction and analysis tool for both the detection and identification of concealed weaponry, and for pilotage obstacle avoidance. The details of the MATLAB-based model which accounts for the effects of all critical sensor and display components, for the effects of atmospheric attenuation, concealment material attenuation, and active illumination, were reported on at the 2005 SPIE Europe Security and Defence Symposium (Brugge). An advanced version of the base model that accounts for both the dramatic impact that target and background orientation can have on target observability as related to specular and Lambertian reflections captured by an active-illumination-based imaging system, and for the impact of target and background thermal emission, was reported on at the 2007 SPIE Defense and Security Symposium (Orlando). Further development of this tool that includes a MODTRAN-based atmospheric attenuation calculator and advanced system architecture configuration inputs that allow for straightforward performance analysis of active or passive systems based on scanning (single- or line-array detector element(s)) or staring (focal-plane-array detector elements) imaging architectures was reported on at the 2011 SPIE Europe Security and Defence Symposium (Prague). This paper provides a comprehensive review of a newly enhanced MMW and SMMW/THz imaging system analysis and design tool that now includes an improved noise sub-model for more accurate and reliable performance predictions, the capability to account for postcapture image contrast enhancement, and the capability to account for concealment material backscatter with active-illumination- based systems. Present plans for additional expansion of the model's predictive capabilities are also outlined.

Novel techniques for enhancement and segmentation of acne vulgaris lesions.

PubMed

Malik, A S; Humayun, J; Kamel, N; Yap, F B-B

2014-08-01

More than 99% acne patients suffer from acne vulgaris. While diagnosing the severity of acne vulgaris lesions, dermatologists have observed inter-rater and intra-rater variability in diagnosis results. This is because during assessment, identifying lesion types and their counting is a tedious job for dermatologists. To make the assessment job objective and easier for dermatologists, an automated system based on image processing methods is proposed in this study. There are two main objectives: (i) to develop an algorithm for the enhancement of various acne vulgaris lesions; and (ii) to develop a method for the segmentation of enhanced acne vulgaris lesions. For the first objective, an algorithm is developed based on the theory of high dynamic range (HDR) images. The proposed algorithm uses local rank transform to generate the HDR images from a single acne image followed by the log transformation. Then, segmentation is performed by clustering the pixels based on Mahalanobis distance of each pixel from spectral models of acne vulgaris lesions. Two metrics are used to evaluate the enhancement of acne vulgaris lesions, i.e., contrast improvement factor (CIF) and image contrast normalization (ICN). The proposed algorithm is compared with two other methods. The proposed enhancement algorithm shows better result than both the other methods based on CIF and ICN. In addition, sensitivity and specificity are calculated for the segmentation results. The proposed segmentation method shows higher sensitivity and specificity than other methods. This article specifically discusses the contrast enhancement and segmentation for automated diagnosis system of acne vulgaris lesions. The results are promising that can be used for further classification of acne vulgaris lesions for final grading of the lesions. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Conjugated Polymer with Intrinsic Alkyne Units for Synergistically Enhanced Raman Imaging in Living Cells.

PubMed

Li, Shengliang; Chen, Tao; Wang, Yunxia; Liu, Libing; Lv, Fengting; Li, Zhiliang; Huang, Yanyi; Schanze, Kirk S; Wang, Shu

2017-10-16

Development of Raman-active materials with enhanced and distinctive Raman vibrations in the Raman-silent region (1800-2800 cm -1 ) is highly required for specific molecular imaging of living cells with high spatial resolution. Herein, water-soluble cationic conjugated polymers (CCPs), poly(phenylene ethynylene) (PPE) derivatives, are explored for use as alkyne-state-dependent Raman probes for living cell imaging due to synergetic enhancement effect of alkyne vibrations in Raman-silent region compared to alkyne-containing small molecules. The enhanced alkyne signals result from the integration of alkyne groups into the rigid backbone and the delocalized π-conjugated structure. PPE-based conjugated polymer nanoparticles (CPNs) were also prepared as Raman-responsive nanomaterials for distinct imaging application. This work opens a new way into the development of conjugated polymer materials for enhanced Raman imaging. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Single underwater image enhancement based on color cast removal and visibility restoration

NASA Astrophysics Data System (ADS)

Li, Chongyi; Guo, Jichang; Wang, Bo; Cong, Runmin; Zhang, Yan; Wang, Jian

2016-05-01

Images taken under underwater condition usually have color cast and serious loss of contrast and visibility. Degraded underwater images are inconvenient for observation and analysis. In order to address these problems, an underwater image-enhancement method is proposed. A simple yet effective underwater image color cast removal algorithm is first presented based on the optimization theory. Then, based on the minimum information loss principle and inherent relationship of medium transmission maps of three color channels in an underwater image, an effective visibility restoration algorithm is proposed to recover visibility, contrast, and natural appearance of degraded underwater images. To evaluate the performance of the proposed method, qualitative comparison, quantitative comparison, and color accuracy test are conducted. Experimental results demonstrate that the proposed method can effectively remove color cast, improve contrast and visibility, and recover natural appearance of degraded underwater images. Additionally, the proposed method is comparable to and even better than several state-of-the-art methods.

Multiphase contrast medium injection for optimization of computed tomographic coronary angiography.

PubMed

Budoff, Matthew Jay; Shinbane, Jerold S; Child, Janis; Carson, Sivi; Chau, Alex; Liu, Stephen H; Mao, SongShou

2006-02-01

Electron beam angiography is a minimally invasive imaging technique. Adequate vascular opacification throughout the study remains a critical issue for image quality. We hypothesized that vascular image opacification and uniformity of vascular enhancement between slices can be improved using multiphase contrast medium injection protocols. We enrolled 244 consecutive patients who were randomized to three different injection protocols: single-phase contrast medium injection (Group 1), dual-phase contrast medium injection with each phase at a different injection rate (Group 2), and a three-phase injection with two phases of contrast medium injection followed by a saline injection phase (Group 3). Parameters measured were aortic opacification based on Hounsfield units and uniformity of aortic enhancement at predetermined slices (locations from top [level 1] to base [level 60]). In Group 1, contrast opacification differed across seven predetermined locations (scan levels: 1st versus 60th, P < .05), demonstrating significant nonuniformity. In Group 2, there was more uniform vascular enhancement, with no significant differences between the first 50 slices (P > .05). In Group 3, there was greater uniformity of vascular enhancement and higher mean Hounsfield units value across all 60 images, from the aortic root to the base of the heart (P < .05). The three-phase injection protocol improved vascular opacification at the base of the heart, as well as uniformity of arterial enhancement throughout the study.

Using component technologies for web based wavelet enhanced mammographic image visualization.

PubMed

Sakellaropoulos, P; Costaridou, L; Panayiotakis, G

2000-01-01

The poor contrast detectability of mammography can be dealt with by domain specific software visualization tools. Remote desktop client access and time performance limitations of a previously reported visualization tool are addressed, aiming at more efficient visualization of mammographic image resources existing in web or PACS image servers. This effort is also motivated by the fact that at present, web browsers do not support domain-specific medical image visualization. To deal with desktop client access the tool was redesigned by exploring component technologies, enabling the integration of stand alone domain specific mammographic image functionality in a web browsing environment (web adaptation). The integration method is based on ActiveX Document Server technology. ActiveX Document is a part of Object Linking and Embedding (OLE) extensible systems object technology, offering new services in existing applications. The standard DICOM 3.0 part 10 compatible image-format specification Papyrus 3.0 is supported, in addition to standard digitization formats such as TIFF. The visualization functionality of the tool has been enhanced by including a fast wavelet transform implementation, which allows for real time wavelet based contrast enhancement and denoising operations. Initial use of the tool with mammograms of various breast structures demonstrated its potential in improving visualization of diagnostic mammographic features. Web adaptation and real time wavelet processing enhance the potential of the previously reported tool in remote diagnosis and education in mammography.

A Morphological Hessian Based Approach for Retinal Blood Vessels Segmentation and Denoising Using Region Based Otsu Thresholding

PubMed Central

BahadarKhan, Khan; A Khaliq, Amir; Shahid, Muhammad

2016-01-01

Diabetic Retinopathy (DR) harm retinal blood vessels in the eye causing visual deficiency. The appearance and structure of blood vessels in retinal images play an essential part in the diagnoses of an eye sicknesses. We proposed a less computational unsupervised automated technique with promising results for detection of retinal vasculature by using morphological hessian based approach and region based Otsu thresholding. Contrast Limited Adaptive Histogram Equalization (CLAHE) and morphological filters have been used for enhancement and to remove low frequency noise or geometrical objects, respectively. The hessian matrix and eigenvalues approach used has been in a modified form at two different scales to extract wide and thin vessel enhanced images separately. Otsu thresholding has been further applied in a novel way to classify vessel and non-vessel pixels from both enhanced images. Finally, postprocessing steps has been used to eliminate the unwanted region/segment, non-vessel pixels, disease abnormalities and noise, to obtain a final segmented image. The proposed technique has been analyzed on the openly accessible DRIVE (Digital Retinal Images for Vessel Extraction) and STARE (STructured Analysis of the REtina) databases along with the ground truth data that has been precisely marked by the experts. PMID:27441646

A real-time MTFC algorithm of space remote-sensing camera based on FPGA

NASA Astrophysics Data System (ADS)

Zhao, Liting; Huang, Gang; Lin, Zhe

2018-01-01

A real-time MTFC algorithm of space remote-sensing camera based on FPGA was designed. The algorithm can provide real-time image processing to enhance image clarity when the remote-sensing camera running on-orbit. The image restoration algorithm adopted modular design. The MTF measurement calculation module on-orbit had the function of calculating the edge extension function, line extension function, ESF difference operation, normalization MTF and MTFC parameters. The MTFC image filtering and noise suppression had the function of filtering algorithm and effectively suppressing the noise. The algorithm used System Generator to design the image processing algorithms to simplify the design structure of system and the process redesign. The image gray gradient dot sharpness edge contrast and median-high frequency were enhanced. The image SNR after recovery reduced less than 1 dB compared to the original image. The image restoration system can be widely used in various fields.

Enhancement of morphological and vascular features in OCT images using a modified Bayesian residual transform

PubMed Central

Tan, Bingyao; Wong, Alexander; Bizheva, Kostadinka

2018-01-01

A novel image processing algorithm based on a modified Bayesian residual transform (MBRT) was developed for the enhancement of morphological and vascular features in optical coherence tomography (OCT) and OCT angiography (OCTA) images. The MBRT algorithm decomposes the original OCT image into multiple residual images, where each image presents information at a unique scale. Scale selective residual adaptation is used subsequently to enhance morphological features of interest, such as blood vessels and tissue layers, and to suppress irrelevant image features such as noise and motion artefacts. The performance of the proposed MBRT algorithm was tested on a series of cross-sectional and enface OCT and OCTA images of retina and brain tissue that were acquired in-vivo. Results show that the MBRT reduces speckle noise and motion-related imaging artefacts locally, thus improving significantly the contrast and visibility of morphological features in the OCT and OCTA images. PMID:29760996

Texton-based super-resolution for achieving high spatiotemporal resolution in hybrid camera system

NASA Astrophysics Data System (ADS)

Kamimura, Kenji; Tsumura, Norimichi; Nakaguchi, Toshiya; Miyake, Yoichi

2010-05-01

Many super-resolution methods have been proposed to enhance the spatial resolution of images by using iteration and multiple input images. In a previous paper, we proposed the example-based super-resolution method to enhance an image through pixel-based texton substitution to reduce the computational cost. In this method, however, we only considered the enhancement of a texture image. In this study, we modified this texton substitution method for a hybrid camera to reduce the required bandwidth of a high-resolution video camera. We applied our algorithm to pairs of high- and low-spatiotemporal-resolution videos, which were synthesized to simulate a hybrid camera. The result showed that the fine detail of the low-resolution video can be reproduced compared with bicubic interpolation and the required bandwidth could be reduced to about 1/5 in a video camera. It was also shown that the peak signal-to-noise ratios (PSNRs) of the images improved by about 6 dB in a trained frame and by 1.0-1.5 dB in a test frame, as determined by comparison with the processed image using bicubic interpolation, and the average PSNRs were higher than those obtained by the well-known Freeman’s patch-based super-resolution method. Compared with that of the Freeman’s patch-based super-resolution method, the computational time of our method was reduced to almost 1/10.

Recovery of Background Structures in Nanoscale Helium Ion Microscope Imaging.

PubMed

Carasso, Alfred S; Vladár, András E

2014-01-01

This paper discusses a two step enhancement technique applicable to noisy Helium Ion Microscope images in which background structures are not easily discernible due to a weak signal. The method is based on a preliminary adaptive histogram equalization, followed by 'slow motion' low-exponent Lévy fractional diffusion smoothing. This combined approach is unexpectedly effective, resulting in a companion enhanced image in which background structures are rendered much more visible, and noise is significantly reduced, all with minimal loss of image sharpness. The method also provides useful enhancements of scanning charged-particle microscopy images obtained by composing multiple drift-corrected 'fast scan' frames. The paper includes software routines, written in Interactive Data Language (IDL),(1) that can perform the above image processing tasks.

Finger-Vein Image Enhancement Using a Fuzzy-Based Fusion Method with Gabor and Retinex Filtering

PubMed Central

Shin, Kwang Yong; Park, Young Ho; Nguyen, Dat Tien; Park, Kang Ryoung

2014-01-01

Because of the advantages of finger-vein recognition systems such as live detection and usage as bio-cryptography systems, they can be used to authenticate individual people. However, images of finger-vein patterns are typically unclear because of light scattering by the skin, optical blurring, and motion blurring, which can degrade the performance of finger-vein recognition systems. In response to these issues, a new enhancement method for finger-vein images is proposed. Our method is novel compared with previous approaches in four respects. First, the local and global features of the vein lines of an input image are amplified using Gabor filters in four directions and Retinex filtering, respectively. Second, the means and standard deviations in the local windows of the images produced after Gabor and Retinex filtering are used as inputs for the fuzzy rule and fuzzy membership function, respectively. Third, the optimal weights required to combine the two Gabor and Retinex filtered images are determined using a defuzzification method. Fourth, the use of a fuzzy-based method means that image enhancement does not require additional training data to determine the optimal weights. Experimental results using two finger-vein databases showed that the proposed method enhanced the accuracy of finger-vein recognition compared with previous methods. PMID:24549251

Automated segmentation of hepatic vessel trees in non-contrast x-ray CT images

NASA Astrophysics Data System (ADS)

Kawajiri, Suguru; Zhou, Xiangrong; Zhang, Xuejin; Hara, Takeshi; Fujita, Hiroshi; Yokoyama, Ryujiro; Kondo, Hiroshi; Kanematsu, Masayuki; Hoshi, Hiroaki

2007-03-01

Hepatic vessel trees are the key structures in the liver. Knowledge of the hepatic vessel trees is important for liver surgery planning and hepatic disease diagnosis such as portal hypertension. However, hepatic vessels cannot be easily distinguished from other liver tissues in non-contrast CT images. Automated segmentation of hepatic vessels in non-contrast CT images is a challenging issue. In this paper, an approach for automated segmentation of hepatic vessels trees in non-contrast X-ray CT images is proposed. Enhancement of hepatic vessels is performed using two techniques: (1) histogram transformation based on a Gaussian window function; (2) multi-scale line filtering based on eigenvalues of Hessian matrix. After the enhancement of hepatic vessels, candidate of hepatic vessels are extracted by thresholding. Small connected regions of size less than 100 voxels are considered as false-positives and are removed from the process. This approach is applied to 20 cases of non-contrast CT images. Hepatic vessel trees segmented from the contrast-enhanced CT images of the same patient are used as the ground truth in evaluating the performance of the proposed segmentation method. Results show that the proposed method can enhance and segment the hepatic vessel regions in non-contrast CT images correctly.

Automatic segmentation of multimodal brain tumor images based on classification of super-voxels.

PubMed

Kadkhodaei, M; Samavi, S; Karimi, N; Mohaghegh, H; Soroushmehr, S M R; Ward, K; All, A; Najarian, K

2016-08-01

Despite the rapid growth in brain tumor segmentation approaches, there are still many challenges in this field. Automatic segmentation of brain images has a critical role in decreasing the burden of manual labeling and increasing robustness of brain tumor diagnosis. We consider segmentation of glioma tumors, which have a wide variation in size, shape and appearance properties. In this paper images are enhanced and normalized to same scale in a preprocessing step. The enhanced images are then segmented based on their intensities using 3D super-voxels. Usually in images a tumor region can be regarded as a salient object. Inspired by this observation, we propose a new feature which uses a saliency detection algorithm. An edge-aware filtering technique is employed to align edges of the original image to the saliency map which enhances the boundaries of the tumor. Then, for classification of tumors in brain images, a set of robust texture features are extracted from super-voxels. Experimental results indicate that our proposed method outperforms a comparable state-of-the-art algorithm in term of dice score.

Method of Improved Fuzzy Contrast Combined Adaptive Threshold in NSCT for Medical Image Enhancement

PubMed Central

Yang, Jie; Kasabov, Nikola

2017-01-01

Noises and artifacts are introduced to medical images due to acquisition techniques and systems. This interference leads to low contrast and distortion in images, which not only impacts the effectiveness of the medical image but also seriously affects the clinical diagnoses. This paper proposes an algorithm for medical image enhancement based on the nonsubsampled contourlet transform (NSCT), which combines adaptive threshold and an improved fuzzy set. First, the original image is decomposed into the NSCT domain with a low-frequency subband and several high-frequency subbands. Then, a linear transformation is adopted for the coefficients of the low-frequency component. An adaptive threshold method is used for the removal of high-frequency image noise. Finally, the improved fuzzy set is used to enhance the global contrast and the Laplace operator is used to enhance the details of the medical images. Experiments and simulation results show that the proposed method is superior to existing methods of image noise removal, improves the contrast of the image significantly, and obtains a better visual effect. PMID:28744464

Widefield quantitative multiplex surface enhanced Raman scattering imaging in vivo

NASA Astrophysics Data System (ADS)

McVeigh, Patrick Z.; Mallia, Rupananda J.; Veilleux, Israel; Wilson, Brian C.

2013-04-01

In recent years numerous studies have shown the potential advantages of molecular imaging in vitro and in vivo using contrast agents based on surface enhanced Raman scattering (SERS), however the low throughput of traditional point-scanned imaging methodologies have limited their use in biological imaging. In this work we demonstrate that direct widefield Raman imaging based on a tunable filter is capable of quantitative multiplex SERS imaging in vivo, and that this imaging is possible with acquisition times which are orders of magnitude lower than achievable with comparable point-scanned methodologies. The system, designed for small animal imaging, has a linear response from (0.01 to 100 pM), acquires typical in vivo images in <10 s, and with suitable SERS reporter molecules is capable of multiplex imaging without compensation for spectral overlap. To demonstrate the utility of widefield Raman imaging in biological applications, we show quantitative imaging of four simultaneous SERS reporter molecules in vivo with resulting probe quantification that is in excellent agreement with known quantities (R2>0.98).

Contrast enhancement of subcutaneous blood vessel images by means of visible and near-infrared hyper-spectral imaging

NASA Astrophysics Data System (ADS)

Katrašnik, Jaka; Bürmen, Miran; Pernuš, Franjo; Likar, Boštjan

2009-02-01

Visualization of subcutaneous veins is very difficult with the naked eye, but important for diagnosis of medical conditions and different medical procedures such as catheter insertion and blood withdrawal. Moreover, recent studies showed that the images of subcutaneous veins could be used for biometric identification. The majority of methods used for enhancing the contrast between the subcutaneous veins and surrounding tissue are based on simple imaging systems utilizing CMOS or CCD cameras with LED illumination capable of acquiring images from the near infrared spectral region, usually near 900 nm. However, such simplified imaging methods cannot exploit the full potential of the spectral information. In this paper, a new highly versatile method for enhancing the contrast of subcutaneous veins based on state-of-the-art high-resolution hyper-spectral imaging system utilizing the spectral region from 550 to 1700 nm is presented. First, a detailed analysis of the contrast between the subcutaneous veins and the surrounding tissue as a function of wavelength, for several different positions on the human arm, was performed in order to extract the spectral regions with the highest contrast. The highest contrast images were acquired at 1100 nm, however, combining the individual images from the extracted spectral regions by the proposed contrast enhancement method resulted in a single image with up to ten-fold better contrast. Therefore, the proposed method has proved to be a useful tool for visualization of subcutaneous veins.

SU-E-J-16: Automatic Image Contrast Enhancement Based On Automatic Parameter Optimization for Radiation Therapy Setup Verification

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

Qiu, J; Washington University in St Louis, St Louis, MO; Li, H. Harlod

Purpose: In RT patient setup 2D images, tissues often cannot be seen well due to the lack of image contrast. Contrast enhancement features provided by image reviewing software, e.g. Mosaiq and ARIA, require manual selection of the image processing filters and parameters thus inefficient and cannot be automated. In this work, we developed a novel method to automatically enhance the 2D RT image contrast to allow automatic verification of patient daily setups as a prerequisite step of automatic patient safety assurance. Methods: The new method is based on contrast limited adaptive histogram equalization (CLAHE) and high-pass filtering algorithms. The mostmore » important innovation is to automatically select the optimal parameters by optimizing the image contrast. The image processing procedure includes the following steps: 1) background and noise removal, 2) hi-pass filtering by subtracting the Gaussian smoothed Result, and 3) histogram equalization using CLAHE algorithm. Three parameters were determined through an iterative optimization which was based on the interior-point constrained optimization algorithm: the Gaussian smoothing weighting factor, the CLAHE algorithm block size and clip limiting parameters. The goal of the optimization is to maximize the entropy of the processed Result. Results: A total 42 RT images were processed. The results were visually evaluated by RT physicians and physicists. About 48% of the images processed by the new method were ranked as excellent. In comparison, only 29% and 18% of the images processed by the basic CLAHE algorithm and by the basic window level adjustment process, were ranked as excellent. Conclusion: This new image contrast enhancement method is robust and automatic, and is able to significantly outperform the basic CLAHE algorithm and the manual window-level adjustment process that are currently used in clinical 2D image review software tools.« less

Brain vascular image enhancement based on gradient adjust with split Bregman

NASA Astrophysics Data System (ADS)

Liang, Xiao; Dong, Di; Hui, Hui; Zhang, Liwen; Fang, Mengjie; Tian, Jie

2016-04-01

Light Sheet Microscopy is a high-resolution fluorescence microscopic technique which enables to observe the mouse brain vascular network clearly with immunostaining. However, micro-vessels are stained with few fluorescence antibodies and their signals are much weaker than large vessels, which make micro-vessels unclear in LSM images. In this work, we developed a vascular image enhancement method to enhance micro-vessel details which should be useful for vessel statistics analysis. Since gradient describes the edge information of the vessel, the main idea of our method is to increase the gradient values of the enhanced image to improve the micro-vessels contrast. Our method contained two steps: 1) calculate the gradient image of LSM image, and then amplify high gradient values of the original image to enhance the vessel edge and suppress low gradient values to remove noises. Then we formulated a new L1-norm regularization optimization problem to find an image with the expected gradient while keeping the main structure information of the original image. 2) The split Bregman iteration method was used to deal with the L1-norm regularization problem and generate the final enhanced image. The main advantage of the split Bregman method is that it has both fast convergence and low memory cost. In order to verify the effectiveness of our method, we applied our method to a series of mouse brain vascular images acquired from a commercial LSM system in our lab. The experimental results showed that our method could greatly enhance micro-vessel edges which were unclear in the original images.

Through-wall image enhancement using fuzzy and QR decomposition.

PubMed

Riaz, Muhammad Mohsin; Ghafoor, Abdul

2014-01-01

QR decomposition and fuzzy logic based scheme is proposed for through-wall image enhancement. QR decomposition is less complex compared to singular value decomposition. Fuzzy inference engine assigns weights to different overlapping subspaces. Quantitative measures and visual inspection are used to analyze existing and proposed techniques.

Enhancement and restoration of non-uniform illuminated Fundus Image of Retina obtained through thin layer of cataract.

PubMed

Mitra, Anirban; Roy, Sudipta; Roy, Somais; Setua, Sanjit Kumar

2018-03-01

Retinal fundus images are extensively used in manually or without human intervention to identify and analyze various diseases. Due to the comprehensive imaging arrangement, there is a large radiance, reflectance and contrast inconsistency within and across images. A novel method is proposed based on the cataract physical model to reduce the generated blurriness of the fundus image at the time of image acquisition through the thin layer of cataract by the fundus camera. After the blurriness reduction the method is proposed the enhancement procedure of the images with an objective on contrast perfection with no preamble of artifacts. Due to the uneven distribution of thickness of the cataract, the cataract surroundings are first predicted in the domain of frequency. Second, the resultant image of first step enhanced by the intensity histogram equalization in the adapted Hue Saturation Intensity (HSI) color image space such as the gamut problem can be avoided. The concluding image with suitable color and disparity is acquired by using the proposed max-min color correction approach. The result indicates that not only the proposed method can more effectively enhanced the non-uniform image of retina obtain through thin layer of cataract, but also the resulting image show appropriate brightness and saturation and maintain complete color space information. The projected enhancement method has been tested on the openly available datasets and the result evaluated with the standard used image enhancement algorithms and the cataract removal method. Results show noticeable development over existing methods. Cataract often prevents the clinician from objectively evaluating fundus feature. Cataract also affect subjective test. Enhancement and restoration of non-uniform illuminated Fundus Image of Retina obtained through thin layer of Cataract has shown here to be potentially beneficial. Copyright © 2018 Elsevier B.V. All rights reserved.

Dual-energy contrast-enhanced digital mammography (DE-CEDM): optimization on digital subtraction with practical x-ray low/high-energy spectra

NASA Astrophysics Data System (ADS)

Chen, Biao; Jing, Zhenxue; Smith, Andrew P.; Parikh, Samir; Parisky, Yuri

2006-03-01

Dual-energy contrast enhanced digital mammography (DE-CEDM), which is based upon the digital subtraction of low/high-energy image pairs acquired before/after the administration of contrast agents, may provide physicians physiologic and morphologic information of breast lesions and help characterize their probability of malignancy. This paper proposes to use only one pair of post-contrast low / high-energy images to obtain digitally subtracted dual-energy contrast-enhanced images with an optimal weighting factor deduced from simulated characteristics of the imaging chain. Based upon our previous CEDM framework, quantitative characteristics of the materials and imaging components in the x-ray imaging chain, including x-ray tube (tungsten) spectrum, filters, breast tissues / lesions, contrast agents (non-ionized iodine solution), and selenium detector, were systemically modeled. Using the base-material (polyethylene-PMMA) decomposition method based on entrance low / high-energy x-ray spectra and breast thickness, the optimal weighting factor was calculated to cancel the contrast between fatty and glandular tissues while enhancing the contrast of iodized lesions. By contrast, previous work determined the optimal weighting factor through either a calibration step or through acquisition of a pre-contrast low/high-energy image pair. Computer simulations were conducted to determine weighting factors, lesions' contrast signal values, and dose levels as functions of x-ray techniques and breast thicknesses. Phantom and clinical feasibility studies were performed on a modified Selenia full field digital mammography system to verify the proposed method and computer-simulated results. The resultant conclusions from the computer simulations and phantom/clinical feasibility studies will be used in the upcoming clinical study.

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.

Enhanced terahertz imaging system performance analysis and design tool for concealed weapon identification

NASA Astrophysics Data System (ADS)

Murrill, Steven R.; Franck, Charmaine C.; Espinola, Richard L.; Petkie, Douglas T.; De Lucia, Frank C.; Jacobs, Eddie L.

2011-11-01

The U.S. Army Research Laboratory (ARL) and the U.S. Army Night Vision and Electronic Sensors Directorate (NVESD) have developed a terahertz-band imaging system performance model/tool for detection and identification of concealed weaponry. The details of the MATLAB-based model which accounts for the effects of all critical sensor and display components, and for the effects of atmospheric attenuation, concealment material attenuation, and active illumination, were reported on at the 2005 SPIE Europe Security & Defence Symposium (Brugge). An advanced version of the base model that accounts for both the dramatic impact that target and background orientation can have on target observability as related to specular and Lambertian reflections captured by an active-illumination-based imaging system, and for the impact of target and background thermal emission, was reported on at the 2007 SPIE Defense and Security Symposium (Orlando). This paper will provide a comprehensive review of an enhanced, user-friendly, Windows-executable, terahertz-band imaging system performance analysis and design tool that now includes additional features such as a MODTRAN-based atmospheric attenuation calculator and advanced system architecture configuration inputs that allow for straightforward performance analysis of active or passive systems based on scanning (single- or line-array detector element(s)) or staring (focal-plane-array detector elements) imaging architectures. This newly enhanced THz imaging system design tool is an extension of the advanced THz imaging system performance model that was developed under the Defense Advanced Research Project Agency's (DARPA) Terahertz Imaging Focal-Plane Technology (TIFT) program. This paper will also provide example system component (active-illumination source and detector) trade-study analyses using the new features of this user-friendly THz imaging system performance analysis and design tool.

Complex adaptation-based LDR image rendering for 3D image reconstruction

NASA Astrophysics Data System (ADS)

Lee, Sung-Hak; Kwon, Hyuk-Ju; Sohng, Kyu-Ik

2014-07-01

A low-dynamic tone-compression technique is developed for realistic image rendering that can make three-dimensional (3D) images similar to realistic scenes by overcoming brightness dimming in the 3D display mode. The 3D surround provides varying conditions for image quality, illuminant adaptation, contrast, gamma, color, sharpness, and so on. In general, gain/offset adjustment, gamma compensation, and histogram equalization have performed well in contrast compression; however, as a result of signal saturation and clipping effects, image details are removed and information is lost on bright and dark areas. Thus, an enhanced image mapping technique is proposed based on space-varying image compression. The performance of contrast compression is enhanced with complex adaptation in a 3D viewing surround combining global and local adaptation. Evaluating local image rendering in view of tone and color expression, noise reduction, and edge compensation confirms that the proposed 3D image-mapping model can compensate for the loss of image quality in the 3D mode.

Introduction to the local enhancement of underwater imagery

NASA Astrophysics Data System (ADS)

Schmalz, Mark S.

1995-06-01

Image-based detection of submerged objects is frequently confounded by optical distortions in the aqueous medium. For example, scattering can severly degrade contrast and resolution in underwater (UW) images when illumination systems and cameras are not range-gated. Prior to the development of range-gated imaging, much research emphasis was placed upon the analysis of greyscale imagery acquired under incoherent illumination. Primarily as a result of current emphasis on coherent optical technologies, the progress of image processing (IP) research that pertains to UW imagery has lagged IP hardware and software development. In this paper, we summarize methods for the digital clarification of images that portray actively illuminated UW scenes, i.e., images of floodlit objects. We model the primary UW image components as: a) contrast degradation resulting from illuminant backscattering from the water column, b) a return signal that results from backscattering of the illuminant from the object of regard, and c) resolution loss, due to forward scattering of the return signal. Letting items a) and c) consititute error sources, one can locally apply the appropriate filters to reduce the contribution of such errors. Our technique emphasized local enhancement, as opposed to the global methods used in previous imaging practice. Our enhancement filters are based upon image-algebraic templates that are designed to compensate for the effects of single and multiple scattering as well as absorption within the water column. Discussion is based upon image clarity, algorithmic complexity, and computational efficiency.

Multi-Image Registration for an Enhanced Vision System

NASA Technical Reports Server (NTRS)

Hines, Glenn; Rahman, Zia-Ur; Jobson, Daniel; Woodell, Glenn

2002-01-01

An Enhanced Vision System (EVS) utilizing multi-sensor image fusion is currently under development at the NASA Langley Research Center. The EVS will provide enhanced images of the flight environment to assist pilots in poor visibility conditions. Multi-spectral images obtained from a short wave infrared (SWIR), a long wave infrared (LWIR), and a color visible band CCD camera, are enhanced and fused using the Retinex algorithm. The images from the different sensors do not have a uniform data structure: the three sensors not only operate at different wavelengths, but they also have different spatial resolutions, optical fields of view (FOV), and bore-sighting inaccuracies. Thus, in order to perform image fusion, the images must first be co-registered. Image registration is the task of aligning images taken at different times, from different sensors, or from different viewpoints, so that all corresponding points in the images match. In this paper, we present two methods for registering multiple multi-spectral images. The first method performs registration using sensor specifications to match the FOVs and resolutions directly through image resampling. In the second method, registration is obtained through geometric correction based on a spatial transformation defined by user selected control points and regression analysis.

Image scanning fluorescence emission difference microscopy based on a detector array.

PubMed

Li, Y; Liu, S; Liu, D; Sun, S; Kuang, C; Ding, Z; Liu, X

2017-06-01

We propose a novel imaging method that enables the enhancement of three-dimensional resolution of confocal microscopy significantly and achieve experimentally a new fluorescence emission difference method for the first time, based on the parallel detection with a detector array. Following the principles of photon reassignment in image scanning microscopy, images captured by the detector array were arranged. And by selecting appropriate reassign patterns, the imaging result with enhanced resolution can be achieved with the method of fluorescence emission difference. Two specific methods are proposed in this paper, showing that the difference between an image scanning microscopy image and a confocal image will achieve an improvement of transverse resolution by approximately 43% compared with that in confocal microscopy, and the axial resolution can also be enhanced by at least 22% experimentally and 35% theoretically. Moreover, the methods presented in this paper can improve the lateral resolution by around 10% than fluorescence emission difference and 15% than Airyscan. The mechanism of our methods is verified by numerical simulations and experimental results, and it has significant potential in biomedical applications. © 2017 The Authors Journal of Microscopy © 2017 Royal Microscopical Society.

Sparsity-driven coupled imaging and autofocusing for interferometric SAR

NASA Astrophysics Data System (ADS)

Zengin, Oǧuzcan; Khwaja, Ahmed Shaharyar; ćetin, Müjdat

2018-04-01

We propose a sparsity-driven method for coupled image formation and autofocusing based on multi-channel data collected in interferometric synthetic aperture radar (IfSAR). Relative phase between SAR images contains valuable information. For example, it can be used to estimate the height of the scene in SAR interferometry. However, this relative phase could be degraded when independent enhancement methods are used over SAR image pairs. Previously, Ramakrishnan et al. proposed a coupled multi-channel image enhancement technique, based on a dual descent method, which exhibits better performance in phase preservation compared to independent enhancement methods. Their work involves a coupled optimization formulation that uses a sparsity enforcing penalty term as well as a constraint tying the multichannel images together to preserve the cross-channel information. In addition to independent enhancement, the relative phase between the acquisitions can be degraded due to other factors as well, such as platform location uncertainties, leading to phase errors in the data and defocusing in the formed imagery. The performance of airborne SAR systems can be affected severely by such errors. We propose an optimization formulation that combines Ramakrishnan et al.'s coupled IfSAR enhancement method with the sparsity-driven autofocus (SDA) approach of Önhon and Çetin to alleviate the effects of phase errors due to motion errors in the context of IfSAR imaging. Our method solves the joint optimization problem with a Lagrangian optimization method iteratively. In our preliminary experimental analysis, we have obtained results of our method on synthetic SAR images and compared its performance to existing methods.

High-resolution T1-weighted 3D real IR imaging of the temporal bone using triple-dose contrast material.

PubMed

Naganawa, Shinji; Koshikawa, Tokiko; Nakamura, Tatsuya; Fukatsu, Hiroshi; Ishigaki, Takeo; Aoki, Ikuo

2003-12-01

The small structures in the temporal bone are surrounded by bone and air. The objectives of this study were (a) to compare contrast-enhanced T1-weighted images acquired by fast spin-echo-based three-dimensional real inversion recovery (3D rIR) against those acquired by gradient echo-based 3D SPGR in the visualization of the enhancement of small structures in the temporal bone, and (b) to determine whether either 3D rIR or 3D SPGR is useful for visualizing enhancement of the cochlear lymph fluid. Seven healthy men (age range 27-46 years) volunteered to participate in this study. All MR imaging was performed using a dedicated bilateral quadrature surface phased-array coil for temporal bone imaging at 1.5 T (Visart EX, Toshiba, Tokyo, Japan). The 3D rIR images (TR/TE/TI: 1800 ms/10 ms/500 ms) and flow-compensated 3D SPGR images (TR/TE/FA: 23 ms/10 ms/25 degrees) were obtained with a reconstructed voxel size of 0.6 x 0.7 x 0.8 mm3. Images were acquired before and 1, 90, 180, and 270 min after the administration of triple-dose Gd-DTPA-BMA (0.3 mmol/kg). In post-contrast MR images, the degree of enhancement of the cochlear aqueduct, endolymphatic sac, subarcuate artery, geniculate ganglion of the facial nerve, and cochlear lymph fluid space was assessed by two radiologists. The degree of enhancement was scored as follows: 0 (no enhancement); 1 (slight enhancement); 2 (intermediate between 1 and 3); and 3 (enhancement similar to that of vessels). Enhancement scores for the endolymphatic sac, subarcuate artery, and geniculate ganglion were higher in 3D rIR than in 3D SPGR. Washout of enhancement in the endolymphatic sac appeared to be delayed compared with that in the subarcuate artery, suggesting that the enhancement in the endolymphatic sac may have been due in part to non-vascular tissue enhancement. Enhancement of the cochlear lymph space was not observed in any of the subjects in 3D rIR and 3D SPGR. The 3D rIR sequence may be more sensitive than the 3D SPGR sequence in visualizing the enhancement of small structures in the temporal bone; however, enhancement of the cochlear fluid space could not be visualized even with 3D rIR, triple-dose contrast, and dedicated coils at 1.5 T.

Automatic medical image annotation and keyword-based image retrieval using relevance feedback.

PubMed

Ko, Byoung Chul; Lee, JiHyeon; Nam, Jae-Yeal

2012-08-01

This paper presents novel multiple keywords annotation for medical images, keyword-based medical image retrieval, and relevance feedback method for image retrieval for enhancing image retrieval performance. For semantic keyword annotation, this study proposes a novel medical image classification method combining local wavelet-based center symmetric-local binary patterns with random forests. For keyword-based image retrieval, our retrieval system use the confidence score that is assigned to each annotated keyword by combining probabilities of random forests with predefined body relation graph. To overcome the limitation of keyword-based image retrieval, we combine our image retrieval system with relevance feedback mechanism based on visual feature and pattern classifier. Compared with other annotation and relevance feedback algorithms, the proposed method shows both improved annotation performance and accurate retrieval results.

Enhancement of low visibility aerial images using histogram truncation and an explicit Retinex representation for balancing contrast and color consistency

NASA Astrophysics Data System (ADS)

Liu, Changjiang; Cheng, Irene; Zhang, Yi; Basu, Anup

2017-06-01

This paper presents an improved multi-scale Retinex (MSR) based enhancement for ariel images under low visibility. For traditional multi-scale Retinex, three scales are commonly employed, which limits its application scenarios. We extend our research to a general purpose enhanced method, and design an MSR with more than three scales. Based on the mathematical analysis and deductions, an explicit multi-scale representation is proposed that balances image contrast and color consistency. In addition, a histogram truncation technique is introduced as a post-processing strategy to remap the multi-scale Retinex output to the dynamic range of the display. Analysis of experimental results and comparisons with existing algorithms demonstrate the effectiveness and generality of the proposed method. Results on image quality assessment proves the accuracy of the proposed method with respect to both objective and subjective criteria.

Multiscale image contrast amplification (MUSICA)

NASA Astrophysics Data System (ADS)

Vuylsteke, Pieter; Schoeters, Emile P.

1994-05-01

This article presents a novel approach to the problem of detail contrast enhancement, based on multiresolution representation of the original image. The image is decomposed into a weighted sum of smooth, localized, 2D basis functions at multiple scales. Each transform coefficient represents the amount of local detail at some specific scale and at a specific position in the image. Detail contrast is enhanced by non-linear amplification of the transform coefficients. An inverse transform is then applied to the modified coefficients. This yields a uniformly contrast- enhanced image without artefacts. The MUSICA-algorithm is being applied routinely to computed radiography images of chest, skull, spine, shoulder, pelvis, extremities, and abdomen examinations, with excellent acceptance. It is useful for a wide range of applications in the medical, graphical, and industrial area.

Recovery of Background Structures in Nanoscale Helium Ion Microscope Imaging

PubMed Central

Carasso, Alfred S; Vladár, András E

2014-01-01

This paper discusses a two step enhancement technique applicable to noisy Helium Ion Microscope images in which background structures are not easily discernible due to a weak signal. The method is based on a preliminary adaptive histogram equalization, followed by ‘slow motion’ low-exponent Lévy fractional diffusion smoothing. This combined approach is unexpectedly effective, resulting in a companion enhanced image in which background structures are rendered much more visible, and noise is significantly reduced, all with minimal loss of image sharpness. The method also provides useful enhancements of scanning charged-particle microscopy images obtained by composing multiple drift-corrected ‘fast scan’ frames. The paper includes software routines, written in Interactive Data Language (IDL),1 that can perform the above image processing tasks. PMID:26601050

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.

Contrast enhanced liver MRI in patients with primary sclerosing cholangitis: inverse appearance of focal confluent fibrosis on delayed phase MR images with hepatocyte specific versus extracellular gadolinium based contrast agents.

PubMed

Husarik, Daniela B; Gupta, Rajan T; Ringe, Kristina I; Boll, Daniel T; Merkle, Elmar M

2011-12-01

To assess the enhancement pattern of focal confluent fibrosis (FCF) on contrast-enhanced hepatic magnetic resonance imaging (MRI) using hepatocyte-specific (Gd-EOB-DTPA) and extracellular (ECA) gadolinium-based contrast agents in patients with primary sclerosing cholangitis (PSC). After institutional review board approval, 10 patients with PSC (6 male, 4 female; 33-61 years) with 13 FCF were included in this retrospective study. All patients had a Gd-EOB-DTPA-enhanced liver MRI exam, and a comparison ECA-enhanced MRI. On each T1-weighted dynamic dataset, the signal intensity (SI) of FCF and the surrounding liver as well as the paraspinal muscle (M) were measured. In the Gd-EOB-DTPA group, hepatocyte phase images were also included. SI FCF/SI M, SI liver/SI M, and [(SI liver - SI FCF)/SI liver] were compared between the different contrast agents for each dynamic phase using the paired Student's t-test. There was no significant difference in SI FCF/SI M in all imaging phases. SI liver/SI M was significantly higher for the Gd-EOB-DTPA group in the delayed phase (P < .001), whereas there was no significant difference in all other imaging phases. In the Gd-EOB-DTPA group, mean [(SI liver - SI FCF)/SI liver] were as follows (values for ECA group in parentheses): unenhanced phase: 0.26 (0.26); arterial phase: 0.01 (-0.31); portal venous phase (PVP): -0.05 (-0.26); delayed phase (DP): 0.14 (-0.54); and hepatocyte phase: 0.26. Differences were significant for the DP (P < .001). On delayed phase MR images the FCF-to-liver contrast is reversed with the lesions appearing hyperintense on ECA enhanced images and hypointense on Gd-EOB-DTPA-enhanced images. Copyright © 2011 AUR. Published by Elsevier Inc. All rights reserved.

Dynamic Denoising of Tracking Sequences

PubMed Central

Michailovich, Oleg; Tannenbaum, Allen

2009-01-01

In this paper, we describe an approach to the problem of simultaneously enhancing image sequences and tracking the objects of interest represented by the latter. The enhancement part of the algorithm is based on Bayesian wavelet denoising, which has been chosen due to its exceptional ability to incorporate diverse a priori information into the process of image recovery. In particular, we demonstrate that, in dynamic settings, useful statistical priors can come both from some reasonable assumptions on the properties of the image to be enhanced as well as from the images that have already been observed before the current scene. Using such priors forms the main contribution of the present paper which is the proposal of the dynamic denoising as a tool for simultaneously enhancing and tracking image sequences. Within the proposed framework, the previous observations of a dynamic scene are employed to enhance its present observation. The mechanism that allows the fusion of the information within successive image frames is Bayesian estimation, while transferring the useful information between the images is governed by a Kalman filter that is used for both prediction and estimation of the dynamics of tracked objects. Therefore, in this methodology, the processes of target tracking and image enhancement “collaborate” in an interlacing manner, rather than being applied separately. The dynamic denoising is demonstrated on several examples of SAR imagery. The results demonstrated in this paper indicate a number of advantages of the proposed dynamic denoising over “static” approaches, in which the tracking images are enhanced independently of each other. PMID:18482881

Contrast-Enhanced Magnetic Resonance Imaging of Gastric Emptying and Motility in Rats.

PubMed

Lu, Kun-Han; Cao, Jiayue; Oleson, Steven Thomas; Powley, Terry L; Liu, Zhongming

2017-11-01

The assessment of gastric emptying and motility in humans and animals typically requires radioactive imaging or invasive measurements. Here, we developed a robust strategy to image and characterize gastric emptying and motility in rats based on contrast-enhanced magnetic resonance imaging (MRI) and computer-assisted image processing. The animals were trained to naturally consume a gadolinium-labeled dietgel while bypassing any need for oral gavage. Following this test meal, the animals were scanned under low-dose anesthesia for high-resolution T1-weighted MRI in 7 Tesla, visualizing the time-varying distribution of the meal with greatly enhanced contrast against non-gastrointestinal (GI) tissues. Such contrast-enhanced images not only depicted the gastric anatomy, but also captured and quantified stomach emptying, intestinal filling, antral contraction, and intestinal absorption with fully automated image processing. Over four postingestion hours, the stomach emptied by 27%, largely attributed to the emptying of the forestomach rather than the corpus and the antrum, and most notable during the first 30 min. Stomach emptying was accompanied by intestinal filling for the first 2 h, whereas afterward intestinal absorption was observable as cumulative contrast enhancement in the renal medulla. The antral contraction was captured as a peristaltic wave propagating from the proximal to distal antrum. The frequency, velocity, and amplitude of the antral contraction were on average 6.34 ± 0.07 contractions per minute, 0.67 ± 0.01 mm/s, and 30.58 ± 1.03%, respectively. These results demonstrate an optimized MRI-based strategy to assess gastric emptying and motility in healthy rats, paving the way for using this technique to understand GI diseases, or test new therapeutics in rat models.The assessment of gastric emptying and motility in humans and animals typically requires radioactive imaging or invasive measurements. Here, we developed a robust strategy to image and characterize gastric emptying and motility in rats based on contrast-enhanced magnetic resonance imaging (MRI) and computer-assisted image processing. The animals were trained to naturally consume a gadolinium-labeled dietgel while bypassing any need for oral gavage. Following this test meal, the animals were scanned under low-dose anesthesia for high-resolution T1-weighted MRI in 7 Tesla, visualizing the time-varying distribution of the meal with greatly enhanced contrast against non-gastrointestinal (GI) tissues. Such contrast-enhanced images not only depicted the gastric anatomy, but also captured and quantified stomach emptying, intestinal filling, antral contraction, and intestinal absorption with fully automated image processing. Over four postingestion hours, the stomach emptied by 27%, largely attributed to the emptying of the forestomach rather than the corpus and the antrum, and most notable during the first 30 min. Stomach emptying was accompanied by intestinal filling for the first 2 h, whereas afterward intestinal absorption was observable as cumulative contrast enhancement in the renal medulla. The antral contraction was captured as a peristaltic wave propagating from the proximal to distal antrum. The frequency, velocity, and amplitude of the antral contraction were on average 6.34 ± 0.07 contractions per minute, 0.67 ± 0.01 mm/s, and 30.58 ± 1.03%, respectively. These results demonstrate an optimized MRI-based strategy to assess gastric emptying and motility in healthy rats, paving the way for using this technique to understand GI diseases, or test new therapeutics in rat models.

An adaptive enhancement algorithm for infrared video based on modified k-means clustering

NASA Astrophysics Data System (ADS)

Zhang, Linze; Wang, Jingqi; Wu, Wen

2016-09-01

In this paper, we have proposed a video enhancement algorithm to improve the output video of the infrared camera. Sometimes the video obtained by infrared camera is very dark since there is no clear target. In this case, infrared video should be divided into frame images by frame extraction, in order to carry out the image enhancement. For the first frame image, which can be divided into k sub images by using K-means clustering according to the gray interval it occupies before k sub images' histogram equalization according to the amount of information per sub image, we used a method to solve a problem that final cluster centers close to each other in some cases; and for the other frame images, their initial cluster centers can be determined by the final clustering centers of the previous ones, and the histogram equalization of each sub image will be carried out after image segmentation based on K-means clustering. The histogram equalization can make the gray value of the image to the whole gray level, and the gray level of each sub image is determined by the ratio of pixels to a frame image. Experimental results show that this algorithm can improve the contrast of infrared video where night target is not obvious which lead to a dim scene, and reduce the negative effect given by the overexposed pixels adaptively in a certain range.

Whole-body MRI including diffusion-weighted MRI compared with 5-HTP PET/CT in the detection of neuroendocrine tumors

PubMed Central

Carlbom, Lina; Caballero-Corbalán, José; Granberg, Dan; Sörensen, Jens; Eriksson, Barbro; Ahlström, Håkan

2017-01-01

Aim We wanted to explore if whole-body magnetic resonance imaging (MRI) including diffusion-weighted (DW) and liver-specific contrast agent-enhanced imaging could be valuable in lesion detection of neuroendocrine tumors (NET). [11C]-5-Hydroxytryptophan positron emission tomography/computed tomography (5-HTP PET/CT) was used for comparison. Materials and methods Twenty-one patients with NET were investigated with whole-body MRI, including DW imaging (DWI) and contrast-enhanced imaging of the liver, and whole-body 5-HTP PET/CT. Seven additional patients underwent upper abdomen MRI including DWI, liver-specific contrast agent-enhanced imaging, and 5-HTP PET/CT. Results There was a patient-based concordance of 61% and a lesion-based concordance of 53% between the modalities. MRI showed good concordance with PET in detecting bone metastases but was less sensitive in detecting metastases in mediastinal lymph nodes. MRI detected more liver metastases than 5-HTP PET/CT. Conclusion Whole-body MRI with DWI did not detect all NET lesions found with whole-body 5-HTP PET/CT. Our findings indicate that MRI of the liver including liver-specific contrast agent-enhanced imaging and DWI could be a useful complement to whole-body 5-HTP PET/CT. PMID:27894208

Diffraction enhance x-ray imaging for quantitative phase contrast studies

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

Agrawal, A. K.; Singh, B., E-mail: balwants@rrcat.gov.in; Kashyap, Y. S.

2016-05-23

Conventional X-ray imaging based on absorption contrast permits limited visibility of feature having small density and thickness variations. For imaging of weakly absorbing material or materials possessing similar densities, a novel phase contrast imaging techniques called diffraction enhanced imaging has been designed and developed at imaging beamline Indus-2 RRCAT Indore. The technique provides improved visibility of the interfaces and show high contrast in the image forsmall density or thickness gradients in the bulk. This paper presents basic principle, instrumentation and analysis methods for this technique. Initial results of quantitative phase retrieval carried out on various samples have also been presented.

Active extravasation of gadolinium-based contrast agent into the subdural space following lumbar puncture.

PubMed

Kothari, Pranay D; Hanser, Evelyn M; Wang, Harrison; Farid, Nikdokht

2016-01-01

A 38year-old male presented with cauda equina syndrome following multiple lumbar puncture attempts. Lumbar spine magnetic resonance imaging (MRI) showed a subdural hematoma and an area of apparent contrast enhancement in the spinal canal on sagittal post-contrast images. Axial post-contrast images obtained seven minutes later demonstrated an increase in size and change in shape of the region of apparent contrast enhancement, indicating active extravasation of the contrast agent. This is the first reported case of active extravasation of gadolinium-based contrast agent in the spine. Copyright © 2016 Elsevier Inc. All rights reserved.

Imaging model for the scintillator and its application to digital radiography image enhancement.

PubMed

Wang, Qian; Zhu, Yining; Li, Hongwei

2015-12-28

Digital Radiography (DR) images obtained by OCD-based (optical coupling detector) Micro-CT system usually suffer from low contrast. In this paper, a mathematical model is proposed to describe the image formation process in scintillator. By solving the correlative inverse problem, the quality of DR images is improved, i.e. higher contrast and spatial resolution. By analyzing the radiative transfer process of visible light in scintillator, scattering is recognized as the main factor leading to low contrast. Moreover, involved blurring effect is also concerned and described as point spread function (PSF). Based on these physical processes, the scintillator imaging model is then established. When solving the inverse problem, pre-correction to the intensity of x-rays, dark channel prior based haze removing technique, and an effective blind deblurring approach are employed. Experiments on a variety of DR images show that the proposed approach could improve the contrast of DR images dramatically as well as eliminate the blurring vision effectively. Compared with traditional contrast enhancement methods, such as CLAHE, our method could preserve the relative absorption values well.

A network-based training environment: a medical image processing paradigm.

PubMed

Costaridou, L; Panayiotakis, G; Sakellaropoulos, P; Cavouras, D; Dimopoulos, J

1998-01-01

The capability of interactive multimedia and Internet technologies is investigated with respect to the implementation of a distance learning environment. The system is built according to a client-server architecture, based on the Internet infrastructure, composed of server nodes conceptually modelled as WWW sites. Sites are implemented by customization of available components. The environment integrates network-delivered interactive multimedia courses, network-based tutoring, SIG support, information databases of professional interest, as well as course and tutoring management. This capability has been demonstrated by means of an implemented system, validated with digital image processing content, specifically image enhancement. Image enhancement methods are theoretically described and applied to mammograms. Emphasis is given to the interactive presentation of the effects of algorithm parameters on images. The system end-user access depends on available bandwidth, so high-speed access can be achieved via LAN or local ISDN connections. Network based training offers new means of improved access and sharing of learning resources and expertise, as promising supplements in training.

Local reconstruction in computed tomography of diffraction enhanced imaging

NASA Astrophysics Data System (ADS)

Huang, Zhi-Feng; Zhang, Li; Kang, Ke-Jun; Chen, Zhi-Qiang; Zhu, Pei-Ping; Yuan, Qing-Xi; Huang, Wan-Xia

2007-07-01

Computed tomography of diffraction enhanced imaging (DEI-CT) based on synchrotron radiation source has extremely high sensitivity of weakly absorbing low-Z samples in medical and biological fields. The authors propose a modified backprojection filtration(BPF)-type algorithm based on PI-line segments to reconstruct region of interest from truncated refraction-angle projection data in DEI-CT. The distribution of refractive index decrement in the sample can be directly estimated from its reconstruction images, which has been proved by experiments at the Beijing Synchrotron Radiation Facility. The algorithm paves the way for local reconstruction of large-size samples by the use of DEI-CT with small field of view based on synchrotron radiation source.

Creating an anthropomorphic digital MR phantom—an extensible tool for comparing and evaluating quantitative imaging algorithms

NASA Astrophysics Data System (ADS)

Bosca, Ryan J.; Jackson, Edward F.

2016-01-01

Assessing and mitigating the various sources of bias and variance associated with image quantification algorithms is essential to the use of such algorithms in clinical research and practice. Assessment is usually accomplished with grid-based digital reference objects (DRO) or, more recently, digital anthropomorphic phantoms based on normal human anatomy. Publicly available digital anthropomorphic phantoms can provide a basis for generating realistic model-based DROs that incorporate the heterogeneity commonly found in pathology. Using a publicly available vascular input function (VIF) and digital anthropomorphic phantom of a normal human brain, a methodology was developed to generate a DRO based on the general kinetic model (GKM) that represented realistic and heterogeneously enhancing pathology. GKM parameters were estimated from a deidentified clinical dynamic contrast-enhanced (DCE) MRI exam. This clinical imaging volume was co-registered with a discrete tissue model, and model parameters estimated from clinical images were used to synthesize a DCE-MRI exam that consisted of normal brain tissues and a heterogeneously enhancing brain tumor. An example application of spatial smoothing was used to illustrate potential applications in assessing quantitative imaging algorithms. A voxel-wise Bland-Altman analysis demonstrated negligible differences between the parameters estimated with and without spatial smoothing (using a small radius Gaussian kernel). In this work, we reported an extensible methodology for generating model-based anthropomorphic DROs containing normal and pathological tissue that can be used to assess quantitative imaging algorithms.

Liver DCE-MRI Registration in Manifold Space Based on Robust Principal Component Analysis.

PubMed

Feng, Qianjin; Zhou, Yujia; Li, Xueli; Mei, Yingjie; Lu, Zhentai; Zhang, Yu; Feng, Yanqiu; Liu, Yaqin; Yang, Wei; Chen, Wufan

2016-09-29

A technical challenge in the registration of dynamic contrast-enhanced magnetic resonance (DCE-MR) imaging in the liver is intensity variations caused by contrast agents. Such variations lead to the failure of the traditional intensity-based registration method. To address this problem, a manifold-based registration framework for liver DCE-MR time series is proposed. We assume that liver DCE-MR time series are located on a low-dimensional manifold and determine intrinsic similarities between frames. Based on the obtained manifold, the large deformation of two dissimilar images can be decomposed into a series of small deformations between adjacent images on the manifold through gradual deformation of each frame to the template image along the geodesic path. Furthermore, manifold construction is important in automating the selection of the template image, which is an approximation of the geodesic mean. Robust principal component analysis is performed to separate motion components from intensity changes induced by contrast agents; the components caused by motion are used to guide registration in eliminating the effect of contrast enhancement. Visual inspection and quantitative assessment are further performed on clinical dataset registration. Experiments show that the proposed method effectively reduces movements while preserving the topology of contrast-enhancing structures and provides improved registration performance.

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).

Low illumination color image enhancement based on improved Retinex

NASA Astrophysics Data System (ADS)

Liao, Shujing; Piao, Yan; Li, Bing

2017-11-01

Low illumination color image usually has the characteristics of low brightness, low contrast, detail blur and high salt and pepper noise, which greatly affected the later image recognition and information extraction. Therefore, in view of the degradation of night images, the improved algorithm of traditional Retinex. The specific approach is: First, the original RGB low illumination map is converted to the YUV color space (Y represents brightness, UV represents color), and the Y component is estimated by using the sampling acceleration guidance filter to estimate the background light; Then, the reflection component is calculated by the classical Retinex formula and the brightness enhancement ratio between original and enhanced is calculated. Finally, the color space conversion from YUV to RGB and the feedback enhancement of the UV color component are carried out.

Improving iris recognition performance using segmentation, quality enhancement, match score fusion, and indexing.

PubMed

Vatsa, Mayank; Singh, Richa; Noore, Afzel

2008-08-01

This paper proposes algorithms for iris segmentation, quality enhancement, match score fusion, and indexing to improve both the accuracy and the speed of iris recognition. A curve evolution approach is proposed to effectively segment a nonideal iris image using the modified Mumford-Shah functional. Different enhancement algorithms are concurrently applied on the segmented iris image to produce multiple enhanced versions of the iris image. A support-vector-machine-based learning algorithm selects locally enhanced regions from each globally enhanced image and combines these good-quality regions to create a single high-quality iris image. Two distinct features are extracted from the high-quality iris image. The global textural feature is extracted using the 1-D log polar Gabor transform, and the local topological feature is extracted using Euler numbers. An intelligent fusion algorithm combines the textural and topological matching scores to further improve the iris recognition performance and reduce the false rejection rate, whereas an indexing algorithm enables fast and accurate iris identification. The verification and identification performance of the proposed algorithms is validated and compared with other algorithms using the CASIA Version 3, ICE 2005, and UBIRIS iris databases.

Evidence based review of the impact of image enhanced endoscopy in the diagnosis of gastric disorders

PubMed Central

Hussain, Ikram; Ang, Tiing Leong

2016-01-01

Gastric cancer is the third most common cause of cancer-related death. Advanced stages of gastric cancers generally have grim prognosis. But, good prognosis can be achieved if such cancers are detected, diagnosed and resected at early stages. However, early gastric cancers and its precursors often produce only subtle mucosal changes and therefore quite commonly remain elusive at the conventional examination with white light endoscopy. Image-enhanced endoscopy makes mucosal lesions more conspicuous and can therefore potentially yield earlier and more accurate diagnoses. Recent years have seen growing work of research in support of various types of image enhanced endoscopy (IEE) techniques (e.g., dye-chromoendoscopy; magnification endoscopy; narrow-band imaging; flexible spectral imaging color enhancement; and I-SCAN) for a variety of gastric pathologies. In this review, we will examine the evidence for the utilization of various IEE techniques in the diagnosis of gastric disorders. PMID:28042388

Spatially selective photonic crystal enhanced fluorescence and application to background reduction for biomolecule detection assays

PubMed Central

Chaudhery, Vikram; Huang, Cheng-Sheng; Pokhriyal, Anusha; Polans, James; Cunningham, Brian T.

2011-01-01

By combining photonic crystal label-free biosensor imaging with photonic crystal enhanced fluorescence, it is possible to selectively enhance the fluorescence emission from regions of the PC surface based upon the density of immobilized capture molecules. A label-free image of the capture molecules enables determination of optimal coupling conditions of the laser used for fluorescence imaging of the photonic crystal surface on a pixel-by-pixel basis, allowing maximization of fluorescence enhancement factor from regions incorporating a biomolecule capture spot and minimization of background autofluorescence from areas between capture spots. This capability significantly improves the contrast of enhanced fluorescent images, and when applied to an antibody protein microarray, provides a substantial advantage over conventional fluorescence microscopy. Using the new approach, we demonstrate detection limits as low as 0.97 pg/ml for a representative protein biomarker in buffer. PMID:22109210

Spatially selective photonic crystal enhanced fluorescence and application to background reduction for biomolecule detection assays.

PubMed

Chaudhery, Vikram; Huang, Cheng-Sheng; Pokhriyal, Anusha; Polans, James; Cunningham, Brian T

2011-11-07

By combining photonic crystal label-free biosensor imaging with photonic crystal enhanced fluorescence, it is possible to selectively enhance the fluorescence emission from regions of the PC surface based upon the density of immobilized capture molecules. A label-free image of the capture molecules enables determination of optimal coupling conditions of the laser used for fluorescence imaging of the photonic crystal surface on a pixel-by-pixel basis, allowing maximization of fluorescence enhancement factor from regions incorporating a biomolecule capture spot and minimization of background autofluorescence from areas between capture spots. This capability significantly improves the contrast of enhanced fluorescent images, and when applied to an antibody protein microarray, provides a substantial advantage over conventional fluorescence microscopy. Using the new approach, we demonstrate detection limits as low as 0.97 pg/ml for a representative protein biomarker in buffer.

Learning a No-Reference Quality Assessment Model of Enhanced Images With Big Data.

PubMed

Gu, Ke; Tao, Dacheng; Qiao, Jun-Fei; Lin, Weisi

2018-04-01

In this paper, we investigate into the problem of image quality assessment (IQA) and enhancement via machine learning. This issue has long attracted a wide range of attention in computational intelligence and image processing communities, since, for many practical applications, e.g., object detection and recognition, raw images are usually needed to be appropriately enhanced to raise the visual quality (e.g., visibility and contrast). In fact, proper enhancement can noticeably improve the quality of input images, even better than originally captured images, which are generally thought to be of the best quality. In this paper, we present two most important contributions. The first contribution is to develop a new no-reference (NR) IQA model. Given an image, our quality measure first extracts 17 features through analysis of contrast, sharpness, brightness and more, and then yields a measure of visual quality using a regression module, which is learned with big-data training samples that are much bigger than the size of relevant image data sets. The results of experiments on nine data sets validate the superiority and efficiency of our blind metric compared with typical state-of-the-art full-reference, reduced-reference and NA IQA methods. The second contribution is that a robust image enhancement framework is established based on quality optimization. For an input image, by the guidance of the proposed NR-IQA measure, we conduct histogram modification to successively rectify image brightness and contrast to a proper level. Thorough tests demonstrate that our framework can well enhance natural images, low-contrast images, low-light images, and dehazed images. The source code will be released at https://sites.google.com/site/guke198701/publications.

The ship edge feature detection based on high and low threshold for remote sensing image

NASA Astrophysics Data System (ADS)

Li, Xuan; Li, Shengyang

2018-05-01

In this paper, a method based on high and low threshold is proposed to detect the ship edge feature due to the low accuracy rate caused by the noise. Analyze the relationship between human vision system and the target features, and to determine the ship target by detecting the edge feature. Firstly, using the second-order differential method to enhance the quality of image; Secondly, to improvement the edge operator, we introduction of high and low threshold contrast to enhancement image edge and non-edge points, and the edge as the foreground image, non-edge as a background image using image segmentation to achieve edge detection, and remove the false edges; Finally, the edge features are described based on the result of edge features detection, and determine the ship target. The experimental results show that the proposed method can effectively reduce the number of false edges in edge detection, and has the high accuracy of remote sensing ship edge detection.

Evaluation of tomotherapy MVCT image enhancement program for tumor volume delineation

PubMed Central

Martin, Spencer; Rodrigues, George; Chen, Quan; Pavamani, Simon; Read, Nancy; Ahmad, Belal; Hammond, J. Alex; Venkatesan, Varagur; Renaud, James

2011-01-01

The aims of this study were to investigate the variability between physicians in delineation of head and neck tumors on original tomotherapy megavoltage CT (MVCT) studies and corresponding software enhanced MVCT images, and to establish an optimal approach for evaluation of image improvement. Five physicians contoured the gross tumor volume (GTV) for three head and neck cancer patients on 34 original and enhanced MVCT studies. Variation between original and enhanced MVCT studies was quantified by DICE coefficient and the coefficient of variance. Based on volume of agreement between physicians, higher correlation in terms of average DICE coefficients was observed in GTV delineation for enhanced MVCT for patients 1, 2, and 3 by 15%, 3%, and 7%, respectively, while delineation variance among physicians was reduced using enhanced MVCT for 12 of 17 weekly image studies. Enhanced MVCT provides advantages in reduction of variance among physicians in delineation of the GTV. Agreement on contouring by the same physician on both original and enhanced MVCT was equally high. PACS numbers: 87.57.N‐, 87.57.np, 87.57.nt

TU-CD-BRA-08: Single-Energy Computed Tomography-Based Pulmonary Perfusion Imaging: Proof-Of-Principle in a Canine Model

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

Yamamoto, T; Boone, J; Kent, M

Purpose: Pulmonary perfusion imaging has provided significant insights into pulmonary diseases, and can be useful in radiotherapy. The purpose of this study was to prospectively establish proof-of-principle in a canine model for single-energy CT-based perfusion imaging, which has the potential for widespread clinical implementation. Methods: Single-energy CT perfusion imaging is based on: (1) acquisition of inspiratory breath-hold CT scans before and after intravenous injection of iodinated contrast medium, (2) deformable image registration (DIR) of the two CT image data sets, and (3) subtraction of the pre-contrast image from post-contrast image, yielding a map of Hounsfield unit (HU) enhancement. These subtractionmore » image data sets hypothetically represent perfused blood volume, a surrogate for perfusion. In an IACUC-approved clinical trial, we acquired pre- and post-contrast CT scans in the prone posture for six anesthetized, mechanically-ventilated dogs. The elastix algorithm was used for DIR. The registration accuracy was quantified using the target registration errors (TREs) for 50 pulmonary landmarks in each dog. The gradient of HU enhancement between gravity-dependent (ventral) and non-dependent (dorsal) regions was evaluated to quantify the known effect of gravity, i.e., greater perfusion in ventral regions. Results: The lung volume difference between the two scans was 4.3±3.5% on average (range 0.3%–10.1%). DIR demonstrated an average TRE of 0.7±1.0 mm. HU enhancement in lung parenchyma was 34±10 HU on average and varied considerably between individual dogs, indicating the need for improvement of the contrast injection protocol. HU enhancement in ventral (gravity-dependent) regions was found to be greater than in dorsal regions. A population average ventral-to-dorsal gradient of HU enhancement was strong (R{sup 2}=0.94) and statistically significant (p<0.01). Conclusion: This canine study demonstrated relatively accurate DIR and a strong ventral-to-dorsal gradient of HU enhancement, providing proof-of-principle for single-energy CT pulmonary perfusion imaging. This ongoing study will enroll more dogs and investigate the physiological significance. This study was supported by a Philips Healthcare/Radiological Society of North America (RSNA) Research Seed Grant (RSD1458)« less

Contrast-dependent saturation adjustment for outdoor image enhancement.

PubMed

Wang, Shuhang; Cho, Woon; Jang, Jinbeum; Abidi, Mongi A; Paik, Joonki

2017-01-01

Outdoor images captured in bad-weather conditions usually have poor intensity contrast and color saturation since the light arriving at the camera is severely scattered or attenuated. The task of improving image quality in poor conditions remains a challenge. Existing methods of image quality improvement are usually effective for a small group of images but often fail to produce satisfactory results for a broader variety of images. In this paper, we propose an image enhancement method, which makes it applicable to enhance outdoor images by using content-adaptive contrast improvement as well as contrast-dependent saturation adjustment. The main contribution of this work is twofold: (1) we propose the content-adaptive histogram equalization based on the human visual system to improve the intensity contrast; and (2) we introduce a simple yet effective prior for adjusting the color saturation depending on the intensity contrast. The proposed method is tested with different kinds of images, compared with eight state-of-the-art methods: four enhancement methods and four haze removal methods. Experimental results show the proposed method can more effectively improve the visibility and preserve the naturalness of the images, as opposed to the compared methods.

Noise properties and task-based evaluation of diffraction-enhanced imaging

PubMed Central

Brankov, Jovan G.; Saiz-Herranz, Alejandro; Wernick, Miles N.

2014-01-01

Abstract. Diffraction-enhanced imaging (DEI) is an emerging x-ray imaging method that simultaneously yields x-ray attenuation and refraction images and holds great promise for soft-tissue imaging. The DEI has been mainly studied using synchrotron sources, but efforts have been made to transition the technology to more practical implementations using conventional x-ray sources. The main technical challenge of this transition lies in the relatively lower x-ray flux obtained from conventional sources, leading to photon-limited data contaminated by Poisson noise. Several issues that must be understood in order to design and optimize DEI imaging systems with respect to noise performance are addressed. Specifically, we: (a) develop equations describing the noise properties of DEI images, (b) derive the conditions under which the DEI algorithm is statistically optimal, (c) characterize the imaging performance that can be obtained as measured by task-based metrics, and (d) consider image-processing steps that may be employed to mitigate noise effects. PMID:26158056

Cortical Enhanced Tissue Segmentation of Neonatal Brain MR Images Acquired by a Dedicated Phased Array Coil

PubMed Central

Shi, Feng; Yap, Pew-Thian; Fan, Yong; Cheng, Jie-Zhi; Wald, Lawrence L.; Gerig, Guido; Lin, Weili; Shen, Dinggang

2010-01-01

The acquisition of high quality MR images of neonatal brains is largely hampered by their characteristically small head size and low tissue contrast. As a result, subsequent image processing and analysis, especially for brain tissue segmentation, are often hindered. To overcome this problem, a dedicated phased array neonatal head coil is utilized to improve MR image quality by effectively combing images obtained from 8 coil elements without lengthening data acquisition time. In addition, a subject-specific atlas based tissue segmentation algorithm is specifically developed for the delineation of fine structures in the acquired neonatal brain MR images. The proposed tissue segmentation method first enhances the sheet-like cortical gray matter (GM) structures in neonatal images with a Hessian filter for generation of cortical GM prior. Then, the prior is combined with our neonatal population atlas to form a cortical enhanced hybrid atlas, which we refer to as the subject-specific atlas. Various experiments are conducted to compare the proposed method with manual segmentation results, as well as with additional two population atlas based segmentation methods. Results show that the proposed method is capable of segmenting the neonatal brain with the highest accuracy, compared to other two methods. PMID:20862268

Local gray level S-curve transformation - A generalized contrast enhancement technique for medical images.

PubMed

Gandhamal, Akash; Talbar, Sanjay; Gajre, Suhas; Hani, Ahmad Fadzil M; Kumar, Dileep

2017-04-01

Most medical images suffer from inadequate contrast and brightness, which leads to blurred or weak edges (low contrast) between adjacent tissues resulting in poor segmentation and errors in classification of tissues. Thus, contrast enhancement to improve visual information is extremely important in the development of computational approaches for obtaining quantitative measurements from medical images. In this research, a contrast enhancement algorithm that applies gray-level S-curve transformation technique locally in medical images obtained from various modalities is investigated. The S-curve transformation is an extended gray level transformation technique that results into a curve similar to a sigmoid function through a pixel to pixel transformation. This curve essentially increases the difference between minimum and maximum gray values and the image gradient, locally thereby, strengthening edges between adjacent tissues. The performance of the proposed technique is determined by measuring several parameters namely, edge content (improvement in image gradient), enhancement measure (degree of contrast enhancement), absolute mean brightness error (luminance distortion caused by the enhancement), and feature similarity index measure (preservation of the original image features). Based on medical image datasets comprising 1937 images from various modalities such as ultrasound, mammograms, fluorescent images, fundus, X-ray radiographs and MR images, it is found that the local gray-level S-curve transformation outperforms existing techniques in terms of improved contrast and brightness, resulting in clear and strong edges between adjacent tissues. The proposed technique can be used as a preprocessing tool for effective segmentation and classification of tissue structures in medical images. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Eu(II)-Containing Cryptate as a Redox Sensor in Magnetic Resonance Imaging of Living Tissue.

PubMed

Ekanger, Levi A; Polin, Lisa A; Shen, Yimin; Haacke, E Mark; Martin, Philip D; Allen, Matthew J

2015-11-23

The Eu(II) ion rivals Gd(III) in its ability to enhance contrast in magnetic resonance imaging. However, all reported Eu(II)-based complexes have been studied in vitro largely because the tendency of Eu(II) to oxidize to Eu(III) has been viewed as a major obstacle to in vivo imaging. Herein, we present solid- and solution-phase characterization of a Eu(II)-containing cryptate and the first in vivo use of Eu(II) to provide contrast enhancement. The results indicate that between one and two water molecules are coordinated to the Eu(II) core upon dissolution. We also demonstrate that Eu(II)-based contrast enhancement can be observed for hours in a mouse. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Using composite sinusoidal patterns in structured-illumination reflectance imaging (SIRI) for enhanced detection of defects in food

USDA-ARS?s Scientific Manuscript database

This study presented a first exploration of using composite sinusoidal patterns that integrated two and three spatial frequencies of interest, in structured-illumination reflectance imaging (SIRI) for enhanced detection of defects in food (e.g., bruises in apples). Three methods based on Fourier tra...

Enhanced light element imaging in atomic resolution scanning transmission electron microscopy.

PubMed

Findlay, S D; Kohno, Y; Cardamone, L A; Ikuhara, Y; Shibata, N

2014-01-01

We show that an imaging mode based on taking the difference between signals recorded from the bright field (forward scattering region) in atomic resolution scanning transmission electron microscopy provides an enhancement of the detectability of light elements over existing techniques. In some instances this is an enhancement of the visibility of the light element columns relative to heavy element columns. In all cases explored it is an enhancement in the signal-to-noise ratio of the image at the light column site. The image formation mechanisms are explained and the technique is compared with earlier approaches. Experimental data, supported by simulation, are presented for imaging the oxygen columns in LaAlO₃. Case studies looking at imaging hydrogen columns in YH₂ and lithium columns in Al₃Li are also explored through simulation, particularly with respect to the dependence on defocus, probe-forming aperture angle and detector collection aperture angles. © 2013 Elsevier B.V. All rights reserved.

Uterine fibroids: semiquantitative perfusion MR imaging parameters associated with the intraprocedural and immediate postprocedural treatment efficiencies of MR imaging-guided high-intensity focused ultrasound ablation.

PubMed

Kim, Young-sun; Kim, Byoung-Gie; Rhim, Hyunchul; Bae, Duk-Soo; Lee, Jeong-Won; Kim, Tae-Joong; Choi, Chel Hun; Lee, Yoo-Young; Lim, Hyo Keun

2014-11-01

To determine whether semiquantitative perfusion magnetic resonance (MR) imaging parameters are associated with therapeutic effectiveness of MR imaging-guided high-intensity focused ultrasound ( HIFU high-intensity focused ultrasound ) ablation of uterine fibroids and which semiquantitative perfusion parameters are significant with regard to treatment efficiency. This study was approved by the institutional review board, and informed consent was obtained from all subjects. Seventy-seven women (mean age, 43.3 years) with 119 fibroids (mean diameter, 7.5 cm) treated with MR imaging-guided HIFU high-intensity focused ultrasound ablation were analyzed. The correlation between semiquantitative perfusion MR parameters (peak enhancement, relative peak enhancement, time to peak, wash-in rate, washout rate) and heating and ablation efficiencies (lethal thermal dose volume based on MR thermometry and nonperfused volume based on immediate contrast-enhanced image divided by intended treatment volume) were evaluated by using a linear mixed model on a per-fibroid basis. The specific value of the significant parameter that had a substantial effect on treatment efficiency was determined. The mean peak enhancement, relative peak enhancement, time to peak, wash-in rate, and washout rate of the fibroids were 1293.1 ± 472.8 (range, 570.2-2477.8), 171.4% ± 57.2 (range, 0.6%-370.2%), 137.2 seconds ± 119.8 (range, 20.0-300.0 seconds), 79.5 per second ± 48.2 (range, 12.5-236.7 per second), and 11.4 per second ± 10.1 (range, 0-39.3 per second), respectively. Relative peak enhancement was found to be independently significant for both heating and ablation efficiencies (B = -0.002, P < .001 and B = -0.003, P = .050, respectively). The washout rate was significantly associated with ablation efficiency (B = -0.018, P = .043). Both efficiencies showed the most abrupt transitions at 220% of relative peak enhancement. Relative peak enhancement at semiquantitative perfusion MR imaging was significantly associated with treatment efficiency of MR imaging-guided HIFU high-intensity focused ultrasound ablation of uterine fibroids, and a value of 220% or less is suggested as a screening guideline for more efficient treatment.

Perylene-diimide-based nanoparticles as highly efficient photoacoustic agents for deep brain tumor imaging in living mice

DOE PAGES

Fan, Quli; Cheng, Kai; Yang, Zhen; ...

2014-11-06

In order to promote preclinical and clinical applications of photoacoustic imaging, novel photoacoustic contrast agents are highly desired for molecular imaging of diseases, especially for deep tumor imaging. In this paper, perylene-3,4,9,10-tetracarboxylic diiimide-based near-infrared-absorptive organic nanoparticles are reported as an efficient agent for photoacoustic imaging of deep brain tumors in living mice with enhanced permeability and retention effect

Nanoantenna-Enhanced Infrared Spectroscopic Chemical Imaging.

PubMed

Kühner, Lucca; Hentschel, Mario; Zschieschang, Ute; Klauk, Hagen; Vogt, Jochen; Huck, Christian; Giessen, Harald; Neubrech, Frank

2017-05-26

Spectroscopic infrared chemical imaging is ideally suited for label-free and spatially resolved characterization of molecular species, but often suffers from low infrared absorption cross sections. Here, we overcome this limitation by utilizing confined electromagnetic near-fields of resonantly excited plasmonic nanoantennas, which enhance the molecular absorption by orders of magnitude. In the experiments, we evaporate microstructured chemical patterns of C 60 and pentacene with nanometer thickness on top of homogeneous arrays of tailored nanoantennas. Broadband mid-infrared spectra containing plasmonic and vibrational information were acquired with diffraction-limited resolution using a two-dimensional focal plane array detector. Evaluating the enhanced infrared absorption at the respective frequencies, spatially resolved chemical images were obtained. In these chemical images, the microstructured chemical patterns are only visible if nanoantennas are used. This confirms the superior performance of our approach over conventional spectroscopic infrared imaging. In addition to the improved sensitivity, our technique provides chemical selectivity, which would not be available with plasmonic imaging that is based on refractive index sensing. To extend the accessible spectral bandwidth of nanoantenna-enhanced spectroscopic imaging, we employed nanostructures with dual-band resonances, providing broadband plasmonic enhancement and sensitivity. Our results demonstrate the potential of nanoantenna-enhanced spectroscopic infrared chemical imaging for spatially resolved characterization of organic layers with thicknesses of several nanometers. This is of potential interest for medical applications which are currently hampered by state-of-art infrared techniques, e.g., for distinguishing cancerous from healthy tissues.

Modified dixon‐based renal dynamic contrast‐enhanced MRI facilitates automated registration and perfusion analysis

PubMed Central

Leiner, Tim; Vink, Eva E.; Blankestijn, Peter J.; van den Berg, Cornelis A.T.

2017-01-01

Purpose Renal dynamic contrast‐enhanced (DCE) MRI provides information on renal perfusion and filtration. However, clinical implementation is hampered by challenges in postprocessing as a result of misalignment of the kidneys due to respiration. We propose to perform automated image registration using the fat‐only images derived from a modified Dixon reconstruction of a dual‐echo acquisition because these provide consistent contrast over the dynamic series. Methods DCE data of 10 hypertensive patients was used. Dual‐echo images were acquired at 1.5 T with temporal resolution of 3.9 s during contrast agent injection. Dixon fat, water, and in‐phase and opposed‐phase (OP) images were reconstructed. Postprocessing was automated. Registration was performed both to fat images and OP images for comparison. Perfusion and filtration values were extracted from a two‐compartment model fit. Results Automatic registration to fat images performed better than automatic registration to OP images with visible contrast enhancement. Median vertical misalignment of the kidneys was 14 mm prior to registration, compared to 3 mm and 5 mm with registration to fat images and OP images, respectively (P = 0.03). Mean perfusion values and MR‐based glomerular filtration rates (GFR) were 233 ± 64 mL/100 mL/min and 60 ± 36 mL/minute, respectively, based on fat‐registered images. MR‐based GFR correlated with creatinine‐based GFR (P = 0.04) for fat‐registered images. For unregistered and OP‐registered images, this correlation was not significant. Conclusion Absence of contrast changes on Dixon fat images improves registration in renal DCE MRI and enables automated postprocessing, resulting in a more accurate estimation of GFR. Magn Reson Med 80:66–76, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. PMID:29134673

Image Encryption Algorithm Based on Hyperchaotic Maps and Nucleotide Sequences Database

PubMed Central

2017-01-01

Image encryption technology is one of the main means to ensure the safety of image information. Using the characteristics of chaos, such as randomness, regularity, ergodicity, and initial value sensitiveness, combined with the unique space conformation of DNA molecules and their unique information storage and processing ability, an efficient method for image encryption based on the chaos theory and a DNA sequence database is proposed. In this paper, digital image encryption employs a process of transforming the image pixel gray value by using chaotic sequence scrambling image pixel location and establishing superchaotic mapping, which maps quaternary sequences and DNA sequences, and by combining with the logic of the transformation between DNA sequences. The bases are replaced under the displaced rules by using DNA coding in a certain number of iterations that are based on the enhanced quaternary hyperchaotic sequence; the sequence is generated by Chen chaos. The cipher feedback mode and chaos iteration are employed in the encryption process to enhance the confusion and diffusion properties of the algorithm. Theoretical analysis and experimental results show that the proposed scheme not only demonstrates excellent encryption but also effectively resists chosen-plaintext attack, statistical attack, and differential attack. PMID:28392799

Resolution enhancement using simultaneous couple illumination

NASA Astrophysics Data System (ADS)

Hussain, Anwar; Martínez Fuentes, José Luis

2016-10-01

A super-resolution technique based on structured illumination created by a liquid crystal on silicon spatial light modulator (LCOS-SLM) is presented. Single and simultaneous pairs of tilted beams are generated to illuminate a target object. Resolution enhancement of an optical 4f system is demonstrated by using numerical simulations. The resulting intensity images are recorded at a charged couple device (CCD) and stored in the computer memory for further processing. One dimension enhancement can be performed with only 15 images. Two dimensional complete improvement requires 153 different images. The resolution of the optical system is extended three times compared to the band limited system.

A Novel Segmentation Approach Combining Region- and Edge-Based Information for Ultrasound Images

PubMed Central

Luo, Yaozhong; Liu, Longzhong; Li, Xuelong

2017-01-01

Ultrasound imaging has become one of the most popular medical imaging modalities with numerous diagnostic applications. However, ultrasound (US) image segmentation, which is the essential process for further analysis, is a challenging task due to the poor image quality. In this paper, we propose a new segmentation scheme to combine both region- and edge-based information into the robust graph-based (RGB) segmentation method. The only interaction required is to select two diagonal points to determine a region of interest (ROI) on the original image. The ROI image is smoothed by a bilateral filter and then contrast-enhanced by histogram equalization. Then, the enhanced image is filtered by pyramid mean shift to improve homogeneity. With the optimization of particle swarm optimization (PSO) algorithm, the RGB segmentation method is performed to segment the filtered image. The segmentation results of our method have been compared with the corresponding results obtained by three existing approaches, and four metrics have been used to measure the segmentation performance. The experimental results show that the method achieves the best overall performance and gets the lowest ARE (10.77%), the second highest TPVF (85.34%), and the second lowest FPVF (4.48%). PMID:28536703

Chain of evidence generation for contrast enhancement in digital image forensics

NASA Astrophysics Data System (ADS)

Battiato, Sebastiano; Messina, Giuseppe; Strano, Daniela

2010-01-01

The quality of the images obtained by digital cameras has improved a lot since digital cameras early days. Unfortunately, it is not unusual in image forensics to find wrongly exposed pictures. This is mainly due to obsolete techniques or old technologies, but also due to backlight conditions. To extrapolate some invisible details a stretching of the image contrast is obviously required. The forensics rules to produce evidences require a complete documentation of the processing steps, enabling the replication of the entire process. The automation of enhancement techniques is thus quite difficult and needs to be carefully documented. This work presents an automatic procedure to find contrast enhancement settings, allowing both image correction and automatic scripting generation. The technique is based on a preprocessing step which extracts the features of the image and selects correction parameters. The parameters are thus saved through a JavaScript code that is used in the second step of the approach to correct the image. The generated script is Adobe Photoshop compliant (which is largely used in image forensics analysis) thus permitting the replication of the enhancement steps. Experiments on a dataset of images are also reported showing the effectiveness of the proposed methodology.

Intensity Variation Normalization for Finger Vein Recognition Using Guided Filter Based Singe Scale Retinex

PubMed Central

Xie, Shan Juan; Lu, Yu; Yoon, Sook; Yang, Jucheng; Park, Dong Sun

2015-01-01

Finger vein recognition has been considered one of the most promising biometrics for personal authentication. However, the capacities and percentages of finger tissues (e.g., bone, muscle, ligament, water, fat, etc.) vary person by person. This usually causes poor quality of finger vein images, therefore degrading the performance of finger vein recognition systems (FVRSs). In this paper, the intrinsic factors of finger tissue causing poor quality of finger vein images are analyzed, and an intensity variation (IV) normalization method using guided filter based single scale retinex (GFSSR) is proposed for finger vein image enhancement. The experimental results on two public datasets demonstrate the effectiveness of the proposed method in enhancing the image quality and finger vein recognition accuracy. PMID:26184226

Intensity Variation Normalization for Finger Vein Recognition Using Guided Filter Based Singe Scale Retinex.

PubMed

Xie, Shan Juan; Lu, Yu; Yoon, Sook; Yang, Jucheng; Park, Dong Sun

2015-07-14

Finger vein recognition has been considered one of the most promising biometrics for personal authentication. However, the capacities and percentages of finger tissues (e.g., bone, muscle, ligament, water, fat, etc.) vary person by person. This usually causes poor quality of finger vein images, therefore degrading the performance of finger vein recognition systems (FVRSs). In this paper, the intrinsic factors of finger tissue causing poor quality of finger vein images are analyzed, and an intensity variation (IV) normalization method using guided filter based single scale retinex (GFSSR) is proposed for finger vein image enhancement. The experimental results on two public datasets demonstrate the effectiveness of the proposed method in enhancing the image quality and finger vein recognition accuracy.

Effects of Instructional Strategies Using Cross Sections on the Recognition of Anatomical Structures in Correlated CT and MR Images

ERIC Educational Resources Information Center

Khalil, Mohammed K.; Paas, Fred; Johnson, Tristan E.; Su, Yung K.; Payer, Andrew F.

2008-01-01

This research is an effort to best utilize the interactive anatomical images for instructional purposes based on cognitive load theory. Three studies explored the differential effects of three computer-based instructional strategies that use anatomical cross-sections to enhance the interpretation of radiological images. These strategies include:…

Clinical utility of wavelet compression for resolution-enhanced chest radiography

NASA Astrophysics Data System (ADS)

Andriole, Katherine P.; Hovanes, Michael E.; Rowberg, Alan H.

2000-05-01

This study evaluates the usefulness of wavelet compression for resolution-enhanced storage phosphor chest radiographs in the detection of subtle interstitial disease, pneumothorax and other abnormalities. A wavelet compression technique, MrSIDTM (LizardTech, Inc., Seattle, WA), is implemented which compresses the images from their original 2,000 by 2,000 (2K) matrix size, and then decompresses the image data for display at optimal resolution by matching the spatial frequency characteristics of image objects using a 4,000- square matrix. The 2K-matrix computed radiography (CR) chest images are magnified to a 4K-matrix using wavelet series expansion. The magnified images are compared with the original uncompressed 2K radiographs and with two-times magnification of the original images. Preliminary results show radiologist preference for MrSIDTM wavelet-based magnification over magnification of original data, and suggest that the compressed/decompressed images may provide an enhancement to the original. Data collection for clinical trials of 100 chest radiographs including subtle interstitial abnormalities and/or subtle pneumothoraces and normal cases, are in progress. Three experienced thoracic radiologists will view images side-by- side on calibrated softcopy workstations under controlled viewing conditions, and rank order preference tests will be performed. This technique combines image compression with image enhancement, and suggests that compressed/decompressed images can actually improve the originals.

High Energy Resolution Hyperspectral X-Ray Imaging for Low-Dose Contrast-Enhanced Digital Mammography.

PubMed

Pani, Silvia; Saifuddin, Sarene C; Ferreira, Filipa I M; Henthorn, Nicholas; Seller, Paul; Sellin, Paul J; Stratmann, Philipp; Veale, Matthew C; Wilson, Matthew D; Cernik, Robert J

2017-09-01

Contrast-enhanced digital mammography (CEDM) is an alternative to conventional X-ray mammography for imaging dense breasts. However, conventional approaches to CEDM require a double exposure of the patient, implying higher dose, and risk of incorrect image registration due to motion artifacts. A novel approach is presented, based on hyperspectral imaging, where a detector combining positional and high-resolution spectral information (in this case based on Cadmium Telluride) is used. This allows simultaneous acquisition of the two images required for CEDM. The approach was tested on a custom breast-equivalent phantom containing iodinated contrast agent (Niopam 150®). Two algorithms were used to obtain images of the contrast agent distribution: K-edge subtraction (KES), providing images of the distribution of the contrast agent with the background structures removed, and a dual-energy (DE) algorithm, providing an iodine-equivalent image and a water-equivalent image. The high energy resolution of the detector allowed the selection of two close-by energies, maximising the signal in KES images, and enhancing the visibility of details with the low surface concentration of contrast agent. DE performed consistently better than KES in terms of contrast-to-noise ratio of the details; moreover, it allowed a correct reconstruction of the surface concentration of the contrast agent in the iodine image. Comparison with CEDM with a conventional detector proved the superior performance of hyperspectral CEDM in terms of the image quality/dose tradeoff.

Dynamic contrast enhanced MRI of the placenta: A tool for prenatal diagnosis of placenta accreta?

PubMed

Millischer, A E; Deloison, B; Silvera, S; Ville, Y; Boddaert, N; Balvay, D; Siauve, N; Cuenod, C A; Tsatsaris, V; Sentilhes, L; Salomon, L J

2017-05-01

Ultrasound (US) is the primary imaging modality for the diagnosis of placenta accreta, but it is not sufficiently accurate. MRI morphologic criteria have recently emerged as a useful tool in this setting, but their analysis is too subjective. Recent studies suggest that gadolinium enhancement may help to distinguish between the stretched myometrium and placenta within a scar area. However, objective MRI criteria are still required for prenatal diagnosis of placenta accreta. The purpose of this study was to assess the diagnostic value of dynamic contrast gadolinium enhancement (DCE) MRI patterns for placenta accreta. MR images were acquired with a 1.5-T unit at 30-35 weeks of gestation in women with a history of Caesarian section, a low-lying anterior placenta, and US features compatible with placenta accreta. Sagittal, axial and coronal SSFP (Steady State Free Precession) sequences were acquired before injection. Then, contrast-enhanced dynamic T1-weighted images were acquired through the entire cross-sectional area of the placenta. Images were obtained sequentially at 10- to 14-s intervals for 2 min, beginning simultaneously with the bolus injection. Functional analysis was performed retrospectively, and tissular relative enhancement parameters were extracted from the recorded images. The suspected area of accreta (SAA) was placed in the region of the previous scar, and a control area (CA) of similar size was placed on the same image plane, as far as possible from the SAA. Semi-quantitative analysis of DCE-MR images was based on the kinetic enhancement curves in these two regions of interest (ROI). Three tissular relative enhancement parameters were compared according to the pregnancy outcomes, namely time to peak, maximal signal intensity, and area under the enhancement curve. We studied 9 women (43%) with accreta and 12 women (57%) with a normal placenta. All three tissular relative enhancement parameters differed significantly between the two groups (p < 10 -3 ). The use of dynamic contrast-enhanced MRI at 30-35 weeks of gestation in women with a high risk of placenta accreta allows the extraction of tissular enhancement parameters that differ significantly between placenta accreta and normal placenta. It therefore provides objective parameters on which to base the diagnosis and patient management. Copyright © 2017. Published by Elsevier Ltd.

Enhancement of dynamic myocardial perfusion PET images based on low-rank plus sparse decomposition.

PubMed

Lu, Lijun; Ma, Xiaomian; Mohy-Ud-Din, Hassan; Ma, Jianhua; Feng, Qianjin; Rahmim, Arman; Chen, Wufan

2018-02-01

The absolute quantification of dynamic myocardial perfusion (MP) PET imaging is challenged by the limited spatial resolution of individual frame images due to division of the data into shorter frames. This study aims to develop a method for restoration and enhancement of dynamic PET images. We propose that the image restoration model should be based on multiple constraints rather than a single constraint, given the fact that the image characteristic is hardly described by a single constraint alone. At the same time, it may be possible, but not optimal, to regularize the image with multiple constraints simultaneously. Fortunately, MP PET images can be decomposed into a superposition of background vs. dynamic components via low-rank plus sparse (L + S) decomposition. Thus, we propose an L + S decomposition based MP PET image restoration model and express it as a convex optimization problem. An iterative soft thresholding algorithm was developed to solve the problem. Using realistic dynamic 82 Rb MP PET scan data, we optimized and compared its performance with other restoration methods. The proposed method resulted in substantial visual as well as quantitative accuracy improvements in terms of noise versus bias performance, as demonstrated in extensive 82 Rb MP PET simulations. In particular, the myocardium defect in the MP PET images had improved visual as well as contrast versus noise tradeoff. The proposed algorithm was also applied on an 8-min clinical cardiac 82 Rb MP PET study performed on the GE Discovery PET/CT, and demonstrated improved quantitative accuracy (CNR and SNR) compared to other algorithms. The proposed method is effective for restoration and enhancement of dynamic PET images. Copyright © 2017 Elsevier B.V. All rights reserved.

Nanogap embedded silver gratings for surface plasmon enhanced fluorescence

NASA Astrophysics Data System (ADS)

Bhatnagar, Kunal

Plasmonic nanostructures have been extensively used in the past few decades for applications in sub-wavelength optics, data storage, optoelectronic circuits, microscopy and bio-photonics. The enhanced electromagnetic field produced at the metal and dielectric interface by the excitation of surface plasmons via incident radiation can be used for signal enhancement in fluorescence and surface enhanced Raman scattering studies. Novel plasmonic structures have shown to provide very efficient and extreme light concentration at the nano-scale in recent years. The enhanced electric field produced within a few hundred nanometers of these surfaces can be used to excite fluorophores in the surrounding environment. Fluorescence based bio-detection and bio-imaging are two of the most important tools in the life sciences and improving the qualities and capabilities of fluorescence based detectors and imaging equipment remains a big challenge for industry manufacturers. We report a novel fabrication technique for producing nano-gap embedded periodic grating substrates on the nanoscale using a store bought HD-DVD and conventional soft lithography procedures. Polymethylsilsesquioxane (PMSSQ) polymer is used as the ink for the micro-contact printing process with PDMS stamps obtained from the inexpensive HD-DVDs as master molds. Fluorescence enhancement factors of up to 118 times were observed with these silver nanostructures in conjugation with Rhodamine-590 fluorescent dye. These substrates are ideal candidates for a robust and inexpensive optical system with applications such as low-level fluorescence based analyte detection, single molecule imaging, and surface enhanced Raman studies. Preliminary results in single molecule experiments have also been obtained by imaging individual 3 nm and 20 nm dye-doped nanoparticles attached to the silver plasmonic gratings using epi-fluorescence microscopy.

A fast color image enhancement algorithm based on Max Intensity Channel

PubMed Central

Sun, Wei; Han, Long; Guo, Baolong; Jia, Wenyan; Sun, Mingui

2014-01-01

In this paper, we extend image enhancement techniques based on the retinex theory imitating human visual perception of scenes containing high illumination variations. This extension achieves simultaneous dynamic range modification, color consistency, and lightness rendition without multi-scale Gaussian filtering which has a certain halo effect. The reflection component is analyzed based on the illumination and reflection imaging model. A new prior named Max Intensity Channel (MIC) is implemented assuming that the reflections of some points in the scene are very high in at least one color channel. Using this prior, the illumination of the scene is obtained directly by performing a gray-scale closing operation and a fast cross-bilateral filtering on the MIC of the input color image. Consequently, the reflection component of each RGB color channel can be determined from the illumination and reflection imaging model. The proposed algorithm estimates the illumination component which is relatively smooth and maintains the edge details in different regions. A satisfactory color rendition is achieved for a class of images that do not satisfy the gray-world assumption implicit to the theoretical foundation of the retinex. Experiments are carried out to compare the new method with several spatial and transform domain methods. Our results indicate that the new method is superior in enhancement applications, improves computation speed, and performs well for images with high illumination variations than other methods. Further comparisons of images from National Aeronautics and Space Administration and a wearable camera eButton have shown a high performance of the new method with better color restoration and preservation of image details. PMID:25110395

A fast color image enhancement algorithm based on Max Intensity Channel.

PubMed

Sun, Wei; Han, Long; Guo, Baolong; Jia, Wenyan; Sun, Mingui

2014-03-30

In this paper, we extend image enhancement techniques based on the retinex theory imitating human visual perception of scenes containing high illumination variations. This extension achieves simultaneous dynamic range modification, color consistency, and lightness rendition without multi-scale Gaussian filtering which has a certain halo effect. The reflection component is analyzed based on the illumination and reflection imaging model. A new prior named Max Intensity Channel (MIC) is implemented assuming that the reflections of some points in the scene are very high in at least one color channel. Using this prior, the illumination of the scene is obtained directly by performing a gray-scale closing operation and a fast cross-bilateral filtering on the MIC of the input color image. Consequently, the reflection component of each RGB color channel can be determined from the illumination and reflection imaging model. The proposed algorithm estimates the illumination component which is relatively smooth and maintains the edge details in different regions. A satisfactory color rendition is achieved for a class of images that do not satisfy the gray-world assumption implicit to the theoretical foundation of the retinex. Experiments are carried out to compare the new method with several spatial and transform domain methods. Our results indicate that the new method is superior in enhancement applications, improves computation speed, and performs well for images with high illumination variations than other methods. Further comparisons of images from National Aeronautics and Space Administration and a wearable camera eButton have shown a high performance of the new method with better color restoration and preservation of image details.

A fast color image enhancement algorithm based on Max Intensity Channel

NASA Astrophysics Data System (ADS)

Sun, Wei; Han, Long; Guo, Baolong; Jia, Wenyan; Sun, Mingui

2014-03-01

In this paper, we extend image enhancement techniques based on the retinex theory imitating human visual perception of scenes containing high illumination variations. This extension achieves simultaneous dynamic range modification, color consistency, and lightness rendition without multi-scale Gaussian filtering which has a certain halo effect. The reflection component is analyzed based on the illumination and reflection imaging model. A new prior named Max Intensity Channel (MIC) is implemented assuming that the reflections of some points in the scene are very high in at least one color channel. Using this prior, the illumination of the scene is obtained directly by performing a gray-scale closing operation and a fast cross-bilateral filtering on the MIC of the input color image. Consequently, the reflection component of each RGB color channel can be determined from the illumination and reflection imaging model. The proposed algorithm estimates the illumination component which is relatively smooth and maintains the edge details in different regions. A satisfactory color rendition is achieved for a class of images that do not satisfy the gray-world assumption implicit to the theoretical foundation of the retinex. Experiments are carried out to compare the new method with several spatial and transform domain methods. Our results indicate that the new method is superior in enhancement applications, improves computation speed, and performs well for images with high illumination variations than other methods. Further comparisons of images from National Aeronautics and Space Administration and a wearable camera eButton have shown a high performance of the new method with better color restoration and preservation of image details.

Single-scale center-surround Retinex based restoration of low-illumination images with edge enhancement

NASA Astrophysics Data System (ADS)

Kwok, Ngaiming; Shi, Haiyan; Peng, Yeping; Wu, Hongkun; Li, Ruowei; Liu, Shilong; Rahman, Md Arifur

2018-04-01

Restoring images captured under low-illuminations is an essential front-end process for most image based applications. The Center-Surround Retinex algorithm has been a popular approach employed to improve image brightness. However, this algorithm in its basic form, is known to produce color degradations. In order to mitigate this problem, here the Single-Scale Retinex algorithm is modifid as an edge extractor while illumination is recovered through a non-linear intensity mapping stage. The derived edges are then integrated with the mapped image to produce the enhanced output. Furthermore, in reducing color distortion, the process is conducted in the magnitude sorted domain instead of the conventional Red-Green-Blue (RGB) color channels. Experimental results had shown that improvements with regard to mean brightness, colorfulness, saturation, and information content can be obtained.

Visual improvement for bad handwriting based on Monte-Carlo method

NASA Astrophysics Data System (ADS)

Shi, Cao; Xiao, Jianguo; Xu, Canhui; Jia, Wenhua

2014-03-01

A visual improvement algorithm based on Monte Carlo simulation is proposed in this paper, in order to enhance visual effects for bad handwriting. The whole improvement process is to use well designed typeface so as to optimize bad handwriting image. In this process, a series of linear operators for image transformation are defined for transforming typeface image to approach handwriting image. And specific parameters of linear operators are estimated by Monte Carlo method. Visual improvement experiments illustrate that the proposed algorithm can effectively enhance visual effect for handwriting image as well as maintain the original handwriting features, such as tilt, stroke order and drawing direction etc. The proposed visual improvement algorithm, in this paper, has a huge potential to be applied in tablet computer and Mobile Internet, in order to improve user experience on handwriting.

A micropixelated ion-imaging detector for mass resolution enhancement of a QMS instrument.

PubMed

Syed, Sarfaraz U A H; Eijkel, Gert B; Maher, Simon; Kistemaker, Piet; Taylor, Stephen; Heeren, Ron M A

2015-03-01

An in-vacuum position-sensitive micropixelated detector (Timepix) is used to investigate the time-dependent spatial distribution of different charge state (and hence different mass-to-charge (m/z)) ions exiting an electrospray ionization (ESI)-based quadrupole mass spectrometer (QMS) instrument. Ion images obtained from the Timepix detector provide a detailed insight into the positions of stable and unstable ions of the mass peak as they exit the QMS. With the help of image processing algorithms and by selecting areas on the ion images where more stable ions impact the detector, an improvement in mass resolution by a factor of 5 was obtained for certain operating conditions. Moreover, our experimental approach of mass resolution enhancement was confirmed by in-house-developed novel QMS instrument simulation software. Utilizing the imaging-based mass resolution enhancement approach, the software predicts instrument mass resolution of ∼1,0000 for a single-filter QMS instrument with a 210-mm long mass filter and a low operating frequency (880 kHz) of the radio frequency (RF) voltage.

Industrial X-Ray Imaging

NASA Technical Reports Server (NTRS)

1997-01-01

In 1990, Lewis Research Center jointly sponsored a conference with the U.S. Air Force Wright Laboratory focused on high speed imaging. This conference, and early funding by Lewis Research Center, helped to spur work by Silicon Mountain Design, Inc. to break the performance barriers of imaging speed, resolution, and sensitivity through innovative technology. Later, under a Small Business Innovation Research contract with the Jet Propulsion Laboratory, the company designed a real-time image enhancing camera that yields superb, high quality images in 1/30th of a second while limiting distortion. The result is a rapidly available, enhanced image showing significantly greater detail compared to image processing executed on digital computers. Current applications include radiographic and pathology-based medicine, industrial imaging, x-ray inspection devices, and automated semiconductor inspection equipment.

Simultaneous multiplexing and encoding of multiple images based on a double random phase encryption system

NASA Astrophysics Data System (ADS)

Alfalou, Ayman; Mansour, Ali

2009-09-01

Nowadays, protecting information is a major issue in any transmission system, as showed by an increasing number of research papers related to this topic. Optical encoding methods, such as a Double Random Phase encryption system i.e. DRP, are widely used and cited in the literature. DRP systems have very simple principle and they are easily applicable to most images (B&W, gray levels or color). Moreover, some applications require an enhanced encoding level based on multiencryption scheme and including biometric keys (as digital fingerprints). The enhancement should be done without increasing transmitted or stored information. In order to achieve that goal, a new approach for simultaneous multiplexing & encoding of several target images is developed in this manuscript. By introducing two additional security levels, our approach enhances the security level of a classic "DRP" system. Our first security level consists in using several independent image-keys (randomly and structurally) along with a new multiplexing algorithm. At this level, several target images (multiencryption) are used. This part can reduce needed information (encoding information). At the second level a standard DRP system is included. Finally, our approach can detect if any vandalism attempt has been done on transmitted encrypted images.

Combining knowledge discovery from databases (KDD) and case-based reasoning (CBR) to support diagnosis of medical images

NASA Astrophysics Data System (ADS)

Stranieri, Andrew; Yearwood, John; Pham, Binh

1999-07-01

The development of data warehouses for the storage and analysis of very large corpora of medical image data represents a significant trend in health care and research. Amongst other benefits, the trend toward warehousing enables the use of techniques for automatically discovering knowledge from large and distributed databases. In this paper, we present an application design for knowledge discovery from databases (KDD) techniques that enhance the performance of the problem solving strategy known as case- based reasoning (CBR) for the diagnosis of radiological images. The problem of diagnosing the abnormality of the cervical spine is used to illustrate the method. The design of a case-based medical image diagnostic support system has three essential characteristics. The first is a case representation that comprises textual descriptions of the image, visual features that are known to be useful for indexing images, and additional visual features to be discovered by data mining many existing images. The second characteristic of the approach presented here involves the development of a case base that comprises an optimal number and distribution of cases. The third characteristic involves the automatic discovery, using KDD techniques, of adaptation knowledge to enhance the performance of the case based reasoner. Together, the three characteristics of our approach can overcome real time efficiency obstacles that otherwise mitigate against the use of CBR to the domain of medical image analysis.

Generalized image contrast enhancement technique based on Heinemann contrast discrimination model

NASA Astrophysics Data System (ADS)

Liu, Hong; Nodine, Calvin F.

1994-03-01

This paper presents a generalized image contrast enhancement technique which equalizes perceived brightness based on the Heinemann contrast discrimination model. This is a modified algorithm which presents an improvement over the previous study by Mokrane in its mathematically proven existence of a unique solution and in its easily tunable parameterization. The model uses a log-log representation of contrast luminosity between targets and the surround in a fixed luminosity background setting. The algorithm consists of two nonlinear gray-scale mapping functions which have seven parameters, two of which are adjustable Heinemann constants. Another parameter is the background gray level. The remaining four parameters are nonlinear functions of gray scale distribution of the image, and can be uniquely determined once the previous three are given. Tests have been carried out to examine the effectiveness of the algorithm for increasing the overall contrast of images. It can be demonstrated that the generalized algorithm provides better contrast enhancement than histogram equalization. In fact, the histogram equalization technique is a special case of the proposed mapping.

Fluorescent Microscopy Enhancement Using Imaging

NASA Astrophysics Data System (ADS)

Conrad, Morgan P.; Reck tenwald, Diether J.; Woodhouse, Bryan S.

1986-06-01

To enhance our capabilities for observing fluorescent stains in biological systems, we are developing a low cost imaging system based around an IBM AT microcomputer and a commercial image capture board compatible with a standard RS-170 format video camera. The image is digitized in real time with 256 grey levels, while being displayed and also stored in memory. The software allows for interactive processing of the data, such as histogram equalization or pseudocolor enhancement of the display. The entire image, or a quadrant thereof, can be averaged over time to improve the signal to noise ratio. Images may be stored to disk for later use or comparison. The camera may be selected for better response in the UV or near IR. Combined with signal averaging, this increases the sensitivity relative to that of the human eye, while still allowing for the fluorescence distribution on either the surface or internal cytoskeletal structure to be observed.

Detection of fresh bruises in apples by structured-illumination reflectance imaging

NASA Astrophysics Data System (ADS)

Lu, Yuzhen; Li, Richard; Lu, Renfu

2016-05-01

Detection of fresh bruises in apples remains a challenging task due to the absence of visual symptoms and significant chemical alterations of fruit tissues during the initial stage after the fruit have been bruised. This paper reports on a new structured-illumination reflectance imaging (SIRI) technique for enhanced detection of fresh bruises in apples. Using a digital light projector engine, sinusoidally-modulated illumination at the spatial frequencies of 50, 100, 150 and 200 cycles/m was generated. A digital camera was then used to capture the reflectance images from `Gala' and `Jonagold' apples, immediately after they had been subjected to two levels of bruising by impact tests. A conventional three-phase demodulation (TPD) scheme was applied to the acquired images for obtaining the planar (direct component or DC) and amplitude (alternating component or AC) images. Bruises were identified in the amplitude images with varying image contrasts, depending on spatial frequency. The bruise visibility was further enhanced through post-processing of the amplitude images. Furthermore, three spiral phase transform (SPT)-based demodulation methods, using single and two images and two phase-shifted images, were proposed for obtaining AC images. Results showed that the demodulation methods greatly enhanced the contrast and spatial resolution of the AC images, making it feasible to detect the fresh bruises that, otherwise, could not be achieved by conventional imaging technique with planar or uniform illumination. The effectiveness of image enhancement, however, varied with spatial frequency. Both 2-image and 2-phase SPT methods achieved the performance similar to that by conventional TPD. SIRI technique has demonstrated the capability of detecting fresh bruises in apples, and it has the potential as a new imaging modality for enhancing food quality and safety detection.

Nano-Gap Embedded Plasmonic Gratings for Surface Plasmon Enhanced Fluorescence

NASA Astrophysics Data System (ADS)

Bhatnagar, Kunal; Bok, Sangho; Korampally, Venumadhav; Gangopadhyay, Shubhra

2012-02-01

Plasmonic nanostructures have been extensively used in the past few decades for applications in sub-wavelength optics, data storage, optoelectronic circuits, microscopy and bio-photonics. The enhanced electromagnetic field produced at the metal/dielectric interface by the excitation of surface plasmons via incident radiation can be used for signal enhancement in fluorescence and surface enhanced Raman scattering studies. Novel plasmonic structures on the sub wavelength scale have been shown to provide very efficient and extreme light concentration at the nano-scale. The enhanced electric field produced within a few hundred nanometers of these structures can be used to excite fluorophores in the surrounding environment. Fluorescence based bio-detection and bio-imaging are two of the most important tools in the life sciences. Improving the qualities and capabilities of fluorescence based detectors and imaging equipment has been a big challenge to the industry manufacturers. We report the novel fabrication of nano-gap embedded periodic grating substrates on the nanoscale using micro-contact printing and polymethylsilsesquioxane (PMSSQ) polymer. Fluorescence enhancement of up to 118 times was observed with these silver nanostructures in conjugation with Rhodamine-590 fluorescent dye. These substrates are ideal candidates for low-level fluorescence detection and single molecule imaging.

A framework for small infrared target real-time visual enhancement

NASA Astrophysics Data System (ADS)

Sun, Xiaoliang; Long, Gucan; Shang, Yang; Liu, Xiaolin

2015-03-01

This paper proposes a framework for small infrared target real-time visual enhancement. The framework is consisted of three parts: energy accumulation for small infrared target enhancement, noise suppression and weighted fusion. Dynamic programming based track-before-detection algorithm is adopted in the energy accumulation to detect the target accurately and enhance the target's intensity notably. In the noise suppression, the target region is weighted by a Gaussian mask according to the target's Gaussian shape. In order to fuse the processed target region and unprocessed background smoothly, the intensity in the target region is treated as weight in the fusion. Experiments on real small infrared target images indicate that the framework proposed in this paper can enhances the small infrared target markedly and improves the image's visual quality notably. The proposed framework outperforms tradition algorithms in enhancing the small infrared target, especially for image in which the target is hardly visible.

Assessment of contrast enhanced respiration managed cone-beam CT for image guided radiotherapy of intrahepatic tumors

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

Jensen, Nikolaj K. G., E-mail: nkyj@regionsjaelland.dk; Stewart, Errol; Imaging Research Lab, Robarts Research Institute, London, Ontario N6A 5B7

2014-05-15

Purpose: Contrast enhancement and respiration management are widely used during image acquisition for radiotherapy treatment planning of liver tumors along with respiration management at the treatment unit. However, neither respiration management nor intravenous contrast is commonly used during cone-beam CT (CBCT) image acquisition for alignment prior to radiotherapy. In this study, the authors investigate the potential gains of injecting an iodinated contrast agent in combination with respiration management during CBCT acquisition for liver tumor radiotherapy. Methods: Five rabbits with implanted liver tumors were subjected to CBCT with and without motion management and contrast injection. The acquired CBCT images were registeredmore » to the planning CT to determine alignment accuracy and dosimetric impact. The authors developed a simulation tool for simulating contrast-enhanced CBCT images from dynamic contrast enhanced CT imaging (DCE-CT) to determine optimal contrast injection protocols. The tool was validated against contrast-enhanced CBCT of the rabbit subjects and was used for five human patients diagnosed with hepatocellular carcinoma. Results: In the rabbit experiment, when neither motion management nor contrast was used, tumor centroid misalignment between planning image and CBCT was 9.2 mm. This was reduced to 2.8 mm when both techniques were employed. Tumors were not visualized in clinical CBCT images of human subjects. Simulated contrast-enhanced CBCT was found to improve tumor contrast in all subjects. Different patients were found to require different contrast injections to maximize tumor contrast. Conclusions: Based on the authors’ animal study, respiration managed contrast enhanced CBCT improves IGRT significantly. Contrast enhanced CBCT benefits from patient specific tracer kinetics determined from DCE-CT.« less

Smart light random memory sprays Retinex: a fast Retinex implementation for high-quality brightness adjustment and color correction.

PubMed

Banić, Nikola; Lončarić, Sven

2015-11-01

Removing the influence of illumination on image colors and adjusting the brightness across the scene are important image enhancement problems. This is achieved by applying adequate color constancy and brightness adjustment methods. One of the earliest models to deal with both of these problems was the Retinex theory. Some of the Retinex implementations tend to give high-quality results by performing local operations, but they are computationally relatively slow. One of the recent Retinex implementations is light random sprays Retinex (LRSR). In this paper, a new method is proposed for brightness adjustment and color correction that overcomes the main disadvantages of LRSR. There are three main contributions of this paper. First, a concept of memory sprays is proposed to reduce the number of LRSR's per-pixel operations to a constant regardless of the parameter values, thereby enabling a fast Retinex-based local image enhancement. Second, an effective remapping of image intensities is proposed that results in significantly higher quality. Third, the problem of LRSR's halo effect is significantly reduced by using an alternative illumination processing method. The proposed method enables a fast Retinex-based image enhancement by processing Retinex paths in a constant number of steps regardless of the path size. Due to the halo effect removal and remapping of the resulting intensities, the method outperforms many of the well-known image enhancement methods in terms of resulting image quality. The results are presented and discussed. It is shown that the proposed method outperforms most of the tested methods in terms of image brightness adjustment, color correction, and computational speed.

Super-Resolution Reconstruction of Remote Sensing Images Using Multifractal Analysis

PubMed Central

Hu, Mao-Gui; Wang, Jin-Feng; Ge, Yong

2009-01-01

Satellite remote sensing (RS) is an important contributor to Earth observation, providing various kinds of imagery every day, but low spatial resolution remains a critical bottleneck in a lot of applications, restricting higher spatial resolution analysis (e.g., intra-urban). In this study, a multifractal-based super-resolution reconstruction method is proposed to alleviate this problem. The multifractal characteristic is common in Nature. The self-similarity or self-affinity presented in the image is useful to estimate details at larger and smaller scales than the original. We first look for the presence of multifractal characteristics in the images. Then we estimate parameters of the information transfer function and noise of the low resolution image. Finally, a noise-free, spatial resolution-enhanced image is generated by a fractal coding-based denoising and downscaling method. The empirical case shows that the reconstructed super-resolution image performs well in detail enhancement. This method is not only useful for remote sensing in investigating Earth, but also for other images with multifractal characteristics. PMID:22291530

Hepatocellular carcinoma metastasizing to the skull base involving multiple cranial nerves.

PubMed

Kim, Soo Ryang; Kanda, Fumio; Kobessho, Hiroshi; Sugimoto, Koji; Matsuoka, Toshiyuki; Kudo, Masatoshi; Hayashi, Yoshitake

2006-11-07

We describe a rare case of HCV-related recurrent multiple hepatocellular carcinoma (HCC) metastasizing to the skull base involving multiple cranial nerves in a 50-year-old woman. The patient presented with symptoms of ptosis, fixation of the right eyeball, and left abducens palsy, indicating disturbances of the right oculomotor and trochlear nerves and bilateral abducens nerves. Brain contrast-enhanced computed tomography (CT) revealed an ill-defined mass with abnormal enhancement around the sella turcica. Brain magnetic resonance imaging (MRI) disclosed that the mass involved the clivus, cavernous sinus, and petrous apex. On contrast-enhanced MRI with gadolinium-chelated contrast medium, the mass showed inhomogeneous intermediate enhancement. The diagnosis of metastatic HCC to the skull base was made on the basis of neurological findings and imaging studies including CT and MRI, without histological examinations. Further studies may provide insights into various methods for diagnosing HCC metastasizing to the craniospinal area.

Enhanced Ultrasound Visualization of Brachytherapy Seeds by a Novel Magnetically Induced Motion Imaging Method

DTIC Science & Technology

2007-04-01

We report our progress in developing Magnetically Induced Motion Imaging (MIMI) for unambiguous identification and localization brachytherapy seeds ...tail artifacts in segmented seed images. The second is a method for joining ends of seeds in segmented seed images based on the phase of the detected

Preliminary results in large bone segmentation from 3D freehand ultrasound

NASA Astrophysics Data System (ADS)

Fanti, Zian; Torres, Fabian; Arámbula Cosío, Fernando

2013-11-01

Computer Assisted Orthopedic Surgery (CAOS) requires a correct registration between the patient in the operating room and the virtual models representing the patient in the computer. In order to increase the precision and accuracy of the registration a set of new techniques that eliminated the need to use fiducial markers have been developed. The majority of these newly developed registration systems are based on costly intraoperative imaging systems like Computed Tomography (CT scan) or Magnetic resonance imaging (MRI). An alternative to these methods is the use of an Ultrasound (US) imaging system for the implementation of a more cost efficient intraoperative registration solution. In order to develop the registration solution with the US imaging system, the bone surface is segmented in both preoperative and intraoperative images, and the registration is done using the acquire surface. In this paper, we present the a preliminary results of a new approach to segment bone surface from ultrasound volumes acquired by means 3D freehand ultrasound. The method is based on the enhancement of the voxels that belongs to surface and its posterior segmentation. The enhancement process is based on the information provided by eigenanalisis of the multiscale 3D Hessian matrix. The preliminary results shows that from the enhance volume the final bone surfaces can be extracted using a singular value thresholding.

Accelerating non-contrast-enhanced MR angiography with inflow inversion recovery imaging by skipped phase encoding and edge deghosting (SPEED).

PubMed

Chang, Zheng; Xiang, Qing-San; Shen, Hao; Yin, Fang-Fang

2010-03-01

To accelerate non-contrast-enhanced MR angiography (MRA) with inflow inversion recovery (IFIR) with a fast imaging method, Skipped Phase Encoding and Edge Deghosting (SPEED). IFIR imaging uses a preparatory inversion pulse to reduce signals from static tissue, while leaving inflow arterial blood unaffected, resulting in sparse arterial vasculature on modest tissue background. By taking advantage of vascular sparsity, SPEED can be simplified with a single-layer model to achieve higher efficiency in both scan time reduction and image reconstruction. SPEED can also make use of information available in multiple coils for further acceleration. The techniques are demonstrated with a three-dimensional renal non-contrast-enhanced IFIR MRA study. Images are reconstructed by SPEED based on a single-layer model to achieve an undersampling factor of up to 2.5 using one skipped phase encoding direction. By making use of information available in multiple coils, SPEED can achieve an undersampling factor of up to 8.3 with four receiver coils. The reconstructed images generally have comparable quality as that of the reference images reconstructed from full k-space data. As demonstrated with a three-dimensional renal IFIR scan, SPEED based on a single-layer model is able to reduce scan time further and achieve higher computational efficiency than the original SPEED.

Combining deep learning with anatomical analysis for segmentation of the portal vein for liver SBRT planning

NASA Astrophysics Data System (ADS)

Ibragimov, Bulat; Toesca, Diego; Chang, Daniel; Koong, Albert; Xing, Lei

2017-12-01

Automated segmentation of the portal vein (PV) for liver radiotherapy planning is a challenging task due to potentially low vasculature contrast, complex PV anatomy and image artifacts originated from fiducial markers and vasculature stents. In this paper, we propose a novel framework for automated segmentation of the PV from computed tomography (CT) images. We apply convolutional neural networks (CNNs) to learn the consistent appearance patterns of the PV using a training set of CT images with reference annotations and then enhance the PV in previously unseen CT images. Markov random fields (MRFs) were further used to smooth the results of the enhancement of the CNN enhancement and remove isolated mis-segmented regions. Finally, CNN-MRF-based enhancement was augmented with PV centerline detection that relied on PV anatomical properties such as tubularity and branch composition. The framework was validated on a clinical database with 72 CT images of patients scheduled for liver stereotactic body radiation therapy. The obtained accuracy of the segmentation was DSC= 0.83 and \

Locally Enhanced Image Quality with Tunable Hybrid Metasurfaces

NASA Astrophysics Data System (ADS)

Shchelokova, Alena V.; Slobozhanyuk, Alexey P.; Melchakova, Irina V.; Glybovski, Stanislav B.; Webb, Andrew G.; Kivshar, Yuri S.; Belov, Pavel A.

2018-01-01

Metasurfaces represent a new paradigm in artificial subwavelength structures due to their potential to overcome many challenges typically associated with bulk metamaterials. The ability to make very thin structures and change their properties dynamically makes metasurfaces an exceptional meta-optics platform for engineering advanced electromagnetic and photonic metadevices. Here, we suggest and demonstrate experimentally a tunable metasurface capable of enhancing significantly the local image quality in magnetic resonance imaging. We present a design of the hybrid metasurface based on electromagnetically coupled dielectric and metallic elements. We demonstrate how to tailor the spectral characteristics of the metasurface eigenmodes by changing dynamically the effective permittivity of the structure. By maximizing a coupling between metasurface eigenmodes and transmitted and received fields in the magnetic resonance imaging (MRI) system, we enhance the device sensitivity that results in a substantial improvement of the image quality.

Comparison of image enhancement methods for the effective diagnosis in successive whole-body bone scans.

PubMed

Jeong, Chang Bu; Kim, Kwang Gi; Kim, Tae Sung; Kim, Seok Ki

2011-06-01

Whole-body bone scan is one of the most frequent diagnostic procedures in nuclear medicine. Especially, it plays a significant role in important procedures such as the diagnosis of osseous metastasis and evaluation of osseous tumor response to chemotherapy and radiation therapy. It can also be used to monitor the possibility of any recurrence of the tumor. However, it is a very time-consuming effort for radiologists to quantify subtle interval changes between successive whole-body bone scans because of many variations such as intensity, geometry, and morphology. In this paper, we present the most effective method of image enhancement based on histograms, which may assist radiologists in interpreting successive whole-body bone scans effectively. Forty-eight successive whole-body bone scans from 10 patients were obtained and evaluated using six methods of image enhancement based on histograms: histogram equalization, brightness-preserving bi-histogram equalization, contrast-limited adaptive histogram equalization, end-in search, histogram matching, and exact histogram matching (EHM). Comparison of the results of the different methods was made using three similarity measures peak signal-to-noise ratio, histogram intersection, and structural similarity. Image enhancement of successive bone scans using EHM showed the best results out of the six methods measured for all similarity measures. EHM is the best method of image enhancement based on histograms for diagnosing successive whole-body bone scans. The method for successive whole-body bone scans has the potential to greatly assist radiologists quantify interval changes more accurately and quickly by compensating for the variable nature of intensity information. Consequently, it can improve radiologists' diagnostic accuracy as well as reduce reading time for detecting interval changes.

Enhanced Imaging of Specific Cell-Surface Glycosylation Based on Multi-FRET.

PubMed

Yuan, Baoyin; Chen, Yuanyuan; Sun, Yuqiong; Guo, Qiuping; Huang, Jin; Liu, Jianbo; Meng, Xiangxian; Yang, Xiaohai; Wen, Xiaohong; Li, Zenghui; Li, Lie; Wang, Kemin

2018-05-15

Cell-surface glycosylation contains abundant biological information that reflects cell physiological state, and it is of great value to image cell-surface glycosylation to elucidate its functions. Here we present a hybridization chain reaction (HCR)-based multifluorescence resonance energy transfer (multi-FRET) method for specific imaging of cell-surface glycosylation. By installing donors through metabolic glycan labeling and acceptors through aptamer-tethered nanoassemblies on the same glycoconjugate, intramolecular multi-FRET occurs due to near donor-acceptor distance. Benefiting from amplified effect and spatial flexibility of the HCR nanoassemblies, enhanced multi-FRET imaging of specific cell-surface glycosylation can be obtained. With this HCR-based multi-FRET method, we achieved obvious contrast in imaging of protein-specific GalNAcylation on 7211 cell surfaces. In addition, we demonstrated the general applicability of this method by visualizing the protein-specific sialylation on CEM cell surfaces. Furthermore, the expression changes of CEM cell-surface protein-specific sialylation under drug treatment was accurately monitored. This developed imaging method may provide a powerful tool in researching glycosylation functions, discovering biomarkers, and screening drugs.

[Non-contrast time-resolved magnetic resonance angiography combining high resolution multiple phase echo planar imaging based signal targeting and alternating radiofrequency contrast inherent inflow enhanced multi phase angiography combining spatial resolution echo planar imaging based signal targeting and alternating radiofrequency in intracranial arteries].

PubMed

Nakamura, Masanobu; Yoneyama, Masami; Tabuchi, Takashi; Takemura, Atsushi; Obara, Makoto; Sawano, Seishi

2012-01-01

Detailed information on anatomy and hemodynamics in cerebrovascular disorders such as AVM and Moyamoya disease is mandatory for defined diagnosis and treatment planning. Arterial spin labeling technique has come to be applied to magnetic resonance angiography (MRA) and perfusion imaging in recent years. However, those non-contrast techniques are mostly limited to single frame images. Recently we have proposed a non-contrast time-resolved MRA technique termed contrast inherent inflow enhanced multi phase angiography combining spatial resolution echo planar imaging based signal targeting and alternating radiofrequency (CINEMA-STAR). CINEMA-STAR can extract the blood flow in the major intracranial arteries at an interval of 70 ms and thus permits us to observe vascular construction in full by preparing MIP images of axial acquisitions with high spatial resolution. This preliminary study demonstrates the usefulness of the CINEMA-STAR technique in evaluating the cerebral vasculature.

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.

An overview of methods to mitigate artifacts in optical coherence tomography imaging of the skin.

PubMed

Adabi, Saba; Fotouhi, Audrey; Xu, Qiuyun; Daveluy, Steve; Mehregan, Darius; Podoleanu, Adrian; Nasiriavanaki, Mohammadreza

2018-05-01

Optical coherence tomography (OCT) of skin delivers three-dimensional images of tissue microstructures. Although OCT imaging offers a promising high-resolution modality, OCT images suffer from some artifacts that lead to misinterpretation of tissue structures. Therefore, an overview of methods to mitigate artifacts in OCT imaging of the skin is of paramount importance. Speckle, intensity decay, and blurring are three major artifacts in OCT images. Speckle is due to the low coherent light source used in the configuration of OCT. Intensity decay is a deterioration of light with respect to depth, and blurring is the consequence of deficiencies of optical components. Two speckle reduction methods (one based on artificial neural network and one based on spatial compounding), an attenuation compensation algorithm (based on Beer-Lambert law) and a deblurring procedure (using deconvolution), are described. Moreover, optical properties extraction algorithm based on extended Huygens-Fresnel (EHF) principle to obtain some additional information from OCT images are discussed. In this short overview, we summarize some of the image enhancement algorithms for OCT images which address the abovementioned artifacts. The results showed a significant improvement in the visibility of the clinically relevant features in the images. The quality improvement was evaluated using several numerical assessment measures. Clinical dermatologists benefit from using these image enhancement algorithms to improve OCT diagnosis and essentially function as a noninvasive optical biopsy. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Raman Imaging in Cell Membranes, Lipid-Rich Organelles, and Lipid Bilayers.

PubMed

Syed, Aleem; Smith, Emily A

2017-06-12

Raman-based optical imaging is a promising analytical tool for noninvasive, label-free chemical imaging of lipid bilayers and cellular membranes. Imaging using spontaneous Raman scattering suffers from a low intensity that hinders its use in some cellular applications. However, developments in coherent Raman imaging, surface-enhanced Raman imaging, and tip-enhanced Raman imaging have enabled video-rate imaging, excellent detection limits, and nanometer spatial resolution, respectively. After a brief introduction to these commonly used Raman imaging techniques for cell membrane studies, this review discusses selected applications of these modalities for chemical imaging of membrane proteins and lipids. Finally, recent developments in chemical tags for Raman imaging and their applications in the analysis of selected cell membrane components are summarized. Ongoing developments toward improving the temporal and spatial resolution of Raman imaging and small-molecule tags with strong Raman scattering cross sections continue to expand the utility of Raman imaging for diverse cell membrane studies.

"If You Look the Part You'll Get the Job": Should Career Professionals Help Clients to Enhance Their Career Image?

ERIC Educational Resources Information Center

Hooley, Tristram; Yates, Julia

2015-01-01

This article presents a critical exploration of the role of career professionals in supporting people to reflect on and enhance their appearance, attractiveness and self-presentation (career image). The article is conceptual and based on a review of the broader literature on career success, appearance and attractiveness. It explores the evidence…

Measuring perceived video quality of MPEG enhancement by people with impaired vision

PubMed Central

Fullerton, Matthew; Woods, Russell L.; Vera-Diaz, Fuensanta A.; Peli, Eli

2007-01-01

We used a new method to measure the perceived quality of contrast-enhanced motion video. Patients with impaired vision (n = 24) and normally-sighted subjects (n = 6) adjusted the level of MPEG-based enhancement of 8 videos (4 minutes each) drawn from 4 categories. They selected the level of enhancement that provided the preferred view of the videos, using a reducing-step-size staircase procedure. Most patients made consistent selections of the preferred level of enhancement, indicating an appreciation of and a perceived benefit from the MPEG-based enhancement. The selections varied between patients and were correlated with letter contrast sensitivity, but the selections were not affected by training, experience or video category. We measured just noticeable differences (JNDs) directly for videos, and mapped the image manipulation (enhancement in our case) onto an approximately linear perceptual space. These tools and approaches will be of value in other evaluations of the image quality of motion video manipulations. PMID:18059909

Pushing the sensitivity envelope of lanthanide-based magnetic resonance imaging (MRI) contrast agents for molecular imaging applications.

PubMed

Aime, Silvio; Castelli, Daniela Delli; Crich, Simonetta Geninatti; Gianolio, Eliana; Terreno, Enzo

2009-07-21

Contrast in magnetic resonance imaging (MRI) arises from changes in the intensity of the proton signal of water between voxels (essentially, the 3D counterpart of pixels). Differences in intervoxel intensity can be significantly enhanced with chemicals that alter the nuclear magnetic resonance (NMR) intensity of the imaged spins; this alteration can occur by various mechanisms. Paramagnetic lanthanide(III) complexes are used in two major classes of MRI contrast agent: the well-established class of Gd-based agents and the emerging class of chemical exchange saturation transfer (CEST) agents. A Gd-based complex increases water signal by enhancing the longitudinal relaxation rate of water protons, whereas CEST agents decrease water signal as a consequence of the transfer of saturated magnetization from the exchangeable protons of the agent. In this Account, we survey recent progress in both areas, focusing on how MRI is becoming a more competitive choice among the various molecular imaging methods. Compared with other imaging modalities, MRI is set apart by its superb anatomical resolution; however, its success in molecular imaging suffers because of its intrinsic insensitivity. A relatively high concentration of molecular agents (0.01-0.1 mM) is necessary to produce a local alteration in the water signal intensity. Unfortunately, the most desirable molecules for visualization in molecular imaging are present at much lower concentrations, in the nano- or picomolar range. Therefore, augmenting the sensitivity of MRI agents is key to the development of MR-based molecular imaging applications. In principle, this task can be tackled either by increasing the sensitivity of the reporting units, through the optimization of their structural and dynamic properties, or by setting up proper amplification strategies that allow the accumulation of a huge number of imaging reporters at the site of interest. For Gd-based agents, high sensitivities can be attained by exploiting a range of nanosized carriers (micelles, liposomes, microemulsions, and the like, as well as biological structures such as apoferritin and lipoproteins) properly loaded with Gd-based chelates. Furthermore, the sensitivity of Gd-based agents can be markedly affected either by their interactions with biological structures or by their cellular localization. For CEST agents, a huge sensitivity enhancement has been obtained by using the water molecules contained in the inner cavity of liposomes as the exchangeable source of protons for magnetization transfer. Several "tricks" (for example, the use of multimeric lanthanide(III) shift reagents, changes in the shape of the liposome container, and so forth) have been devised to improve the chemical shift separation between the intraliposomal water and the "bulk" water resonances. Overall, excellent sensitivity enhancements have been obtained for both classes of agents, enabling their use in MR molecular imaging applications.

Noninvasive Classification of Hepatic Fibrosis Based on Texture Parameters From Double Contrast-Enhanced Magnetic Resonance Images

PubMed Central

Bahl, Gautam; Cruite, Irene; Wolfson, Tanya; Gamst, Anthony C.; Collins, Julie M.; Chavez, Alyssa D.; Barakat, Fatma; Hassanein, Tarek; Sirlin, Claude B.

2016-01-01

Purpose To demonstrate a proof of concept that quantitative texture feature analysis of double contrast-enhanced magnetic resonance imaging (MRI) can classify fibrosis noninvasively, using histology as a reference standard. Materials and Methods A Health Insurance Portability and Accountability Act (HIPAA)-compliant Institutional Review Board (IRB)-approved retrospective study of 68 patients with diffuse liver disease was performed at a tertiary liver center. All patients underwent double contrast-enhanced MRI, with histopathology-based staging of fibrosis obtained within 12 months of imaging. The MaZda software program was used to compute 279 texture parameters for each image. A statistical regularization technique, generalized linear model (GLM)-path, was used to develop a model based on texture features for dichotomous classification of fibrosis category (F ≤2 vs. F ≥3) of the 68 patients, with histology as the reference standard. The model's performance was assessed and cross-validated. There was no additional validation performed on an independent cohort. Results Cross-validated sensitivity, specificity, and total accuracy of the texture feature model in classifying fibrosis were 91.9%, 83.9%, and 88.2%, respectively. Conclusion This study shows proof of concept that accurate, noninvasive classification of liver fibrosis is possible by applying quantitative texture analysis to double contrast-enhanced MRI. Further studies are needed in independent cohorts of subjects. PMID:22851409

Construction of Silica-Based Micro/Nanoplatforms for Ultrasound Theranostic Biomedicine.

PubMed

Zhou, Yang; Han, Xiaoxia; Jing, Xiangxiang; Chen, Yu

2017-09-01

Ultrasound (US)-based biomedicine has been extensively explored for its applications in both diagnostic imaging and disease therapy. The fast development of theranostic nanomedicine significantly promotes the development of US-based biomedicine. This progress report summarizes and discusses the recent developments of rational design and fabrication of silica-based micro/nanoparticles for versatile US-based biomedical applications. The synthetic strategies and surface-engineering approaches of silica-based micro/nanoparticles are initially discussed, followed by detailed introduction on their US-based theranostic applications. They have been extensively explored in contrast-enhanced US imaging, US-based multi-modality imaging, synergistic high-intensity focused US (HIFU) ablation, sonosensitizer-enhanced sonodynamic therapy (SDT), as well as US-triggered chemotherapy. Their biological effects and biosafety have been briefly discussed to guarantee further clinical translation. Based on the high biocompatibility, versatile composition/structure and high performance in US-based theranostic biomedicine, these silica-based theranostic agents are expected to pave a new way for achieving efficient US-based theranostics of disease by taking the specific advantages of material science, nanotechnology and US-based biomedicine. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Deep neural network-based bandwidth enhancement of photoacoustic data.

PubMed

Gutta, Sreedevi; Kadimesetty, Venkata Suryanarayana; Kalva, Sandeep Kumar; Pramanik, Manojit; Ganapathy, Sriram; Yalavarthy, Phaneendra K

2017-11-01

Photoacoustic (PA) signals collected at the boundary of tissue are always band-limited. A deep neural network was proposed to enhance the bandwidth (BW) of the detected PA signal, thereby improving the quantitative accuracy of the reconstructed PA images. A least square-based deconvolution method that utilizes the Tikhonov regularization framework was used for comparison with the proposed network. The proposed method was evaluated using both numerical and experimental data. The results indicate that the proposed method was capable of enhancing the BW of the detected PA signal, which inturn improves the contrast recovery and quality of reconstructed PA images without adding any significant computational burden. (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

High-contrast fluorescence imaging based on the polarization dependence of the fluorescence enhancement using an optical interference mirror slide.

PubMed

Yasuda, Mitsuru; Akimoto, Takuo

2015-01-01

High-contrast fluorescence imaging using an optical interference mirror (OIM) slide that enhances the fluorescence from a fluorophore located on top of the OIM surface is reported. To enhance the fluorescence and reduce the background light of the OIM, transverse-electric-polarized excitation light was used as incident light, and the transverse-magnetic-polarized fluorescence signal was detected. As a result, an approximate 100-fold improvement in the signal-to-noise ratio was achieved through a 13-fold enhancement of the fluorescence signal and an 8-fold reduction of the background light.

Automated, on-board terrain analysis for precision landings

NASA Technical Reports Server (NTRS)

Rahman, Zia-ur; Jobson, Daniel J.; Woodell, Glenn A.; Hines, Glenn D.

2006-01-01

Advances in space robotics technology hinge to a large extent upon the development and deployment of sophisticated new vision-based methods for automated in-space mission operations and scientific survey. To this end, we have developed a new concept for automated terrain analysis that is based upon a generic image enhancement platform|multi-scale retinex (MSR) and visual servo (VS) processing. This pre-conditioning with the MSR and the vs produces a "canonical" visual representation that is largely independent of lighting variations, and exposure errors. Enhanced imagery is then processed with a biologically inspired two-channel edge detection process, followed by a smoothness based criteria for image segmentation. Landing sites can be automatically determined by examining the results of the smoothness-based segmentation which shows those areas in the image that surpass a minimum degree of smoothness. Though the msr has proven to be a very strong enhancement engine, the other elements of the approach|the vs, terrain map generation, and smoothness-based segmentation|are in early stages of development. Experimental results on data from the Mars Global Surveyor show that the imagery can be processed to automatically obtain smooth landing sites. In this paper, we describe the method used to obtain these landing sites, and also examine the smoothness criteria in terms of the imager and scene characteristics. Several examples of applying this method to simulated and real imagery are shown.

Intra-operative registration for image enhanced endoscopic sinus surgery using photo-consistency.

PubMed

Chen, Min Si; Gonzalez, Gerardo; Lapeer, Rudy

2007-01-01

The purpose of this paper is to present an intensity based algorithm for aligning 2D endoscopic images with virtual images generated from pre-operative 3D data. The proposed algorithm uses photo-consistency as the measurement of similarity between images, provided the illumination is independent from the viewing direction.

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.

Application of Super-Resolution Convolutional Neural Network for Enhancing Image Resolution in Chest CT.

PubMed

Umehara, Kensuke; Ota, Junko; Ishida, Takayuki

2017-10-18

In this study, the super-resolution convolutional neural network (SRCNN) scheme, which is the emerging deep-learning-based super-resolution method for enhancing image resolution in chest CT images, was applied and evaluated using the post-processing approach. For evaluation, 89 chest CT cases were sampled from The Cancer Imaging Archive. The 89 CT cases were divided randomly into 45 training cases and 44 external test cases. The SRCNN was trained using the training dataset. With the trained SRCNN, a high-resolution image was reconstructed from a low-resolution image, which was down-sampled from an original test image. For quantitative evaluation, two image quality metrics were measured and compared to those of the conventional linear interpolation methods. The image restoration quality of the SRCNN scheme was significantly higher than that of the linear interpolation methods (p < 0.001 or p < 0.05). The high-resolution image reconstructed by the SRCNN scheme was highly restored and comparable to the original reference image, in particular, for a ×2 magnification. These results indicate that the SRCNN scheme significantly outperforms the linear interpolation methods for enhancing image resolution in chest CT images. The results also suggest that SRCNN may become a potential solution for generating high-resolution CT images from standard CT images.

Optical image transformation and encryption by phase-retrieval-based double random-phase encoding and compressive ghost imaging

NASA Astrophysics Data System (ADS)

Yuan, Sheng; Yang, Yangrui; Liu, Xuemei; Zhou, Xin; Wei, Zhenzhuo

2018-01-01

An optical image transformation and encryption scheme is proposed based on double random-phase encoding (DRPE) and compressive ghost imaging (CGI) techniques. In this scheme, a secret image is first transformed into a binary image with the phase-retrieval-based DRPE technique, and then encoded by a series of random amplitude patterns according to the ghost imaging (GI) principle. Compressive sensing, corrosion and expansion operations are implemented to retrieve the secret image in the decryption process. This encryption scheme takes the advantage of complementary capabilities offered by the phase-retrieval-based DRPE and GI-based encryption techniques. That is the phase-retrieval-based DRPE is used to overcome the blurring defect of the decrypted image in the GI-based encryption, and the CGI not only reduces the data amount of the ciphertext, but also enhances the security of DRPE. Computer simulation results are presented to verify the performance of the proposed encryption scheme.

Digital watermarking algorithm research of color images based on quaternion Fourier transform

NASA Astrophysics Data System (ADS)

An, Mali; Wang, Weijiang; Zhao, Zhen

2013-10-01

A watermarking algorithm of color images based on the quaternion Fourier Transform (QFFT) and improved quantization index algorithm (QIM) is proposed in this paper. The original image is transformed by QFFT, the watermark image is processed by compression and quantization coding, and then the processed watermark image is embedded into the components of the transformed original image. It achieves embedding and blind extraction of the watermark image. The experimental results show that the watermarking algorithm based on the improved QIM algorithm with distortion compensation achieves a good tradeoff between invisibility and robustness, and better robustness for the attacks of Gaussian noises, salt and pepper noises, JPEG compression, cropping, filtering and image enhancement than the traditional QIM algorithm.

Digital Imaging

NASA Technical Reports Server (NTRS)

1986-01-01

Digital Imaging is the computer processed numerical representation of physical images. Enhancement of images results in easier interpretation. Quantitative digital image analysis by Perceptive Scientific Instruments, locates objects within an image and measures them to extract quantitative information. Applications are CAT scanners, radiography, microscopy in medicine as well as various industrial and manufacturing uses. The PSICOM 327 performs all digital image analysis functions. It is based on Jet Propulsion Laboratory technology, is accurate and cost efficient.

Performance enhancement of various real-time image processing techniques via speculative execution

NASA Astrophysics Data System (ADS)

Younis, Mohamed F.; Sinha, Purnendu; Marlowe, Thomas J.; Stoyenko, Alexander D.

1996-03-01

In real-time image processing, an application must satisfy a set of timing constraints while ensuring the semantic correctness of the system. Because of the natural structure of digital data, pure data and task parallelism have been used extensively in real-time image processing to accelerate the handling time of image data. These types of parallelism are based on splitting the execution load performed by a single processor across multiple nodes. However, execution of all parallel threads is mandatory for correctness of the algorithm. On the other hand, speculative execution is an optimistic execution of part(s) of the program based on assumptions on program control flow or variable values. Rollback may be required if the assumptions turn out to be invalid. Speculative execution can enhance average, and sometimes worst-case, execution time. In this paper, we target various image processing techniques to investigate applicability of speculative execution. We identify opportunities for safe and profitable speculative execution in image compression, edge detection, morphological filters, and blob recognition.

Line-scan hyperspectral imaging platform for agro-food safety and quality evaluation: System enhancement and characterization

USDA-ARS?s Scientific Manuscript database

Line-scan-based hyperspectral imaging techniques have often served as a research tool to develop rapid multispectral methods based on only a few spectral bands for rapid online applications. With continuing technological advances and greater accessibility to and availability of optoelectronic imagin...

Size effect of Au/PAMAM contrast agent on CT imaging of reticuloendothelial system and tumor tissue

NASA Astrophysics Data System (ADS)

Wang, Wei; Li, Jian; Liu, Ransheng; Zhang, Aixu; Yuan, Zhiyong

2016-09-01

Polyamidoamine (PAMAM)-entrapped Au nanoparticles were synthesized with distinct sizes to figure out the size effect of Au-based contrast agent on CT imaging of passively targeted tissues. Au/PAMAM nanoparticles were first synthesized with narrow distribution of particles size of 22.2 ± 3.1, 54.2 ± 3.7, and 104.9 ± 4.7 nm in diameters. Size effect leads no significant difference on X-ray attenuation when Au/PAMAM was ≤0.05 mol/L. For CT imaging of a tumor model, small Au/PAMAM were more easily internalized via endocytosis in the liver, leading to more obviously enhanced contrast. Similarly, contrast agents with small sizes were more effective in tumor imaging because of the enhanced permeability and retention effect. Overall, the particle size of Au/PAMAM heavily affected the efficiency of CT enhancement in imaging RES and tumors.

Realization of a single image haze removal system based on DaVinci DM6467T processor

NASA Astrophysics Data System (ADS)

Liu, Zhuang

2014-10-01

Video monitoring system (VMS) has been extensively applied in domains of target recognition, traffic management, remote sensing, auto navigation and national defence. However the VMS has a strong dependence on the weather, for instance, in foggy weather, the quality of images received by the VMS are distinct degraded and the effective range of VMS is also decreased. All in all, the VMS performs terribly in bad weather. Thus the research of fog degraded images enhancement has very high theoretical and practical application value. A design scheme of a fog degraded images enhancement system based on the TI DaVinci processor is presented in this paper. The main function of the referred system is to extract and digital cameras capture images and execute image enhancement processing to obtain a clear image. The processor used in this system is the dual core TI DaVinci DM6467T - ARM@500MHz+DSP@1GH. A MontaVista Linux operating system is running on the ARM subsystem which handles I/O and application processing. The DSP handles signal processing and the results are available to the ARM subsystem in shared memory.The system benefits from the DaVinci processor so that, with lower power cost and smaller volume, it provides the equivalent image processing capability of a X86 computer. The outcome shows that the system in this paper can process images at 25 frames per second on D1 resolution.

Rotation covariant image processing for biomedical applications.

PubMed

Skibbe, Henrik; Reisert, Marco

2013-01-01

With the advent of novel biomedical 3D image acquisition techniques, the efficient and reliable analysis of volumetric images has become more and more important. The amount of data is enormous and demands an automated processing. The applications are manifold, ranging from image enhancement, image reconstruction, and image description to object/feature detection and high-level contextual feature extraction. In most scenarios, it is expected that geometric transformations alter the output in a mathematically well-defined manner. In this paper we emphasis on 3D translations and rotations. Many algorithms rely on intensity or low-order tensorial-like descriptions to fulfill this demand. This paper proposes a general mathematical framework based on mathematical concepts and theories transferred from mathematical physics and harmonic analysis into the domain of image analysis and pattern recognition. Based on two basic operations, spherical tensor differentiation and spherical tensor multiplication, we show how to design a variety of 3D image processing methods in an efficient way. The framework has already been applied to several biomedical applications ranging from feature and object detection tasks to image enhancement and image restoration techniques. In this paper, the proposed methods are applied on a variety of different 3D data modalities stemming from medical and biological sciences.

Temporal subtraction contrast-enhanced dedicated breast CT

NASA Astrophysics Data System (ADS)

Gazi, Peymon M.; Aminololama-Shakeri, Shadi; Yang, Kai; Boone, John M.

2016-09-01

The development of a framework of deformable image registration and segmentation for the purpose of temporal subtraction contrast-enhanced breast CT is described. An iterative histogram-based two-means clustering method was used for the segmentation. Dedicated breast CT images were segmented into background (air), adipose, fibroglandular and skin components. Fibroglandular tissue was classified as either normal or contrast-enhanced then divided into tiers for the purpose of categorizing degrees of contrast enhancement. A variant of the Demons deformable registration algorithm, intensity difference adaptive Demons (IDAD), was developed to correct for the large deformation forces that stemmed from contrast enhancement. In this application, the accuracy of the proposed method was evaluated in both mathematically-simulated and physically-acquired phantom images. Clinical usage and accuracy of the temporal subtraction framework was demonstrated using contrast-enhanced breast CT datasets from five patients. Registration performance was quantified using normalized cross correlation (NCC), symmetric uncertainty coefficient, normalized mutual information (NMI), mean square error (MSE) and target registration error (TRE). The proposed method outperformed conventional affine and other Demons variations in contrast enhanced breast CT image registration. In simulation studies, IDAD exhibited improvement in MSE (0-16%), NCC (0-6%), NMI (0-13%) and TRE (0-34%) compared to the conventional Demons approaches, depending on the size and intensity of the enhancing lesion. As lesion size and contrast enhancement levels increased, so did the improvement. The drop in the correlation between the pre- and post-contrast images for the largest enhancement levels in phantom studies is less than 1.2% (150 Hounsfield units). Registration error, measured by TRE, shows only submillimeter mismatches between the concordant anatomical target points in all patient studies. The algorithm was implemented using a parallel processing architecture resulting in rapid execution time for the iterative segmentation and intensity-adaptive registration techniques. Characterization of contrast-enhanced lesions is improved using temporal subtraction contrast-enhanced dedicated breast CT. Adaptation of Demons registration forces as a function of contrast-enhancement levels provided a means to accurately align breast tissue in pre- and post-contrast image acquisitions, improving subtraction results. Spatial subtraction of the aligned images yields useful diagnostic information with respect to enhanced lesion morphology and uptake.

Tectonic evaluation of the Nubian shield of Northeastern Sudan using thematic mapper imagery

NASA Technical Reports Server (NTRS)

1986-01-01

Bechtel is nearing completion of a one-year program that uses digitally enhanced LANDSAT Thematic Mapper (TM) data to compile the first comprehensive regional tectonic map of the Proterozoic Nubian Shield exposed in the northern Red Sea Hills of northeastern Sudan. The status of significant objectives of this study are given. Pertinent published and unpublished geologic literature and maps of the northern Red Sea Hills to establish the geologic framework of the region were reviewed. Thematic mapper imagery for optimal base-map enhancements was processed. Photo mosaics of enhanced images to serve as base maps for compilation of geologic information were completed. Interpretation of TM imagery to define and delineate structural and lithogologic provinces was completed. Geologic information (petrologic, and radiometric data) was compiled from the literature review onto base-map overlays. Evaluation of the tectonic evolution of the Nubian Shield based on the image interpretation and the compiled tectonic maps is continuing.

Depth image enhancement using perceptual texture priors

NASA Astrophysics Data System (ADS)

Bang, Duhyeon; Shim, Hyunjung

2015-03-01

A depth camera is widely used in various applications because it provides a depth image of the scene in real time. However, due to the limited power consumption, the depth camera presents severe noises, incapable of providing the high quality 3D data. Although the smoothness prior is often employed to subside the depth noise, it discards the geometric details so to degrade the distance resolution and hinder achieving the realism in 3D contents. In this paper, we propose a perceptual-based depth image enhancement technique that automatically recovers the depth details of various textures, using a statistical framework inspired by human mechanism of perceiving surface details by texture priors. We construct the database composed of the high quality normals. Based on the recent studies in human visual perception (HVP), we select the pattern density as a primary feature to classify textures. Upon the classification results, we match and substitute the noisy input normals with high quality normals in the database. As a result, our method provides the high quality depth image preserving the surface details. We expect that our work is effective to enhance the details of depth image from 3D sensors and to provide a high-fidelity virtual reality experience.

Fast and robust brain tumor segmentation using level set method with multiple image information.

PubMed

Lok, Ka Hei; Shi, Lin; Zhu, Xianlun; Wang, Defeng

2017-01-01

Brain tumor segmentation is a challenging task for its variation in intensity. The phenomenon is caused by the inhomogeneous content of tumor tissue and the choice of imaging modality. In 2010 Zhang developed the Selective Binary Gaussian Filtering Regularizing Level Set (SBGFRLS) model that combined the merits of edge-based and region-based segmentation. To improve the SBGFRLS method by modifying the singed pressure force (SPF) term with multiple image information and demonstrate effectiveness of proposed method on clinical images. In original SBGFRLS model, the contour evolution direction mainly depends on the SPF. By introducing a directional term in SPF, the metric could control the evolution direction. The SPF is altered by statistic values enclosed by the contour. This concept can be extended to jointly incorporate multiple image information. The new SPF term is expected to bring a solution for blur edge problem in brain tumor segmentation. The proposed method is validated with clinical images including pre- and post-contrast magnetic resonance images. The accuracy and robustness is compared with sensitivity, specificity, DICE similarity coefficient and Jaccard similarity index. Experimental results show improvement, in particular the increase of sensitivity at the same specificity, in segmenting all types of tumors except for the diffused tumor. The novel brain tumor segmentation method is clinical-oriented with fast, robust and accurate implementation and a minimal user interaction. The method effectively segmented homogeneously enhanced, non-enhanced, heterogeneously-enhanced, and ring-enhanced tumor under MR imaging. Though the method is limited by identifying edema and diffuse tumor, several possible solutions are suggested to turn the curve evolution into a fully functional clinical diagnosis tool.

Fast Fourier transform-based Retinex and alpha-rooting color image enhancement

NASA Astrophysics Data System (ADS)

Grigoryan, Artyom M.; Agaian, Sos S.; Gonzales, Analysa M.

2015-05-01

Efficiency in terms of both accuracy and speed is highly important in any system, especially when it comes to image processing. The purpose of this paper is to improve an existing implementation of multi-scale retinex (MSR) by utilizing the fast Fourier transforms (FFT) within the illumination estimation step of the algorithm to improve the speed at which Gaussian blurring filters were applied to the original input image. In addition, alpha-rooting can be used as a separate technique to achieve a sharper image in order to fuse its results with those of the retinex algorithm for the sake of achieving the best image possible as shown by the values of the considered color image enhancement measure (EMEC).

Image enhancement by spectral-error correction for dual-energy computed tomography.

PubMed

Park, Kyung-Kook; Oh, Chang-Hyun; Akay, Metin

2011-01-01

Dual-energy CT (DECT) was reintroduced recently to use the additional spectral information of X-ray attenuation and aims for accurate density measurement and material differentiation. However, the spectral information lies in the difference between low and high energy images or measurements, so that it is difficult to acquire accurate spectral information due to amplification of high pixel noise in the resulting difference image. In this work, an image enhancement technique for DECT is proposed, based on the fact that the attenuation of a higher density material decreases more rapidly as X-ray energy increases. We define as spectral error the case when a pixel pair of low and high energy images deviates far from the expected attenuation trend. After analyzing the spectral-error sources of DECT images, we propose a DECT image enhancement method, which consists of three steps: water-reference offset correction, spectral-error correction, and anti-correlated noise reduction. It is the main idea of this work that makes spectral errors distributed like random noise over the true attenuation and suppressed by the well-known anti-correlated noise reduction. The proposed method suppressed noise of liver lesions and improved contrast between liver lesions and liver parenchyma in DECT contrast-enhanced abdominal images and their two-material decomposition.

New false color mapping for image fusion

NASA Astrophysics Data System (ADS)

Toet, Alexander; Walraven, Jan

1996-03-01

A pixel-based color-mapping algorithm is presented that produces a fused false color rendering of two gray-level images representing different sensor modalities. The resulting images have a higher information content than each of the original images and retain sensor-specific image information. The unique component of each image modality is enhanced in the resulting fused color image representation. First, the common component of the two original input images is determined. Second, the common component is subtracted from the original images to obtain the unique component of each image. Third, the unique component of each image modality is subtracted from the image of the other modality. This step serves to enhance the representation of sensor-specific details in the final fused result. Finally, a fused color image is produced by displaying the images resulting from the last step through, respectively, the red and green channels of a color display. The method is applied to fuse thermal and visual images. The results show that the color mapping enhances the visibility of certain details and preserves the specificity of the sensor information. The fused images also have a fairly natural appearance. The fusion scheme involves only operations on corresponding pixels. The resolution of a fused image is therefore directly related to the resolution of the input images. Before fusing, the contrast of the images can be enhanced and their noise can be reduced by standard image- processing techniques. The color mapping algorithm is computationally simple. This implies that the investigated approaches can eventually be applied in real time and that the hardware needed is not too complicated or too voluminous (an important consideration when it has to fit in an airplane, for instance).

Contrast-Enhanced Magnetic Resonance Cholangiography: Practical Tips and Clinical Indications for Biliary Disease Management.

PubMed

Palmucci, Stefano; Roccasalva, Federica; Piccoli, Marina; Fuccio Sanzà, Giovanni; Foti, Pietro Valerio; Ragozzino, Alfonso; Milone, Pietro; Ettorre, Giovanni Carlo

2017-01-01

Since its introduction, MRCP has been improved over the years due to the introduction of several technical advances and innovations. It consists of a noninvasive method for biliary tree representation, based on heavily T2-weighted images. Conventionally, its protocol includes two-dimensional single-shot fast spin-echo images, acquired with thin sections or with multiple thick slabs. In recent years, three-dimensional T2-weighted fast-recovery fast spin-echo images have been added to the conventional protocol, increasing the possibility of biliary anatomy demonstration and leading to a significant benefit over conventional 2D imaging. A significant innovation has been reached with the introduction of hepatobiliary contrasts, represented by gadoxetic acid and gadobenate dimeglumine: they are excreted into the bile canaliculi, allowing the opacification of the biliary tree. Recently, 3D interpolated T1-weighted spoiled gradient echo images have been proposed for the evaluation of the biliary tree, obtaining images after hepatobiliary contrast agent administration. Thus, the acquisition of these excretory phases improves the diagnostic capability of conventional MRCP-based on T2 acquisitions. In this paper, technical features of contrast-enhanced magnetic resonance cholangiography are briefly discussed; main diagnostic tips of hepatobiliary phase are showed, emphasizing the benefit of enhanced cholangiography in comparison with conventional MRCP.

Dangerous gas detection based on infrared video

NASA Astrophysics Data System (ADS)

Ding, Kang; Hong, Hanyu; Huang, Likun

2018-03-01

As the gas leak infrared imaging detection technology has significant advantages of high efficiency and remote imaging detection, in order to enhance the detail perception of observers and equivalently improve the detection limit, we propose a new type of gas leak infrared image detection method, which combines background difference methods and multi-frame interval difference method. Compared to the traditional frame methods, the multi-frame interval difference method we proposed can extract a more complete target image. By fusing the background difference image and the multi-frame interval difference image, we can accumulate the information of infrared target image of the gas leak in many aspect. The experiment demonstrate that the completeness of the gas leakage trace information is enhanced significantly, and the real-time detection effect can be achieved.

Contrast-enhanced endoscopic ultrasonography in digestive diseases.

PubMed

Hirooka, Yoshiki; Itoh, Akihiro; Kawashima, Hiroki; Ohno, Eizaburo; Itoh, Yuya; Nakamura, Yosuke; Hiramatsu, Takeshi; Sugimoto, Hiroyuki; Sumi, Hajime; Hayashi, Daijiro; Ohmiya, Naoki; Miyahara, Ryoji; Nakamura, Masanao; Funasaka, Kohei; Ishigami, Masatoshi; Katano, Yoshiaki; Goto, Hidemi

2012-10-01

Contrast-enhanced endoscopic ultrasonography (CE-EUS) was introduced in the early 1990s. The concept of the injection of carbon dioxide microbubbles into the hepatic artery as a contrast material (enhanced ultrasonography) led to "endoscopic ultrasonographic angiography". After the arrival of the first-generation contrast agent, high-frequency (12 MHz) EUS brought about the enhancement of EUS images in the diagnosis of pancreatico-biliary diseases, upper gastrointestinal (GI) cancer, and submucosal tumors. The electronic scanning endosonoscope with both radial and linear probes enabled the use of high-end ultrasound machines and depicted the enhancement of both color/power Doppler flow-based imaging and harmonic-based imaging using second-generation contrast agents. Many reports have described the usefulness of the differential diagnosis of pancreatic diseases and other abdominal lesions. Quantitative evaluation of CE-EUS images was an objective method of diagnosis using the time-intensity curve (TIC), but it was limited to the region of interest. Recently developed Inflow Time Mapping™ can be generated from stored clips and used to display the pattern of signal enhancement with time after injection, offering temporal difference of contrast agents and improved tumor characterization. On the other hand, three-dimensional CE-EUS images added new information to the literature, but lacked positional information. Three-dimensional CE-EUS with accurate positional information is awaited. To date, most reports have been related to pancreatic lesions or lymph nodes. Hemodynamic analysis might be of use for diseases in other organs: upper GI cancer diagnosis, submucosal tumors, and biliary disorders, and it might also provide functional information. Studies of CE-EUS in diseases in many other organs will increase in the near future.

Dynamic Contrast-Enhanced Magnetic Resonance Imaging Reveals Stress-Induced Angiogenesis in MCF7 Human Breast Tumors

NASA Astrophysics Data System (ADS)

Furman-Haran, Edna; Margalit, Raanan; Grobgeld, Dov; Degani, Hadassa

1996-06-01

The mechanism of contrast enhancement of tumors using magnetic resonance imaging was investigated in MCF7 human breast cancer implanted in nude mice. Dynamic contrast-enhanced images recorded at high spatial resolution were analyzed by an image analysis method based on a physiological model, which included the blood circulation, the tumor, the remaining tissues, and clearance via the kidneys. This analysis enabled us to map in rapidly enhancing regions within the tumor, the capillary permeability factor (capillary permeability times surface area per voxel volume) and the fraction of leakage space. Correlation of these maps with T2-weighted spin echo images, with histopathology, and with immunohistochemical staining of endothelial cells demonstrated the presence of dense permeable microcapillaries in the tumor periphery and in intratumoral regions that surrounded necrotic loci. The high leakage from the intratumoral permeable capillaries indicated an induction of a specific angiogenic process associated with stress conditions that cause necrosis. This induction was augmented in tumors responding to tamoxifen treatment. Determination of the distribution and extent of this stress-induced angiogenic activity by contrast-enhanced MRI might be of diagnostic and of prognostic value.

Study of quality perception in medical images based on comparison of contrast enhancement techniques in mammographic images

NASA Astrophysics Data System (ADS)

Matheus, B.; Verçosa, L. B.; Barufaldi, B.; Schiabel, H.

2014-03-01

With the absolute prevalence of digital images in mammography several new tools became available for radiologist; such as CAD schemes, digital zoom and contrast alteration. This work focuses in contrast variation and how the radiologist reacts to these changes when asked to evaluated image quality. Three contrast enhancing techniques were used in this study: conventional equalization, CCB Correction [1] - a digitization correction - and value subtraction. A set of 100 images was used in tests from some available online mammographic databases. The tests consisted of the presentation of all four versions of an image (original plus the three contrast enhanced images) to the specialist, requested to rank each one from the best up to worst quality for diagnosis. Analysis of results has demonstrated that CCB Correction [1] produced better images in almost all cases. Equalization, which mathematically produces a better contrast, was considered the worst for mammography image quality enhancement in the majority of cases (69.7%). The value subtraction procedure produced images considered better than the original in 84% of cases. Tests indicate that, for the radiologist's perception, it seems more important to guaranty full visualization of nuances than a high contrast image. Another result observed is that the "ideal" scanner curve does not yield the best result for a mammographic image. The important contrast range is the middle of the histogram, where nodules and masses need to be seen and clearly distinguished.

Fingerprint pattern restoration by digital image processing techniques.

PubMed

Wen, Che-Yen; Yu, Chiu-Chung

2003-09-01

Fingerprint evidence plays an important role in solving criminal problems. However, defective (lacking information needed for completeness) or contaminated (undesirable information included) fingerprint patterns make identifying and recognizing processes difficult. Unfortunately. this is the usual case. In the recognizing process (enhancement of patterns, or elimination of "false alarms" so that a fingerprint pattern can be searched in the Automated Fingerprint Identification System (AFIS)), chemical and physical techniques have been proposed to improve pattern legibility. In the identifying process, a fingerprint examiner can enhance contaminated (but not defective) fingerprint patterns under guidelines provided by the Scientific Working Group on Friction Ridge Analysis, Study and Technology (SWGFAST), the Scientific Working Group on Imaging Technology (SWGIT), and an AFIS working group within the National Institute of Justice. Recently, the image processing techniques have been successfully applied in forensic science. For example, we have applied image enhancement methods to improve the legibility of digital images such as fingerprints and vehicle plate numbers. In this paper, we propose a novel digital image restoration technique based on the AM (amplitude modulation)-FM (frequency modulation) reaction-diffusion method to restore defective or contaminated fingerprint patterns. This method shows its potential application to fingerprint pattern enhancement in the recognizing process (but not for the identifying process). Synthetic and real images are used to show the capability of the proposed method. The results of enhancing fingerprint patterns by the manual process and our method are evaluated and compared.

Visual Search with Image Modification in Age-Related Macular Degeneration

PubMed Central

Wiecek, Emily; Jackson, Mary Lou; Dakin, Steven C.; Bex, Peter

2012-01-01

Purpose. AMD results in loss of central vision and a dependence on low-resolution peripheral vision. While many image enhancement techniques have been proposed, there is a lack of quantitative comparison of the effectiveness of enhancement. We developed a natural visual search task that uses patients' eye movements as a quantitative and functional measure of the efficacy of image modification. Methods. Eye movements of 17 patients (mean age = 77 years) with AMD were recorded while they searched for target objects in natural images. Eight different image modification methods were implemented and included manipulations of local image or edge contrast, color, and crowding. In a subsequent task, patients ranked their preference of the image modifications. Results. Within individual participants, there was no significant difference in search duration or accuracy across eight different image manipulations. When data were collapsed across all image modifications, a multivariate model identified six significant predictors for normalized search duration including scotoma size and acuity, as well as interactions among scotoma size, age, acuity, and contrast (P < 0.05). Additionally, an analysis of image statistics showed no correlation with search performance across all image modifications. Rank ordering of enhancement methods based on participants' preference revealed a trend that participants preferred the least modified images (P < 0.05). Conclusions. There was no quantitative effect of image modification on search performance. A better understanding of low- and high-level components of visual search in natural scenes is necessary to improve future attempts at image enhancement for low vision patients. Different search tasks may require alternative image modifications to improve patient functioning and performance. PMID:22930725

Three-dimensional fluorescence-enhanced optical tomography using a hand-held probe based imaging system

PubMed Central

Ge, Jiajia; Zhu, Banghe; Regalado, Steven; Godavarty, Anuradha

2008-01-01

Hand-held based optical imaging systems are a recent development towards diagnostic imaging of breast cancer. To date, all the hand-held based optical imagers are used to perform only surface mapping and target localization, but are not capable of demonstrating tomographic imaging. Herein, a novel hand-held probe based optical imager is developed towards three-dimensional (3-D) optical tomography studies. The unique features of this optical imager, which primarily consists of a hand-held probe and an intensified charge coupled device detector, are its ability to; (i) image large tissue areas (5×10 sq. cm) in a single scan, (ii) perform simultaneous multiple point illumination and collection, thus reducing the overall imaging time; and (iii) adapt to varying tissue curvatures, from a flexible probe head design. Experimental studies are performed in the frequency domain on large slab phantoms (∼650 ml) using fluorescence target(s) under perfect uptake (1:0) contrast ratios, and varying target depths (1–2 cm) and X-Y locations. The effect of implementing simultaneous over sequential multiple point illumination towards 3-D tomography is experimentally demonstrated. The feasibility of 3-D optical tomography studies has been demonstrated for the first time using a hand-held based optical imager. Preliminary fluorescence-enhanced optical tomography studies are able to reconstruct 0.45 ml target(s) located at different target depths (1–2 cm). However, the depth recovery was limited as the actual target depth increased, since only reflectance measurements were acquired. Extensive tomography studies are currently carried out to determine the resolution and performance limits of the imager on flat and curved phantoms. PMID:18697559

Three-dimensional fluorescence-enhanced optical tomography using a hand-held probe based imaging system.

PubMed

Ge, Jiajia; Zhu, Banghe; Regalado, Steven; Godavarty, Anuradha

2008-07-01

Hand-held based optical imaging systems are a recent development towards diagnostic imaging of breast cancer. To date, all the hand-held based optical imagers are used to perform only surface mapping and target localization, but are not capable of demonstrating tomographic imaging. Herein, a novel hand-held probe based optical imager is developed towards three-dimensional (3-D) optical tomography studies. The unique features of this optical imager, which primarily consists of a hand-held probe and an intensified charge coupled device detector, are its ability to; (i) image large tissue areas (5 x 10 sq. cm) in a single scan, (ii) perform simultaneous multiple point illumination and collection, thus reducing the overall imaging time; and (iii) adapt to varying tissue curvatures, from a flexible probe head design. Experimental studies are performed in the frequency domain on large slab phantoms (approximately 650 ml) using fluorescence target(s) under perfect uptake (1:0) contrast ratios, and varying target depths (1-2 cm) and X-Y locations. The effect of implementing simultaneous over sequential multiple point illumination towards 3-D tomography is experimentally demonstrated. The feasibility of 3-D optical tomography studies has been demonstrated for the first time using a hand-held based optical imager. Preliminary fluorescence-enhanced optical tomography studies are able to reconstruct 0.45 ml target(s) located at different target depths (1-2 cm). However, the depth recovery was limited as the actual target depth increased, since only reflectance measurements were acquired. Extensive tomography studies are currently carried out to determine the resolution and performance limits of the imager on flat and curved phantoms.

Experimental Assessment and Enhancement of Planar Laser-Induced Fluorescence Measurements of Nitric Oxide in an Inverse Diffusion Flame

NASA Technical Reports Server (NTRS)

Partridge, William P.; Laurendeau, Normand M.

1997-01-01

We have experimentally assessed the quantitative nature of planar laser-induced fluorescence (PLIF) measurements of NO concentration in a unique atmospheric pressure, laminar, axial inverse diffusion flame (IDF). The PLIF measurements were assessed relative to a two-dimensional array of separate laser saturated fluorescence (LSF) measurements. We demonstrated and evaluated several experimentally-based procedures for enhancing the quantitative nature of PLIF concentration images. Because these experimentally-based PLIF correction schemes require only the ability to make PLIF and LSF measurements, they produce a more broadly applicable PLIF diagnostic compared to numerically-based correction schemes. We experimentally assessed the influence of interferences on both narrow-band and broad-band fluorescence measurements at atmospheric and high pressures. Optimum excitation and detection schemes were determined for the LSF and PLIF measurements. Single-input and multiple-input, experimentally-based PLIF enhancement procedures were developed for application in test environments with both negligible and significant quench-dependent error gradients. Each experimentally-based procedure provides an enhancement of approximately 50% in the quantitative nature of the PLIF measurements, and results in concentration images nominally as quantitative as LSF point measurements. These correction procedures can be applied to other species, including radicals, for which no experimental data are available from which to implement numerically-based PLIF enhancement procedures.

Quantitative characterization of edge enhancement in phase contrast x-ray imaging.

PubMed

Monnin, P; Bulling, S; Hoszowska, J; Valley, J F; Meuli, R; Verdun, F R

2004-06-01

The aim of this study was to model the edge enhancement effect in in-line holography phase contrast imaging. A simple analytical approach was used to quantify refraction and interference contrasts in terms of beam energy and imaging geometry. The model was applied to predict the peak intensity and frequency of the edge enhancement for images of cylindrical fibers. The calculations were compared with measurements, and the relationship between the spatial resolution of the detector and the amplitude of the phase contrast signal was investigated. Calculations using the analytical model were in good agreement with experimental results for nylon, aluminum and copper wires of 50 to 240 microm diameter, and with numerical simulations based on Fresnel-Kirchhoff theory. A relationship between the defocusing distance and the pixel size of the image detector was established. This analytical model is a useful tool for optimizing imaging parameters in phase contrast in-line holography, including defocusing distance, detector resolution and beam energy.

Dehazed Image Quality Assessment by Haze-Line Theory

NASA Astrophysics Data System (ADS)

Song, Yingchao; Luo, Haibo; Lu, Rongrong; Ma, Junkai

2017-06-01

Images captured in bad weather suffer from low contrast and faint color. Recently, plenty of dehazing algorithms have been proposed to enhance visibility and restore color. However, there is a lack of evaluation metrics to assess the performance of these algorithms or rate them. In this paper, an indicator of contrast enhancement is proposed basing on the newly proposed haze-line theory. The theory assumes that colors of a haze-free image are well approximated by a few hundred distinct colors, which form tight clusters in RGB space. The presence of haze makes each color cluster forms a line, which is named haze-line. By using these haze-lines, we assess performance of dehazing algorithms designed to enhance the contrast by measuring the inter-cluster deviations between different colors of dehazed image. Experimental results demonstrated that the proposed Color Contrast (CC) index correlates well with human judgments of image contrast taken in a subjective test on various scene of dehazed images and performs better than state-of-the-art metrics.

Adaptive sigmoid function bihistogram equalization for image contrast enhancement

NASA Astrophysics Data System (ADS)

Arriaga-Garcia, Edgar F.; Sanchez-Yanez, Raul E.; Ruiz-Pinales, Jose; Garcia-Hernandez, Ma. de Guadalupe

2015-09-01

Contrast enhancement plays a key role in a wide range of applications including consumer electronic applications, such as video surveillance, digital cameras, and televisions. The main goal of contrast enhancement is to increase the quality of images. However, most state-of-the-art methods induce different types of distortion such as intensity shift, wash-out, noise, intensity burn-out, and intensity saturation. In addition, in consumer electronics, simple and fast methods are required in order to be implemented in real time. A bihistogram equalization method based on adaptive sigmoid functions is proposed. It consists of splitting the image histogram into two parts that are equalized independently by using adaptive sigmoid functions. In order to preserve the mean brightness of the input image, the parameter of the sigmoid functions is chosen to minimize the absolute mean brightness metric. Experiments on the Berkeley database have shown that the proposed method improves the quality of images and preserves their mean brightness. An application to improve the colorfulness of images is also presented.

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.

Phospholipid micelle-based magneto-plasmonic nanoformulation for magnetic field-directed, imaging-guided photo-induced cancer therapy.

PubMed

Ohulchanskyy, Tymish Y; Kopwitthaya, Atcha; Jeon, Mansik; Guo, Moran; Law, Wing-Cheung; Furlani, Edward P; Kim, Chulhong; Prasad, Paras N

2013-11-01

We present a magnetoplasmonic nanoplatform combining gold nanorods (GNR) and iron-oxide nanoparticles within phospholipid-based polymeric nanomicelles (PGRFe). The gold nanorods exhibit plasmon resonance absorbance at near infrared wavelengths to enable photoacoustic imaging and photothermal therapy, while the Fe3O4 nanoparticles enable magnetophoretic control of the nanoformulation. The fabricated nanoformulation can be directed and concentrated by an external magnetic field, which provides enhancement of a photoacoustic signal. Application of an external field also leads to enhanced uptake of the magnetoplasmonic formulation by cancer cells in vitro. Under laser irradiation at the wavelength of the GNR absorption peak, the PGRFe formulation efficiently generates plasmonic nanobubbles within cancer cells, as visualized by confocal microscopy, causing cell destruction. The combined magnetic and plasmonic functionalities of the nanoplatform enable magnetic field-directed, imaging-guided, enhanced photo-induced cancer therapy. In this study, a nano-formulation of gold nanorods and iron oxide nanoparticles is presented using a phospholipid micelle-based delivery system for magnetic field-directed and imaging-guided photo-induced cancer therapy. The gold nanorods enable photoacoustic imaging and photothermal therapy, while the Fe3O4 nanoparticles enable magnetophoretic control of the formulation. This and similar systems could enable more precise and efficient cancer therapy, hopefully in the near future, after additional testing. Copyright © 2013 Elsevier Inc. All rights reserved.

Toward knowledge-enhanced viewing using encyclopedias and model-based segmentation

NASA Astrophysics Data System (ADS)

Kneser, Reinhard; Lehmann, Helko; Geller, Dieter; Qian, Yue-Chen; Weese, Jürgen

2009-02-01

To make accurate decisions based on imaging data, radiologists must associate the viewed imaging data with the corresponding anatomical structures. Furthermore, given a disease hypothesis possible image findings which verify the hypothesis must be considered and where and how they are expressed in the viewed images. If rare anatomical variants, rare pathologies, unfamiliar protocols, or ambiguous findings are present, external knowledge sources such as medical encyclopedias are consulted. These sources are accessed using keywords typically describing anatomical structures, image findings, pathologies. In this paper we present our vision of how a patient's imaging data can be automatically enhanced with anatomical knowledge as well as knowledge about image findings. On one hand, we propose the automatic annotation of the images with labels from a standard anatomical ontology. These labels are used as keywords for a medical encyclopedia such as STATdx to access anatomical descriptions, information about pathologies and image findings. On the other hand we envision encyclopedias to contain links to region- and finding-specific image processing algorithms. Then a finding is evaluated on an image by applying the respective algorithm in the associated anatomical region. Towards realization of our vision, we present our method and results of automatic annotation of anatomical structures in 3D MRI brain images. Thereby we develop a complex surface mesh model incorporating major structures of the brain and a model-based segmentation method. We demonstrate the validity by analyzing the results of several training and segmentation experiments with clinical data focusing particularly on the visual pathway.

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.

Diffusible iodine-based contrast-enhanced computed tomography (diceCT): an emerging tool for rapid, high-resolution, 3-D imaging of metazoan soft tissues.

PubMed

Gignac, Paul M; Kley, Nathan J; Clarke, Julia A; Colbert, Matthew W; Morhardt, Ashley C; Cerio, Donald; Cost, Ian N; Cox, Philip G; Daza, Juan D; Early, Catherine M; Echols, M Scott; Henkelman, R Mark; Herdina, A Nele; Holliday, Casey M; Li, Zhiheng; Mahlow, Kristin; Merchant, Samer; Müller, Johannes; Orsbon, Courtney P; Paluh, Daniel J; Thies, Monte L; Tsai, Henry P; Witmer, Lawrence M

2016-06-01

Morphologists have historically had to rely on destructive procedures to visualize the three-dimensional (3-D) anatomy of animals. More recently, however, non-destructive techniques have come to the forefront. These include X-ray computed tomography (CT), which has been used most commonly to examine the mineralized, hard-tissue anatomy of living and fossil metazoans. One relatively new and potentially transformative aspect of current CT-based research is the use of chemical agents to render visible, and differentiate between, soft-tissue structures in X-ray images. Specifically, iodine has emerged as one of the most widely used of these contrast agents among animal morphologists due to its ease of handling, cost effectiveness, and differential affinities for major types of soft tissues. The rapid adoption of iodine-based contrast agents has resulted in a proliferation of distinct specimen preparations and scanning parameter choices, as well as an increasing variety of imaging hardware and software preferences. Here we provide a critical review of the recent contributions to iodine-based, contrast-enhanced CT research to enable researchers just beginning to employ contrast enhancement to make sense of this complex new landscape of methodologies. We provide a detailed summary of recent case studies, assess factors that govern success at each step of the specimen storage, preparation, and imaging processes, and make recommendations for standardizing both techniques and reporting practices. Finally, we discuss potential cutting-edge applications of diffusible iodine-based contrast-enhanced computed tomography (diceCT) and the issues that must still be overcome to facilitate the broader adoption of diceCT going forward. © 2016 The Authors. Journal of Anatomy published by John Wiley & Sons Ltd on behalf of Anatomical Society.

Spatial and Angular Resolution Enhancement of Light Fields Using Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Gul, M. Shahzeb Khan; Gunturk, Bahadir K.

2018-05-01

Light field imaging extends the traditional photography by capturing both spatial and angular distribution of light, which enables new capabilities, including post-capture refocusing, post-capture aperture control, and depth estimation from a single shot. Micro-lens array (MLA) based light field cameras offer a cost-effective approach to capture light field. A major drawback of MLA based light field cameras is low spatial resolution, which is due to the fact that a single image sensor is shared to capture both spatial and angular information. In this paper, we present a learning based light field enhancement approach. Both spatial and angular resolution of captured light field is enhanced using convolutional neural networks. The proposed method is tested with real light field data captured with a Lytro light field camera, clearly demonstrating spatial and angular resolution improvement.

Spatial and Angular Resolution Enhancement of Light Fields Using Convolutional Neural Networks.

PubMed

Gul, M Shahzeb Khan; Gunturk, Bahadir K

2018-05-01

Light field imaging extends the traditional photography by capturing both spatial and angular distribution of light, which enables new capabilities, including post-capture refocusing, post-capture aperture control, and depth estimation from a single shot. Micro-lens array (MLA) based light field cameras offer a cost-effective approach to capture light field. A major drawback of MLA based light field cameras is low spatial resolution, which is due to the fact that a single image sensor is shared to capture both spatial and angular information. In this paper, we present a learning based light field enhancement approach. Both spatial and angular resolution of captured light field is enhanced using convolutional neural networks. The proposed method is tested with real light field data captured with a Lytro light field camera, clearly demonstrating spatial and angular resolution improvement.

Brain vascular image segmentation based on fuzzy local information C-means clustering

NASA Astrophysics Data System (ADS)

Hu, Chaoen; Liu, Xia; Liang, Xiao; Hui, Hui; Yang, Xin; Tian, Jie

2017-02-01

Light sheet fluorescence microscopy (LSFM) is a powerful optical resolution fluorescence microscopy technique which enables to observe the mouse brain vascular network in cellular resolution. However, micro-vessel structures are intensity inhomogeneity in LSFM images, which make an inconvenience for extracting line structures. In this work, we developed a vascular image segmentation method by enhancing vessel details which should be useful for estimating statistics like micro-vessel density. Since the eigenvalues of hessian matrix and its sign describes different geometric structure in images, which enable to construct vascular similarity function and enhance line signals, the main idea of our method is to cluster the pixel values of the enhanced image. Our method contained three steps: 1) calculate the multiscale gradients and the differences between eigenvalues of Hessian matrix. 2) In order to generate the enhanced microvessels structures, a feed forward neural network was trained by 2.26 million pixels for dealing with the correlations between multi-scale gradients and the differences between eigenvalues. 3) The fuzzy local information c-means clustering (FLICM) was used to cluster the pixel values in enhance line signals. To verify the feasibility and effectiveness of this method, mouse brain vascular images have been acquired by a commercial light-sheet microscope in our lab. The experiment of the segmentation method showed that dice similarity coefficient can reach up to 85%. The results illustrated that our approach extracting line structures of blood vessels dramatically improves the vascular image and enable to accurately extract blood vessels in LSFM images.

A promising limited angular computed tomography reconstruction via segmentation based regional enhancement and total variation minimization

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

Zhang, Wenkun; Zhang, Hanming; Li, Lei

2016-08-15

X-ray computed tomography (CT) is a powerful and common inspection technique used for the industrial non-destructive testing. However, large-sized and heavily absorbing objects cause the formation of artifacts because of either the lack of specimen penetration in specific directions or the acquisition of data from only a limited angular range of views. Although the sparse optimization-based methods, such as the total variation (TV) minimization method, can suppress artifacts to some extent, reconstructing the images such that they converge to accurate values remains difficult because of the deficiency in continuous angular data and inconsistency in the projections. To address this problem,more » we use the idea of regional enhancement of the true values and suppression of the illusory artifacts outside the region to develop an efficient iterative algorithm. This algorithm is based on the combination of regional enhancement of the true values and TV minimization for the limited angular reconstruction. In this algorithm, the segmentation approach is introduced to distinguish the regions of different image knowledge and generate the support mask of the image. A new regularization term, which contains the support knowledge to enhance the true values of the image, is incorporated into the objective function. Then, the proposed optimization model is solved by variable splitting and the alternating direction method efficiently. A compensation approach is also designed to extract useful information from the initial projections and thus reduce false segmentation result and correct the segmentation support and the segmented image. The results obtained from comparing both simulation studies and real CT data set reconstructions indicate that the proposed algorithm generates a more accurate image than do the other reconstruction methods. The experimental results show that this algorithm can produce high-quality reconstructed images for the limited angular reconstruction and suppress the illusory artifacts caused by the deficiency in valid data.« less

A promising limited angular computed tomography reconstruction via segmentation based regional enhancement and total variation minimization

NASA Astrophysics Data System (ADS)

Zhang, Wenkun; Zhang, Hanming; Li, Lei; Wang, Linyuan; Cai, Ailong; Li, Zhongguo; Yan, Bin

2016-08-01

X-ray computed tomography (CT) is a powerful and common inspection technique used for the industrial non-destructive testing. However, large-sized and heavily absorbing objects cause the formation of artifacts because of either the lack of specimen penetration in specific directions or the acquisition of data from only a limited angular range of views. Although the sparse optimization-based methods, such as the total variation (TV) minimization method, can suppress artifacts to some extent, reconstructing the images such that they converge to accurate values remains difficult because of the deficiency in continuous angular data and inconsistency in the projections. To address this problem, we use the idea of regional enhancement of the true values and suppression of the illusory artifacts outside the region to develop an efficient iterative algorithm. This algorithm is based on the combination of regional enhancement of the true values and TV minimization for the limited angular reconstruction. In this algorithm, the segmentation approach is introduced to distinguish the regions of different image knowledge and generate the support mask of the image. A new regularization term, which contains the support knowledge to enhance the true values of the image, is incorporated into the objective function. Then, the proposed optimization model is solved by variable splitting and the alternating direction method efficiently. A compensation approach is also designed to extract useful information from the initial projections and thus reduce false segmentation result and correct the segmentation support and the segmented image. The results obtained from comparing both simulation studies and real CT data set reconstructions indicate that the proposed algorithm generates a more accurate image than do the other reconstruction methods. The experimental results show that this algorithm can produce high-quality reconstructed images for the limited angular reconstruction and suppress the illusory artifacts caused by the deficiency in valid data.

Nonlinear Fusion of Multispectral Citrus Fruit Image Data with Information Contents.

PubMed

Li, Peilin; Lee, Sang-Heon; Hsu, Hung-Yao; Park, Jae-Sam

2017-01-13

The main issue of vison-based automatic harvesting manipulators is the difficulty in the correct fruit identification in the images under natural lighting conditions. Mostly, the solution has been based on a linear combination of color components in the multispectral images. However, the results have not reached a satisfactory level. To overcome this issue, this paper proposes a robust nonlinear fusion method to augment the original color image with the synchronized near infrared image. The two images are fused with Daubechies wavelet transform (DWT) in a multiscale decomposition approach. With DWT, the background noises are reduced and the necessary image features are enhanced by fusing the color contrast of the color components and the homogeneity of the near infrared (NIR) component. The resulting fused color image is classified with a C-means algorithm for reconstruction. The performance of the proposed approach is evaluated with the statistical F measure in comparison to some existing methods using linear combinations of color components. The results show that the fusion of information in different spectral components has the advantage of enhancing the image quality, therefore improving the classification accuracy in citrus fruit identification in natural lighting conditions.

Nonlinear Fusion of Multispectral Citrus Fruit Image Data with Information Contents

PubMed Central

Li, Peilin; Lee, Sang-Heon; Hsu, Hung-Yao; Park, Jae-Sam

2017-01-01

The main issue of vison-based automatic harvesting manipulators is the difficulty in the correct fruit identification in the images under natural lighting conditions. Mostly, the solution has been based on a linear combination of color components in the multispectral images. However, the results have not reached a satisfactory level. To overcome this issue, this paper proposes a robust nonlinear fusion method to augment the original color image with the synchronized near infrared image. The two images are fused with Daubechies wavelet transform (DWT) in a multiscale decomposition approach. With DWT, the background noises are reduced and the necessary image features are enhanced by fusing the color contrast of the color components and the homogeneity of the near infrared (NIR) component. The resulting fused color image is classified with a C-means algorithm for reconstruction. The performance of the proposed approach is evaluated with the statistical F measure in comparison to some existing methods using linear combinations of color components. The results show that the fusion of information in different spectral components has the advantage of enhancing the image quality, therefore improving the classification accuracy in citrus fruit identification in natural lighting conditions. PMID:28098797

Medulloblastoma with Atypical Dynamic Imaging Changes: Case Report with Literature Review.

PubMed

Song, Shuang-Shuang; Wang, Jian-Hong; Fu, Wei-Wei; Li, Ying; Sui, Qing-Lan; Liu, Xue-Jun

2017-09-01

We analyzed a case of medulloblastoma with atypical dynamic imaging changes retrospectively to summarize the atypical magnetic resonance imaging (MRI) features of medulloblastoma by reviewing the literature. An atypical case of medulloblastoma in the cerebellar hemisphere confirmed by pathology was analyzed retrospectively, and the literature about it was reviewed. The radiologic findings of the patient were based on 3 examinations. The first examination showed that the cortex of the bilateral cerebellar hemisphere had diffuse nodular thickening, with a high signal on diffusion-weighted imaging and significant enhancement. Contrast enhancement MRI 1 year later showed the signal of cerebellar hemisphere returned to normal but revealed an enhanced nodule. A reexamination 6 months later showed an irregular mass with a high-density shadow in the cerebellar vermis on CT scan. The T2-weighted image revealed multiple degenerative cysts, and the mass had significant enhancement. The radiologic characteristics of atypical medulloblastomas vary in adults and children. Understanding the radiologic characteristics of medulloblastomas, such as MRI features, age of onset, and location of atypical medulloblastomas, can help improve the diagnosis of medulloblastomas. Copyright © 2017. Published by Elsevier Inc.

Visible continuum pulses based on enhanced dispersive wave generation for endogenous fluorescence imaging.

PubMed

Cui, Quan; Chen, Zhongyun; Liu, Qian; Zhang, Zhihong; Luo, Qingming; Fu, Ling

2017-09-01

In this study, we demonstrate endogenous fluorescence imaging using visible continuum pulses based on 100-fs Ti:sapphire oscillator and a nonlinear photonic crystal fiber. Broadband (500-700 nm) and high-power (150 mW) continuum pulses are generated through enhanced dispersive wave generation by pumping femtosecond pulses at the anomalous dispersion region near zero-dispersion wavelength of high-nonlinear photonic crystal fibers. We also minimize the continuum pulse width by determining the proper fiber length. The visible-wavelength two-photon microscopy produces NADH and tryptophan images of mice tissues simultaneously. Our 500-700 nm continuum pulses support extending nonlinear microscopy to visible wavelength range that is inaccessible to 100-fs Ti:sapphire oscillators and other applications requiring visible laser pulses.

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

Giant solitary fibrous tumor of the diaphragm: a case report and review of literature

PubMed Central

Ge, Wei; Yu, De-Cai; Jiang, Chun-Ping; Ding, Yi-Tao

2014-01-01

A young gentleman presented with difficulty in breathing. Computed tomography (CT) scan showed a huge mass located between the heart and stomach, which might have rooted in the diaphragm. Magnetic resonance imaging (MRI) with enhanced three dimensional construction showed a lobulated, heterogeneous soft tissue mass with short T1 weighted imaging signal and flake long T2-weighted imaging (T2WI). Tumor-enhanced scanning demonstrated heterogeneous contrast enhancement. The preliminary diagnosis was intra-abdominal huge mass and considering sarcoma. Resection was conducted where the base of the tumor was located in the diaphragm oppressing the left liver lobe and heart. The base of the tumor, together with partial surrounding of the diaphragm, pericardium base, and the left lateral hepatic segment, was resected. The defect in the diaphragm and pericardium was repaired by patching, and thoracic close drainage and abdominal drainage were placed following the surgical operation. The pathological report showed giant solitary fibrous tumor (SFT). This case report may provide a reference resource for the diagnosis and treatment of SFT located in the diaphragm. PMID:25674285

Enhanced facial recognition for thermal imagery using polarimetric imaging.

PubMed

Gurton, Kristan P; Yuffa, Alex J; Videen, Gorden W

2014-07-01

We present a series of long-wave-infrared (LWIR) polarimetric-based thermal images of facial profiles in which polarization-state information of the image-forming radiance is retained and displayed. The resultant polarimetric images show enhanced facial features, additional texture, and details that are not present in corresponding conventional thermal imagery. It has been generally thought that conventional thermal imagery (MidIR or LWIR) could not produce the detailed spatial information required for reliable human identification due to the so-called "ghosting" effect often seen in thermal imagery of human subjects. By using polarimetric information, we are able to extract subtle surface features of the human face, thus improving subject identification. Polarimetric image sets considered include the conventional thermal intensity image, S0, the two Stokes images, S1 and S2, and a Stokes image product called the degree-of-linear-polarization image.

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.

Medical image enhancement using resolution synthesis

NASA Astrophysics Data System (ADS)

Wong, Tak-Shing; Bouman, Charles A.; Thibault, Jean-Baptiste; Sauer, Ken D.

2011-03-01

We introduce a post-processing approach to improve the quality of CT reconstructed images. The scheme is adapted from the resolution-synthesis (RS)1 interpolation algorithm. In this approach, we consider the input image, scanned at a particular dose level, as a degraded version of a high quality image scanned at a high dose level. Image enhancement is achieved by predicting the high quality image by classification based linear regression. To improve the robustness of our scheme, we also apply the minimum description length principle to determine the optimal number of predictors to use in the scheme, and the ridge regression to regularize the design of the predictors. Experimental results show that our scheme is effective in reducing the noise in images reconstructed from filtered back projection without significant loss of image details. Alternatively, our scheme can also be applied to reduce dose while maintaining image quality at an acceptable level.

Image quality enhancement in low-light-level ghost imaging using modified compressive sensing method

NASA Astrophysics Data System (ADS)

Shi, Xiaohui; Huang, Xianwei; Nan, Suqin; Li, Hengxing; Bai, Yanfeng; Fu, Xiquan

2018-04-01

Detector noise has a significantly negative impact on ghost imaging at low light levels, especially for existing recovery algorithm. Based on the characteristics of the additive detector noise, a method named modified compressive sensing ghost imaging is proposed to reduce the background imposed by the randomly distributed detector noise at signal path. Experimental results show that, with an appropriate choice of threshold value, modified compressive sensing ghost imaging algorithm can dramatically enhance the contrast-to-noise ratio of the object reconstruction significantly compared with traditional ghost imaging and compressive sensing ghost imaging methods. The relationship between the contrast-to-noise ratio of the reconstruction image and the intensity ratio (namely, the average signal intensity to average noise intensity ratio) for the three reconstruction algorithms are also discussed. This noise suppression imaging technique will have great applications in remote-sensing and security areas.

Enhancing SDO/HMI images using deep learning

NASA Astrophysics Data System (ADS)

Baso, C. J. Díaz; Ramos, A. Asensio

2018-06-01

Context. The Helioseismic and Magnetic Imager (HMI) provides continuum images and magnetograms with a cadence better than one per minute. It has been continuously observing the Sun 24 h a day for the past 7 yr. The trade-off between full disk observations and spatial resolution means that HMI is not adequate for analyzing the smallest-scale events in the solar atmosphere. Aims: Our aim is to develop a new method to enhance HMI data, simultaneously deconvolving and super-resolving images and magnetograms. The resulting images will mimic observations with a diffraction-limited telescope twice the diameter of HMI. Methods: Our method, which we call Enhance, is based on two deep, fully convolutional neural networks that input patches of HMI observations and output deconvolved and super-resolved data. The neural networks are trained on synthetic data obtained from simulations of the emergence of solar active regions. Results: We have obtained deconvolved and super-resolved HMI images. To solve this ill-defined problem with infinite solutions we have used a neural network approach to add prior information from the simulations. We test Enhance against Hinode data that has been degraded to a 28 cm diameter telescope showing very good consistency. The code is open source.

Image enhancement by spatial frequency post-processing of images obtained with pupil filters

NASA Astrophysics Data System (ADS)

Estévez, Irene; Escalera, Juan C.; Stefano, Quimey Pears; Iemmi, Claudio; Ledesma, Silvia; Yzuel, María J.; Campos, Juan

2016-12-01

The use of apodizing or superresolving filters improves the performance of an optical system in different frequency bands. This improvement can be seen as an increase in the OTF value compared to the OTF for the clear aperture. In this paper we propose a method to enhance the contrast of an image in both its low and its high frequencies. The method is based on the generation of a synthetic Optical Transfer Function, by multiplexing the OTFs given by the use of different non-uniform transmission filters on the pupil. We propose to capture three images, one obtained with a clear pupil, one obtained with an apodizing filter that enhances the low frequencies and another one taken with a superresolving filter that improves the high frequencies. In the Fourier domain the three spectra are combined by using smoothed passband filters, and then the inverse transform is performed. We show that we can create an enhanced image better than the image obtained with the clear aperture. To evaluate the performance of the method, bar tests (sinusoidal tests) with different frequency content are used. The results show that a contrast improvement in the high and low frequencies is obtained.

Configuration-controlled Au nanocluster arrays on inverse micelle nano-patterns: versatile platforms for SERS and SPR sensors

NASA Astrophysics Data System (ADS)

Jang, Yoon Hee; Chung, Kyungwha; Quan, Li Na; Špačková, Barbora; Šípová, Hana; Moon, Seyoung; Cho, Won Joon; Shin, Hae-Young; Jang, Yu Jin; Lee, Ji-Eun; Kochuveedu, Saji Thomas; Yoon, Min Ji; Kim, Jihyeon; Yoon, Seokhyun; Kim, Jin Kon; Kim, Donghyun; Homola, Jiří; Kim, Dong Ha

2013-11-01

Nanopatterned 2-dimensional Au nanocluster arrays with controlled configuration are fabricated onto reconstructed nanoporous poly(styrene-block-vinylpyridine) inverse micelle monolayer films. Near-field coupling of localized surface plasmons is studied and compared for disordered and ordered core-centered Au NC arrays. Differences in evolution of the absorption band and field enhancement upon Au nanoparticle adsorption are shown. The experimental results are found to be in good agreement with theoretical studies based on the finite-difference time-domain method and rigorous coupled-wave analysis. The realized Au nanopatterns are exploited as substrates for surface-enhanced Raman scattering and integrated into Kretschmann-type SPR sensors, based on which unprecedented SPR-coupling-type sensors are demonstrated.Nanopatterned 2-dimensional Au nanocluster arrays with controlled configuration are fabricated onto reconstructed nanoporous poly(styrene-block-vinylpyridine) inverse micelle monolayer films. Near-field coupling of localized surface plasmons is studied and compared for disordered and ordered core-centered Au NC arrays. Differences in evolution of the absorption band and field enhancement upon Au nanoparticle adsorption are shown. The experimental results are found to be in good agreement with theoretical studies based on the finite-difference time-domain method and rigorous coupled-wave analysis. The realized Au nanopatterns are exploited as substrates for surface-enhanced Raman scattering and integrated into Kretschmann-type SPR sensors, based on which unprecedented SPR-coupling-type sensors are demonstrated. Electronic supplementary information (ESI) available: TEM image and UV-vis absorption spectrum of citrate-capped Au NPs, AFM images of Au NC arrays on the PS-b-P4VP (41k-24k) template, ImageJ-analyzed results of PS-b-P4VP (41k-24k)-templated Au NC arrays, calculated %-surface coverage values, SEM images of Au NC arrays on the PS-b-P2VP (172k-42k) template for SPR biosensing, corresponding ImageJ-analyzed images by varying the Au NP deposition time and results of image analysis. See DOI: 10.1039/c3nr03860b

A parameterized logarithmic image processing method with Laplacian of Gaussian filtering for lung nodule enhancement in chest radiographs.

PubMed

Chen, Sheng; Yao, Liping; Chen, Bao

2016-11-01

The enhancement of lung nodules in chest radiographs (CXRs) plays an important role in the manual as well as computer-aided detection (CADe) lung cancer. In this paper, we proposed a parameterized logarithmic image processing (PLIP) method combined with the Laplacian of a Gaussian (LoG) filter to enhance lung nodules in CXRs. We first applied several LoG filters with varying parameters to an original CXR to enhance the nodule-like structures as well as the edges in the image. We then applied the PLIP model, which can enhance lung nodule images with high contrast and was beneficial in extracting effective features for nodule detection in the CADe scheme. Our method combined the advantages of both the PLIP algorithm and the LoG algorithm, which can enhance lung nodules in chest radiographs with high contrast. To test our nodule enhancement method, we tested a CADe scheme, with a relatively high performance in nodule detection, using a publically available database containing 140 nodules in 140 CXRs enhanced through our nodule enhancement method. The CADe scheme attained a sensitivity of 81 and 70 % with an average of 5.0 frame rate (FP) and 2.0 FP, respectively, in a leave-one-out cross-validation test. By contrast, the CADe scheme based on the original image recorded a sensitivity of 77 and 63 % at 5.0 FP and 2.0 FP, respectively. We introduced the measurement of enhancement by entropy evaluation to objectively assess our method. Experimental results show that the proposed method obtains an effective enhancement of lung nodules in CXRs for both radiologists and CADe schemes.

Vascular applications of contrast-enhanced ultrasound imaging.

PubMed

Mehta, Kunal S; Lee, Jake J; Taha, Ashraf G; Avgerinos, Efthymios; Chaer, Rabih A

2017-07-01

Contrast-enhanced ultrasound (CEUS) imaging is a powerful noninvasive modality offering numerous potential diagnostic and therapeutic applications in vascular medicine. CEUS imaging uses microbubble contrast agents composed of an encapsulating shell surrounding a gaseous core. These microbubbles act as nearly perfect intravascular reflectors of ultrasound energy and may be used to enhance the overall contrast and quality of ultrasound images. The purpose of this narrative review is to survey the current literature regarding CEUS imaging and discuss its diagnostic and therapeutic roles in current vascular and selected nonvascular applications. The PubMed, MEDLINE, and Embase databases were searched until July 2016 using the PubMed and Ovid Web-based search engines. The search terms used included contrast-enhanced, microbubble, ultrasound, carotid, aneurysm, and arterial. The diagnostic and therapeutic utility of CEUS imaging has grown exponentially, particularly in the realms of extracranial carotid arterial disease, aortic disease, and peripheral arterial disease. Studies have demonstrated that CEUS imaging is diagnostically superior to conventional ultrasound imaging in identifying vessel irregularities and measuring neovascularization to assess plaque vulnerability and end-muscle perfusion. Groups have begun to use microbubbles as agents in therapeutic applications for targeted drug and gene therapy delivery as well as for the enhancement of sonothrombolysis. The emerging technology of microbubbles and CEUS imaging holds considerable promise for cardiovascular medicine and cancer therapy given its diagnostic and therapeutic utility. Overall, with proper training and credentialing of technicians, the clinical implications are innumerable as microbubble technology is rapidly bursting onto the scene of cardiovascular medicine. Copyright © 2017 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

Sum of top-hat transform based algorithm for vessel enhancement in MRA images

NASA Astrophysics Data System (ADS)

Ouazaa, Hibet-Allah; Jlassi, Hajer; Hamrouni, Kamel

2018-04-01

The Magnetic Resonance Angiography (MRA) is rich with information's. But, they suffer from poor contrast, illumination and noise. Thus, it is required to enhance the images. But, these significant information can be lost if improper techniques are applied. Therefore, in this paper, we propose a new method of enhancement. We applied firstly the CLAHE method to increase the contrast of the image. Then, we applied the sum of Top-Hat Transform to increase the brightness of vessels. It is performed with the structuring element oriented in different angles. The methodology is tested and evaluated on the publicly available database BRAINIX. And, we used the measurement methods MSE (Mean Square Error), PSNR (Peak Signal to Noise Ratio) and SNR (Signal to Noise Ratio) for the evaluation. The results demonstrate that the proposed method could efficiently enhance the image details and is comparable with state of the art algorithms. Hence, the proposed method could be broadly used in various applications.

Enhancing in vivo tumor boundary delineation with structured illumination fluorescence molecular imaging and spatial gradient mapping

NASA Astrophysics Data System (ADS)

Sun, Jessica; Miller, Jessica P.; Hathi, Deep; Zhou, Haiying; Achilefu, Samuel; Shokeen, Monica; Akers, Walter J.

2016-08-01

Fluorescence imaging, in combination with tumor-avid near-infrared (NIR) fluorescent molecular probes, provides high specificity and sensitivity for cancer detection in preclinical animal models, and more recently, assistance during oncologic surgery. However, conventional camera-based fluorescence imaging techniques are heavily surface-weighted such that surface reflection from skin or other nontumor tissue and nonspecific fluorescence signals dominate, obscuring true cancer-specific signals and blurring tumor boundaries. To address this challenge, we applied structured illumination fluorescence molecular imaging (SIFMI) in live animals for automated subtraction of nonspecific surface signals to better delineate accumulation of an NIR fluorescent probe targeting α4β1 integrin in mice bearing subcutaneous plasma cell xenografts. SIFMI demonstrated a fivefold improvement in tumor-to-background contrast when compared with other full-field fluorescence imaging methods and required significantly reduced scanning time compared with diffuse optical spectroscopy imaging. Furthermore, the spatial gradient mapping enhanced highlighting of tumor boundaries. Through the relatively simple hardware and software modifications described, SIFMI can be integrated with clinical fluorescence imaging systems, enhancing intraoperative tumor boundary delineation from the uninvolved tissue.

Dynamic Contrast-Enhanced MRI in the Evaluation of Carotid Space Paraganglioma versus Schwannoma.

PubMed

Gaddikeri, Santhosh; Hippe, Daniel S; Anzai, Yoshimi

2016-11-01

To describe the potential role of dynamic contrast-enhanced (DCE) MRI in differentiating carotid space (CS) paraganglioma from schwannoma in the head and neck. We retrospectively reviewed records of 126 patients who had undergone DCE-MRI between June 2008 and July 2014 and found six patients with histologically verified benign CS tumors. The images were evaluated for tumor T1 and T2 signal characteristics, flow voids, and enhancement pattern. The dynamic data were analyzed for quantitative parameters using extended Toft's model (K trans , K ep , V e , and V p ) and semiquantitative parameters based on time-intensity curve (area under curve, peak enhancement, wash-in, wash-out, signal-enhancement ratio [SER], and time for maximum enhancement [TME]). Due to the small sample size, groups were compared qualitatively. Patients with CS paraganglioma (P group, n = 2) and schwannoma (S group, n = 4) were included. All tumors were hypointense on T1W imaging, hyperintense on T2W imaging, and show avid enhancement. One patient with paraganglioma had subtle flow voids. The conventional MR images were insufficient to confidently diagnose tumor type. Both paragangliomas had high peak enhancement and SER, and a short TME, while the schwannomas had relatively low peak enhancement and SER with a longer TME. K trans , K ep , and V e were relatively low in the paragangliomas than in the schwannomas. DCE-MRI could potentially be used to assist differentiating paraganglioma from schwannoma, when diagnosis is difficult on the conventional MR imaging sequences. Simple assessment of semiquantitative parameters suffices to provide supportive information. Copyright © 2016 by the American Society of Neuroimaging.

Intratumor partitioning and texture analysis of dynamic contrast-enhanced (DCE)-MRI identifies relevant tumor subregions to predict pathological response of breast cancer to neoadjuvant chemotherapy.

PubMed

Wu, Jia; Gong, Guanghua; Cui, Yi; Li, Ruijiang

2016-11-01

To predict pathological response of breast cancer to neoadjuvant chemotherapy (NAC) based on quantitative, multiregion analysis of dynamic contrast enhancement magnetic resonance imaging (DCE-MRI). In this Institutional Review Board-approved study, 35 patients diagnosed with stage II/III breast cancer were retrospectively investigated using 3T DCE-MR images acquired before and after the first cycle of NAC. First, principal component analysis (PCA) was used to reduce the dimensionality of the DCE-MRI data with high temporal resolution. We then partitioned the whole tumor into multiple subregions using k-means clustering based on the PCA-defined eigenmaps. Within each tumor subregion, we extracted four quantitative Haralick texture features based on the gray-level co-occurrence matrix (GLCM). The change in texture features in each tumor subregion between pre- and during-NAC was used to predict pathological complete response after NAC. Three tumor subregions were identified through clustering, each with distinct enhancement characteristics. In univariate analysis, all imaging predictors except one extracted from the tumor subregion associated with fast washout were statistically significant (P < 0.05) after correcting for multiple testing, with area under the receiver operating characteristic (ROC) curve (AUC) or AUCs between 0.75 and 0.80. In multivariate analysis, the proposed imaging predictors achieved an AUC of 0.79 (P = 0.002) in leave-one-out cross-validation. This improved upon conventional imaging predictors such as tumor volume (AUC = 0.53) and texture features based on whole-tumor analysis (AUC = 0.65). The heterogeneity of the tumor subregion associated with fast washout on DCE-MRI predicted pathological response to NAC in breast cancer. J. Magn. Reson. Imaging 2016;44:1107-1115. © 2016 International Society for Magnetic Resonance in Medicine.

Do we need gadolinium-based contrast medium for brain magnetic resonance imaging in children?

PubMed

Dünger, Dennis; Krause, Matthias; Gräfe, Daniel; Merkenschlager, Andreas; Roth, Christian; Sorge, Ina

2018-06-01

Brain imaging is the most common examination in pediatric magnetic resonance imaging (MRI), often combined with the use of a gadolinium-based contrast medium. The application of gadolinium-based contrast medium poses some risk. There is limited evidence of the benefits of contrast medium in pediatric brain imaging. To assess the diagnostic gain of contrast-enhanced sequences in brain MRI when the unenhanced sequences are normal. We retrospectively assessed 6,683 brain MR examinations using contrast medium in children younger than 16 years in the pediatric radiology department of the University Hospital Leipzig to determine whether contrast-enhanced sequences delivered additional, clinically relevant information to pre-contrast sequences. All examinations were executed using a 1.5-T or a 3-T system. In 8 of 3,003 (95% confidence interval 0.12-0.52%) unenhanced normal brain examinations, a relevant additional finding was detected when contrast medium was administered. Contrast enhancement led to a change in diagnosis in only one of these cases. Children with a normal pre-contrast brain MRI rarely benefit from contrast medium application. Comparing these results to the risks and disadvantages of a routine gadolinium application, there is substantiated numerical evidence for avoiding routine administration of gadolinium in a pre-contrast normal MRI examination.

Multi-slice ultrasound image calibration of an intelligent skin-marker for soft tissue artefact compensation.

PubMed

Masum, M A; Pickering, M R; Lambert, A J; Scarvell, J M; Smith, P N

2017-09-06

In this paper, a novel multi-slice ultrasound (US) image calibration of an intelligent skin-marker used for soft tissue artefact compensation is proposed to align and orient image slices in an exact H-shaped pattern. Multi-slice calibration is complex, however, in the proposed method, a phantom based visual alignment followed by transform parameters estimation greatly reduces the complexity and provides sufficient accuracy. In this approach, the Hough Transform (HT) is used to further enhance the image features which originate from the image feature enhancing elements integrated into the physical phantom model, thus reducing feature detection uncertainty. In this framework, slice by slice image alignment and calibration are carried out and this provides manual ease and convenience. Copyright © 2016 Elsevier Ltd. All rights reserved.

More IMPATIENT: A Gridding-Accelerated Toeplitz-based Strategy for Non-Cartesian High-Resolution 3D MRI on GPUs

PubMed Central

Gai, Jiading; Obeid, Nady; Holtrop, Joseph L.; Wu, Xiao-Long; Lam, Fan; Fu, Maojing; Haldar, Justin P.; Hwu, Wen-mei W.; Liang, Zhi-Pei; Sutton, Bradley P.

2013-01-01

Several recent methods have been proposed to obtain significant speed-ups in MRI image reconstruction by leveraging the computational power of GPUs. Previously, we implemented a GPU-based image reconstruction technique called the Illinois Massively Parallel Acquisition Toolkit for Image reconstruction with ENhanced Throughput in MRI (IMPATIENT MRI) for reconstructing data collected along arbitrary 3D trajectories. In this paper, we improve IMPATIENT by removing computational bottlenecks by using a gridding approach to accelerate the computation of various data structures needed by the previous routine. Further, we enhance the routine with capabilities for off-resonance correction and multi-sensor parallel imaging reconstruction. Through implementation of optimized gridding into our iterative reconstruction scheme, speed-ups of more than a factor of 200 are provided in the improved GPU implementation compared to the previous accelerated GPU code. PMID:23682203

PSMA-Targeted Nano-Conjugates as Dual-Modality (MRI/PET) Imaging Probes for the Non-Invasive Detection of Prostate Cancer

DTIC Science & Technology

2009-10-01

be made. Currently, iodine based compounds are used to enhance contrast of CT which have the limitations of short imaging window due to rapid...number compared to conventionally used iodine compounds . Nanoparticle based CT contrast agents have been demonstrated for vascular imaging, which...constructs with gamma or positron emitting isotopes through a covalent attachment of a bifunctional chelator to the nanoparticles surface. However, in

Visual wetness perception based on image color statistics.

PubMed

Sawayama, Masataka; Adelson, Edward H; Nishida, Shin'ya

2017-05-01

Color vision provides humans and animals with the abilities to discriminate colors based on the wavelength composition of light and to determine the location and identity of objects of interest in cluttered scenes (e.g., ripe fruit among foliage). However, we argue that color vision can inform us about much more than color alone. Since a trichromatic image carries more information about the optical properties of a scene than a monochromatic image does, color can help us recognize complex material qualities. Here we show that human vision uses color statistics of an image for the perception of an ecologically important surface condition (i.e., wetness). Psychophysical experiments showed that overall enhancement of chromatic saturation, combined with a luminance tone change that increases the darkness and glossiness of the image, tended to make dry scenes look wetter. Theoretical analysis along with image analysis of real objects indicated that our image transformation, which we call the wetness enhancing transformation, is consistent with actual optical changes produced by surface wetting. Furthermore, we found that the wetness enhancing transformation operator was more effective for the images with many colors (large hue entropy) than for those with few colors (small hue entropy). The hue entropy may be used to separate surface wetness from other surface states having similar optical properties. While surface wetness and surface color might seem to be independent, there are higher order color statistics that can influence wetness judgments, in accord with the ecological statistics. The present findings indicate that the visual system uses color image statistics in an elegant way to help estimate the complex physical status of a scene.

Energy weighted x-ray dark-field imaging.

PubMed

Pelzer, Georg; Zang, Andrea; Anton, Gisela; Bayer, Florian; Horn, Florian; Kraus, Manuel; Rieger, Jens; Ritter, Andre; Wandner, Johannes; Weber, Thomas; Fauler, Alex; Fiederle, Michael; Wong, Winnie S; Campbell, Michael; Meiser, Jan; Meyer, Pascal; Mohr, Jürgen; Michel, Thilo

2014-10-06

The dark-field image obtained in grating-based x-ray phase-contrast imaging can provide information about the objects' microstructures on a scale smaller than the pixel size even with low geometric magnification. In this publication we demonstrate that the dark-field image quality can be enhanced with an energy-resolving pixel detector. Energy-resolved x-ray dark-field images were acquired with a 16-energy-channel photon-counting pixel detector with a 1 mm thick CdTe sensor in a Talbot-Lau x-ray interferometer. A method for contrast-noise-ratio (CNR) enhancement is proposed and validated experimentally. In measurements, a CNR improvement by a factor of 1.14 was obtained. This is equivalent to a possible radiation dose reduction of 23%.

Imaging-related medications: a class overview

PubMed Central

2007-01-01

Imaging-related medications (contrast agents) are commonly utilized to improve visualization of radiographic, computed tomography (CT), and magnetic resonance (MR) images. While traditional medications are used specifically for their pharmacological actions, the ideal imaging agent provides enhanced contrast with little biological interaction. The radiopaque agents, barium sulfate and iodinated contrast agents, confer “contrast” to x-ray films by their physical ability to directly absorb x-rays. Gadolinium-based MR agents enhance visualization of tissues when exposed to a magnetic field. Ferrous-ferric oxide–based paramagnetic agents provide negative contrast for MR liver studies. This article provides an overview of clinically relevant information for the imaging-related medications commonly in use. It reviews the safety improvements in new generations of drugs; risk factors and precautions for the reduction of severe adverse reactions (i.e., extravasation, contrast-induced nephropathy, metformin-induced lactic acidosis, and nephrogenic fibrosing dermopathy/nephrogenic systemic fibrosis); and the significance of diligent patient screening before contrast exposure and appropriate monitoring after exposure. PMID:17948119

Multispectral image enhancement for H&E stained pathological tissue specimens

NASA Astrophysics Data System (ADS)

Bautista, Pinky A.; Abe, Tokiya; Yamaguchi, Masahiro; Ohyama, Nagaaki; Yagi, Yukako

2008-03-01

The presence of a liver disease such as cirrhosis can be determined by examining the proliferation of collagen fiber from a tissue slide stained with special stain such as the Masson's trichrome(MT) stain. Collagen fiber and smooth muscle, which are both stained the same in an H&E stained slide, are stained blue and pink respectively in an MT-stained slide. In this paper we show that with multispectral imaging the difference between collagen fiber and smooth muscle can be visualized even from an H&E stained image. In the method M KL bases are derived using the spectral data of those H&E stained tissue components which can be easily differentiated from each other, i.e. nucleus, cytoplasm, red blood cells, etc. and based on the spectral residual error of fiber weighting factors are determined to enhance spectral features at certain wavelengths. Results of our experiment demonstrate the capability of multispectral imaging and its advantage compared to the conventional RGB imaging systems to delineate tissue structures with subtle colorimetric difference.

Signal-to-noise ratio enhancement on SEM images using a cubic spline interpolation with Savitzky-Golay filters and weighted least squares error.

PubMed

Kiani, M A; Sim, K S; Nia, M E; Tso, C P

2015-05-01

A new technique based on cubic spline interpolation with Savitzky-Golay smoothing using weighted least squares error filter is enhanced for scanning electron microscope (SEM) images. A diversity of sample images is captured and the performance is found to be better when compared with the moving average and the standard median filters, with respect to eliminating noise. This technique can be implemented efficiently on real-time SEM images, with all mandatory data for processing obtained from a single image. Noise in images, and particularly in SEM images, are undesirable. A new noise reduction technique, based on cubic spline interpolation with Savitzky-Golay and weighted least squares error method, is developed. We apply the combined technique to single image signal-to-noise ratio estimation and noise reduction for SEM imaging system. This autocorrelation-based technique requires image details to be correlated over a few pixels, whereas the noise is assumed to be uncorrelated from pixel to pixel. The noise component is derived from the difference between the image autocorrelation at zero offset, and the estimation of the corresponding original autocorrelation. In the few test cases involving different images, the efficiency of the developed noise reduction filter is proved to be significantly better than those obtained from the other methods. Noise can be reduced efficiently with appropriate choice of scan rate from real-time SEM images, without generating corruption or increasing scanning time. © 2015 The Authors Journal of Microscopy © 2015 Royal Microscopical Society.

Enhancement of the visibility of objects located below the surface of a scattering medium

DOEpatents

Demos, Stavros

2013-11-19

Techniques are provided for enhancing the visibility of objects located below the surface of a scattering medium such as tissue, water and smoke. Examples of such an object include a vein located below the skin, a mine located below the surface of the sea and a human in a location covered by smoke. The enhancement of the image contrast of a subsurface structure is based on the utilization of structured illumination. In the specific application of this invention to image the veins in the arm or other part of the body, the issue of how to control the intensity of the image of a metal object (such as a needle) that must be inserted into the vein is also addressed.

Single-energy non-contrast hepatic steatosis criteria applied to virtual non-contrast images: is it still highly specific and positively predictive?

PubMed

Haji-Momenian, S; Parkinson, W; Khati, N; Brindle, K; Earls, J; Zeman, R K

2018-06-01

To determine the sensitivity, specificity, and predictive values of single-energy non-contrast hepatic steatosis criteria on dual-energy virtual non-contrast (VNC) images. Forty-eight computed tomography (CT) examinations, which included single-energy non-contrast (TNC) and contrast-enhanced dual-energy CT angiography (CTA) of the abdomen, were enrolled. VNC images were reconstructed from the CTA. Region of interest (ROI) attenuations were measured in the right and left hepatic lobes, spleen, and aorta on TNC and VNC images. The right and left hepatic lobes were treated as separate samples. Steatosis was diagnosed based on TNC liver attenuation of ≤40 HU or liver attenuation index (LAI) of ≤-10 HU, which are extremely specific and predictive for moderate to severe steatosis. The sensitivity, specificity, and predictive values of VNC images for steatosis were calculated. VNC-TNC deviations were correlated with aortic enhancement and patient water equivalent diameter (PWED). Thirty-two liver ROIs met steatosis criteria based on TNC attenuation; VNC attenuation had sensitivity, specificity, and a positive predictive value of 66.7%, 100%, and 100%, respectively. Twenty-one liver ROIs met steatosis criteria based on TNC LAI. VNC LAI had sensitivity, specificity, and positive predictive values of 61.9%, 90.7%, and 65%, respectively. Hepatic and splenic VNC-TNC deviations did not correlate with one another (R 2 =0.08), aortic enhancement (R 2 <0.06) or PWED (R 2 <0.09). Non-contrast hepatic attenuation criteria is extremely specific and positively predictive for moderate to severe steatosis on VNC reconstructions from the arterial phase. Hepatic attenuation performs better than LAI criteria. VNC deviations are independent of aortic enhancement and PWED. Copyright © 2018 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Enhanced spectral domain optical coherence tomography for pathological and functional studies

NASA Astrophysics Data System (ADS)

Yuan, Zhijia

Optical coherence tomography (OCT) is a novel technique that enables noninvasive or minimally invasive, cross-sectional imaging of biological tissue at sub-10mum spatial resolution and up to 2-3mm imaging depth. Numerous technological advances have emerged in recent years that have shown great potential to develop OCT into a powerful imaging and diagnostic tools. In particular, the implementation of Fourier-domain OCT (FDOCT) is a major step forward that leads to greatly improved imaging rate and image fidelity of OCT. This dissertation summarizes the work that focuses on enhancing the performances and functionalities of spectral radar based FDOCT (SDOCT) for pathological and functional applications. More specifically, chapters 1-4 emphasize on the development of SDOCT and its utility in pathological studies, including cancer diagnosis. The principle of SDOCT is first briefly outlined, followed by the design of our bench-top SDOCT systems with emphasis on spectral linear interpolation, calibration and system dispersion compensation. For ultrahigh-resolution SDOCT, time-lapse image registration and frame averaging is introduced to effectively reduce speckle noise and uncover subcellular details, showing great promise for enhancing the diagnosis of carcinoma in situ. To overcome the image depth limitation of OCT, a dual-modal imaging method combing SDOCT with high-frequency ultrasound is proposed and examined in animal cancer models to enhance the sensitivity and staging capabilities for bladder cancer diagnosis. Chapters 5-7 summarize the work on developing Doppler SDOCT for functional studies. Digital-frequency-ramping OCT (DFR-OCT) is developed in the study, which has demonstrated the ability to significantly improve the signal-to-noise ratio and thus sensitivity for retrieving subsurface blood flow imaging. New DFR algorithms and imaging processing methods are discussed to further enhance cortical CBF imaging. Applications of DFR-OCT for brain functional studies are presented and laser speckle imaging is combined to enable quantitative cerebral blood flow (CBF) imaging at high spatiotemporal resolutions. An angiography-enhanced Doppler optical coherence tomography (aDFR-OCT) was also demonstrated to enable quantitative imaging of capillary changes for brain functional studies. Lastly, future work on technological development and potential biomedical applications is briefly outlined.

Deep learning enables reduced gadolinium dose for contrast-enhanced brain MRI.

PubMed

Gong, Enhao; Pauly, John M; Wintermark, Max; Zaharchuk, Greg

2018-02-13

There are concerns over gadolinium deposition from gadolinium-based contrast agents (GBCA) administration. To reduce gadolinium dose in contrast-enhanced brain MRI using a deep learning method. Retrospective, crossover. Sixty patients receiving clinically indicated contrast-enhanced brain MRI. 3D T 1 -weighted inversion-recovery prepped fast-spoiled-gradient-echo (IR-FSPGR) imaging was acquired at both 1.5T and 3T. In 60 brain MRI exams, the IR-FSPGR sequence was obtained under three conditions: precontrast, postcontrast images with 10% low-dose (0.01mmol/kg) and 100% full-dose (0.1 mmol/kg) of gadobenate dimeglumine. We trained a deep learning model using the first 10 cases (with mixed indications) to approximate full-dose images from the precontrast and low-dose images. Synthesized full-dose images were created using the trained model in two test sets: 20 patients with mixed indications and 30 patients with glioma. For both test sets, low-dose, true full-dose, and the synthesized full-dose postcontrast image sets were compared quantitatively using peak-signal-to-noise-ratios (PSNR) and structural-similarity-index (SSIM). For the test set comprised of 20 patients with mixed indications, two neuroradiologists scored blindly and independently for the three postcontrast image sets, evaluating image quality, motion-artifact suppression, and contrast enhancement compared with precontrast images. Results were assessed using paired t-tests and noninferiority tests. The proposed deep learning method yielded significant (n = 50, P < 0.001) improvements over the low-dose images (>5 dB PSNR gains and >11.0% SSIM). Ratings on image quality (n = 20, P = 0.003) and contrast enhancement (n = 20, P < 0.001) were significantly increased. Compared to true full-dose images, the synthesized full-dose images have a slight but not significant reduction in image quality (n = 20, P = 0.083) and contrast enhancement (n = 20, P = 0.068). Slightly better (n = 20, P = 0.039) motion-artifact suppression was noted in the synthesized images. The noninferiority test rejects the inferiority of the synthesized to true full-dose images for image quality (95% CI: -14-9%), artifacts suppression (95% CI: -5-20%), and contrast enhancement (95% CI: -13-6%). With the proposed deep learning method, gadolinium dose can be reduced 10-fold while preserving contrast information and avoiding significant image quality degradation. 3 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2018. © 2018 International Society for Magnetic Resonance in Medicine.

Degraded document image enhancement

NASA Astrophysics Data System (ADS)

Agam, G.; Bal, G.; Frieder, G.; Frieder, O.

2007-01-01

Poor quality documents are obtained in various situations such as historical document collections, legal archives, security investigations, and documents found in clandestine locations. Such documents are often scanned for automated analysis, further processing, and archiving. Due to the nature of such documents, degraded document images are often hard to read, have low contrast, and are corrupted by various artifacts. We describe a novel approach for the enhancement of such documents based on probabilistic models which increases the contrast, and thus, readability of such documents under various degradations. The enhancement produced by the proposed approach can be viewed under different viewing conditions if desired. The proposed approach was evaluated qualitatively and compared to standard enhancement techniques on a subset of historical documents obtained from the Yad Vashem Holocaust museum. In addition, quantitative performance was evaluated based on synthetically generated data corrupted under various degradation models. Preliminary results demonstrate the effectiveness of the proposed approach.

A novel technique of contrast-enhanced optical coherence tomography imaging in evaluation of clearance of lipids in human tears.

PubMed

Napoli, Pietro Emanuele; Coronella, Franco; Satta, Giovanni Maria; Fossarello, Maurizio

2014-01-01

The aim of this work was to gather preliminary data in different conditions of healthy eyes, aqueous tear deficient dry eyes, obstructive meibomian gland disease (MGD) and non-obvious obstructive MGD (NOMGD) individuals, using a new, contrast-enhanced optical coherence tomography (OCT) imaging method to evaluate the clearance of lipids in human tears. Eighty-two adult patients presenting with complaints of ocular irritation were studied for abnormalities of the ocular surface and classified as healthy (n = 21), aqueous tear deficient dry eyes (n = 20), obstructive MGD (n = 15) and NOMGD (n = 26) individuals. A lipid-based tracer, containing an oil-in-water emulsion, was used to obtain an enhanced OCT imaging of the lower tear meniscus. After instillation, a dramatic initial increase of reflectivity of the lower tear meniscus was detected by OCT, followed by a decay back to baseline values over time. Based on this finding, the clearance of lipids was measured in real-time by Fourier-domain anterior segment OCT. The differences in the clearance of lipids among the four groups as well as the correlations between symptom questionnaire score, standardized visual scale test, fluorescein break-up time, ocular surface fluorescein staining score, Schirmer I test scores were found to be statistically significant. The individual areas under the curve of the clearance of lipids calculated by the receiver operating characteristic curve technique ranged from 0.66 to 0.98, suggesting reliable sensitivity and specificity of lipid-enhanced OCT imaging. This new technique of contrast-enhanced OCT imaging of the tear film following lipid-based tracer instillation provides a measure of the clearance of lipids. The quantitative values found are in agreement with other methods of evaluation of the lacrimal system. An improvement of the clinician's ability in the diagnosis and understanding of abnormalities of the ocular surface may be achieved by this simple approach.

Enhance the Quality of Crowdsensing for Fine-Grained Urban Environment Monitoring via Data Correlation

PubMed Central

Kang, Xu; Liu, Liang; Ma, Huadong

2017-01-01

Monitoring the status of urban environments, which provides fundamental information for a city, yields crucial insights into various fields of urban research. Recently, with the popularity of smartphones and vehicles equipped with onboard sensors, a people-centric scheme, namely “crowdsensing”, for city-scale environment monitoring is emerging. This paper proposes a data correlation based crowdsensing approach for fine-grained urban environment monitoring. To demonstrate urban status, we generate sensing images via crowdsensing network, and then enhance the quality of sensing images via data correlation. Specifically, to achieve a higher quality of sensing images, we not only utilize temporal correlation of mobile sensing nodes but also fuse the sensory data with correlated environment data by introducing a collective tensor decomposition approach. Finally, we conduct a series of numerical simulations and a real dataset based case study. The results validate that our approach outperforms the traditional spatial interpolation-based method. PMID:28054968

Reconstructing White Walls: Multi-View Multi-Shot 3d Reconstruction of Textureless Surfaces

NASA Astrophysics Data System (ADS)

Ley, Andreas; Hänsch, Ronny; Hellwich, Olaf

2016-06-01

The reconstruction of the 3D geometry of a scene based on image sequences has been a very active field of research for decades. Nevertheless, there are still existing challenges in particular for homogeneous parts of objects. This paper proposes a solution to enhance the 3D reconstruction of weakly-textured surfaces by using standard cameras as well as a standard multi-view stereo pipeline. The underlying idea of the proposed method is based on improving the signal-to-noise ratio in weakly-textured regions while adaptively amplifying the local contrast to make better use of the limited numerical range in 8-bit images. Based on this premise, multiple shots per viewpoint are used to suppress statistically uncorrelated noise and enhance low-contrast texture. By only changing the image acquisition and adding a preprocessing step, a tremendous increase of up to 300% in completeness of the 3D reconstruction is achieved.

Breast tissue classification in digital tomosynthesis images based on global gradient minimization and texture features

NASA Astrophysics Data System (ADS)

Qin, Xulei; Lu, Guolan; Sechopoulos, Ioannis; Fei, Baowei

2014-03-01

Digital breast tomosynthesis (DBT) is a pseudo-three-dimensional x-ray imaging modality proposed to decrease the effect of tissue superposition present in mammography, potentially resulting in an increase in clinical performance for the detection and diagnosis of breast cancer. Tissue classification in DBT images can be useful in risk assessment, computer-aided detection and radiation dosimetry, among other aspects. However, classifying breast tissue in DBT is a challenging problem because DBT images include complicated structures, image noise, and out-of-plane artifacts due to limited angular tomographic sampling. In this project, we propose an automatic method to classify fatty and glandular tissue in DBT images. First, the DBT images are pre-processed to enhance the tissue structures and to decrease image noise and artifacts. Second, a global smooth filter based on L0 gradient minimization is applied to eliminate detailed structures and enhance large-scale ones. Third, the similar structure regions are extracted and labeled by fuzzy C-means (FCM) classification. At the same time, the texture features are also calculated. Finally, each region is classified into different tissue types based on both intensity and texture features. The proposed method is validated using five patient DBT images using manual segmentation as the gold standard. The Dice scores and the confusion matrix are utilized to evaluate the classified results. The evaluation results demonstrated the feasibility of the proposed method for classifying breast glandular and fat tissue on DBT images.

Segmentation of knee MRI using structure enhanced local phase filtering

NASA Astrophysics Data System (ADS)

Lim, Mikhiel; Hacihaliloglu, Ilker

2016-03-01

The segmentation of bone surfaces from magnetic resonance imaging (MRI) data has applications in the quanti- tative measurement of knee osteoarthritis, surgery planning for patient specific total knee arthroplasty and its subsequent fabrication of artificial implants. However, due to the problems associated with MRI imaging such as low contrast between bone and surrounding tissues, noise, bias fields, and the partial volume effect, segmentation of bone surfaces continues to be a challenging operation. In this paper, a new framework is presented for the enhancement of knee MRI scans prior to segmentation in order to obtain high contrast bone images. During the first stage, a new contrast enhanced relative total variation (RTV) regularization method is used in order to remove textural noise from the bone structures and surrounding soft tissue interface. This salient bone edge information is further enhanced using a sparse gradient counting method based on L0 gradient minimization, which globally controls how many non-zero gradients are resulted in order to approximate prominent bone structures in a structure-sparsity-management manner. The last stage of the framework involves incorporation of local phase bone boundary information in order to provide an intensity invariant enhancement of contrast between the bone and surrounding soft tissue. The enhanced images are segmented using a fast random walker algorithm. Validation against expert segmentation was performed on 10 clinical knee MRI images, and achieved a mean dice similarity coefficient (DSC) of 0.975.

Rotation Covariant Image Processing for Biomedical Applications

PubMed Central

Reisert, Marco

2013-01-01

With the advent of novel biomedical 3D image acquisition techniques, the efficient and reliable analysis of volumetric images has become more and more important. The amount of data is enormous and demands an automated processing. The applications are manifold, ranging from image enhancement, image reconstruction, and image description to object/feature detection and high-level contextual feature extraction. In most scenarios, it is expected that geometric transformations alter the output in a mathematically well-defined manner. In this paper we emphasis on 3D translations and rotations. Many algorithms rely on intensity or low-order tensorial-like descriptions to fulfill this demand. This paper proposes a general mathematical framework based on mathematical concepts and theories transferred from mathematical physics and harmonic analysis into the domain of image analysis and pattern recognition. Based on two basic operations, spherical tensor differentiation and spherical tensor multiplication, we show how to design a variety of 3D image processing methods in an efficient way. The framework has already been applied to several biomedical applications ranging from feature and object detection tasks to image enhancement and image restoration techniques. In this paper, the proposed methods are applied on a variety of different 3D data modalities stemming from medical and biological sciences. PMID:23710255

Image dehazing based on non-local saturation

NASA Astrophysics Data System (ADS)

Wang, Linlin; Zhang, Qian; Yang, Deyun; Hou, Yingkun; He, Xiaoting

2018-04-01

In this paper, a method based on non-local saturation algorithm is proposed to avoid block and halo effect for single image dehazing with dark channel prior. First we convert original image from RGB color space into HSV color space with the idea of non-local method. Image saturation is weighted equally by the size of fixed window according to image resolution. Second we utilize the saturation to estimate the atmospheric light value and transmission rate. Then through the function of saturation and transmission, the haze-free image is obtained based on the atmospheric scattering model. Comparing the results of existing methods, our method can restore image color and enhance contrast. We guarantee the proposed method with quantitative and qualitative evaluation respectively. Experiments show the better visual effect with high efficiency.

MEMS-based system and image processing strategy for epiretinal prosthesis.

PubMed

Xia, Peng; Hu, Jie; Qi, Jin; Gu, Chaochen; Peng, Yinghong

2015-01-01

Retinal prostheses have the potential to restore some level of visual function to the patients suffering from retinal degeneration. In this paper, an epiretinal approach with active stimulation devices is presented. The MEMS-based processing system consists of an external micro-camera, an information processor, an implanted electrical stimulator and a microelectrode array. The image processing strategy combining image clustering and enhancement techniques was proposed and evaluated by psychophysical experiments. The results indicated that the image processing strategy improved the visual performance compared with direct merging pixels to low resolution. The image processing methods assist epiretinal prosthesis for vision restoration.

Stokes vector based interpolation method to improve the efficiency of bio-inspired polarization-difference imaging in turbid media

NASA Astrophysics Data System (ADS)

Guan, Jinge; Ren, Wei; Cheng, Yaoyu

2018-04-01

We demonstrate an efficient polarization-difference imaging system in turbid conditions by using the Stokes vector of light. The interaction of scattered light with the polarizer is analyzed by the Stokes-Mueller formalism. An interpolation method is proposed to replace the mechanical rotation of the polarization axis of the analyzer theoretically, and its performance is verified by the experiment at different turbidity levels. We show that compared with direct imaging, the Stokes vector based imaging method can effectively reduce the effect of light scattering and enhance the image contrast.

MO-FG-CAMPUS-IeP1-02: Dose Reduction in Contrast-Enhanced Digital Mammography Using a Photon-Counting Detector

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

Lee, S; Kang, S; Eom, J

Purpose: Photon-counting detectors (PCDs) allow multi-energy X-ray imaging without additional exposures and spectral overlap. This capability results in the improvement of accuracy of material decomposition for dual-energy X-ray imaging and the reduction of radiation dose. In this study, the PCD-based contrast-enhanced dual-energy mammography (CEDM) was compared with the conventional CDEM in terms of radiation dose, image quality and accuracy of material decomposition. Methods: A dual-energy model was designed by using Beer-Lambert’s law and rational inverse fitting function for decomposing materials from a polychromatic X-ray source. A cadmium zinc telluride (CZT)-based PCD, which has five energy thresholds, and iodine solutions includedmore » in a 3D half-cylindrical phantom, which composed of 50% glandular and 50% adipose tissues, were simulated by using a Monte Carlo simulation tool. The low- and high-energy images were obtained in accordance with the clinical exposure conditions for the conventional CDEM. Energy bins of 20–33 and 34–50 keV were defined from X-ray energy spectra simulated at 50 kVp with different dose levels for implementing the PCD-based CDEM. The dual-energy mammographic techniques were compared by means of absorbed dose, noise property and normalized root-mean-square error (NRMSE). Results: Comparing to the conventional CEDM, the iodine solutions were clearly decomposed for the PCD-based CEDM. Although the radiation dose for the PCD-based CDEM was lower than that for the conventional CEDM, the PCD-based CDEM improved the noise property and accuracy of decomposition images. Conclusion: This study demonstrates that the PCD-based CDEM allows the quantitative material decomposition, and reduces radiation dose in comparison with the conventional CDEM. Therefore, the PCD-based CDEM is able to provide useful information for detecting breast tumor and enhancing diagnostic accuracy in mammography.« less

[Future perspectives for diagnostic imaging in urology: from anatomic and functional to molecular imaging].

PubMed

Macis, Giuseppe; Di Giovanni, Silvia; Di Franco, Davide; Bonomo, Lorenzo

2013-01-01

The future approach of diagnostic imaging in urology follows the technological progress, which made the visualization of in vivo molecular processes possible. From anatomo-morphological diagnostic imaging and through functional imaging molecular radiology is reached. Based on molecular probes, imaging is aimed at assessing the in vivo molecular processes, their physiology and function at cellular level. The future imaging will investigate the complex tumor functioning as metabolism, aerobic glycolysis in particular, angiogenesis, cell proliferation, metastatic potential, hypoxia, apoptosis and receptors expressed by neoplastic cells. Methods for performing molecular radiology are CT, MRI, PET-CT, PET-MRI, SPECT and optical imaging. Molecular ultrasound combines technological advancement with targeted contrast media based on microbubbles, this allowing the selective registration of microbubble signal while that of stationary tissues is suppressed. An experimental study was carried out where the ultrasound molecular probe BR55 strictly bound to prostate tumor results in strong enhancement in the early phase after contrast, this contrast being maintained in the late phase. This late enhancement is markedly significant for the detection of prostatic cancer foci and to guide the biopsy sampling. The 124I-cG250 molecular antibody which is strictly linked to cellular carbonic anhydrase IX of clear cell renal carcinoma, allows the acquisition of diagnostic PET images of clear cell renal carcinoma without biopsy. This WG-250 (RENCAREX) antibody was used as a therapy in metastatic clear cell renal carcinoma. Future advancements and applications will result in early cancer diagnosis, personalized therapy that will be specific according to the molecular features of cancer and leading to the development of catheter-based multichannel molecular imaging devices for cystoscopy-based molecular imaging diagnosis and intervention.

Information granules in image histogram analysis.

PubMed

Wieclawek, Wojciech

2018-04-01

A concept of granular computing employed in intensity-based image enhancement is discussed. First, a weighted granular computing idea is introduced. Then, the implementation of this term in the image processing area is presented. Finally, multidimensional granular histogram analysis is introduced. The proposed approach is dedicated to digital images, especially to medical images acquired by Computed Tomography (CT). As the histogram equalization approach, this method is based on image histogram analysis. Yet, unlike the histogram equalization technique, it works on a selected range of the pixel intensity and is controlled by two parameters. Performance is tested on anonymous clinical CT series. Copyright © 2017 Elsevier Ltd. All rights reserved.

Laser applications and system considerations in ocular imaging

PubMed Central

Elsner, Ann E.; Muller, Matthew S.

2009-01-01

We review laser applications for primarily in vivo ocular imaging techniques, describing their constraints based on biological tissue properties, safety, and the performance of the imaging system. We discuss the need for cost effective sources with practical wavelength tuning capabilities for spectral studies. Techniques to probe the pathological changes of layers beneath the highly scattering retina and diagnose the onset of various eye diseases are described. The recent development of several optical coherence tomography based systems for functional ocular imaging is reviewed, as well as linear and nonlinear ocular imaging techniques performed with ultrafast lasers, emphasizing recent source developments and methods to enhance imaging contrast. PMID:21052482

Gap-mode enhancement on MoS2 probed by functionalized tip-enhanced Raman spectroscopy

NASA Astrophysics Data System (ADS)

Alajlan, Abdulrahman M.; Voronine, Dmitri V.; Sinyukov, Alexander M.; Zhang, Zhenrong; Sokolov, Alexei V.; Scully, Marlan O.

2016-09-01

Surface enhancement of molecular spectroscopic signals has been widely used for sensing and nanoscale imaging. Because of the weak electromagnetic enhancement of Raman signals on semiconductors, it is motivating but challenging to study the electromagnetic effect separately from the chemical effects. We report tip-enhanced Raman scattering measurements on Au and bulk MoS2 substrates using a metallic tip functionalized with copper phthalocyanine molecules and demonstrate similar gap-mode enhancement on both substrates. We compare the experimental results with theoretical calculations to confirm the gap-mode enhancement on MoS2 using a well-established electrostatic model. The functionalized tip approach allows for suppressing the background and is ideal for separating electromagnetic and chemical enhancement mechanisms on various substrates. Our results may find a wide range of applications in MoS2-based devices, sensors, and metal-free nanoscale bio-imaging.

Development of a multispectral structured-illumination reflectance imaging (SIRI) system and its application to bruise detection of apples

USDA-ARS?s Scientific Manuscript database

Structured-illumination reflectance imaging (SIRI) is a new, promising imaging modality for enhancing quality detection of food. A liquid-crystal tunable filter (LCTF)-based multispectral SIRI system was developed and used for selecting optimal wavebands to detect bruising in apples. Immediately aft...

Nanoscale imaging with table-top coherent extreme ultraviolet source based on high harmonic generation

NASA Astrophysics Data System (ADS)

Ba Dinh, Khuong; Le, Hoang Vu; Hannaford, Peter; Van Dao, Lap

2017-08-01

A table-top coherent diffractive imaging experiment on a sample with biological-like characteristics using a focused narrow-bandwidth high harmonic source around 30 nm is performed. An approach involving a beam stop and a new reconstruction algorithm to enhance the quality of reconstructed the image is described.

Shadow detection and removal in RGB VHR images for land use unsupervised classification

NASA Astrophysics Data System (ADS)

Movia, A.; Beinat, A.; Crosilla, F.

2016-09-01

Nowadays, high resolution aerial images are widely available thanks to the diffusion of advanced technologies such as UAVs (Unmanned Aerial Vehicles) and new satellite missions. Although these developments offer new opportunities for accurate land use analysis and change detection, cloud and terrain shadows actually limit benefits and possibilities of modern sensors. Focusing on the problem of shadow detection and removal in VHR color images, the paper proposes new solutions and analyses how they can enhance common unsupervised classification procedures for identifying land use classes related to the CO2 absorption. To this aim, an improved fully automatic procedure has been developed for detecting image shadows using exclusively RGB color information, and avoiding user interaction. Results show a significant accuracy enhancement with respect to similar methods using RGB based indexes. Furthermore, novel solutions derived from Procrustes analysis have been applied to remove shadows and restore brightness in the images. In particular, two methods implementing the so called "anisotropic Procrustes" and the "not-centered oblique Procrustes" algorithms have been developed and compared with the linear correlation correction method based on the Cholesky decomposition. To assess how shadow removal can enhance unsupervised classifications, results obtained with classical methods such as k-means, maximum likelihood, and self-organizing maps, have been compared to each other and with a supervised clustering procedure.

Interferometric detection of nanoparticles

NASA Astrophysics Data System (ADS)

Hayrapetyan, Karen

Interferometric surfaces enhance light scattering from nanoparticles through constructive interference of partial scattered waves. By placing the nanoparticles on interferometric surfaces tuned to a special surface phase interferometric condition, the particles are detectable in the dilute limit through interferometric image contrast in a heterodyne light scattering configuration, or through diffraction in a homodyne scattering configuration. The interferometric enhancement has applications for imaging and diffractive biosensors. We present a modified model based on Double Interaction (DI) to explore bead-based detection mechanisms using imaging, scanning and diffraction. The application goal of this work is to explore the trade-offs between the sensitivity and throughput among various detection methods. Experimentally we use thermal oxide on silicon to establish and control surface interferometric conditions. Surface-captured gold beads are detected using Molecular Interferometric Imaging (MI2) and Spinning-Disc Interferometry (SDI). Double-resonant enhancement of light scattering leads to high-contrast detection of 100 nm radius gold nanoparticles on an interferometric surface. The double-resonance condition is achieved when resonance (or anti-resonance) from an asymmetric Fabry-Perot substrate coincides with the Mie resonance of the gold nanoparticle. The double-resonance condition is observed experimentally using molecular interferometric imaging (MI2). An invisibility condition is identified for which the gold nanoparticles are optically cloaked by the interferometric surface.

Self-recovery fragile watermarking algorithm based on SPHIT

NASA Astrophysics Data System (ADS)

Xin, Li Ping

2015-12-01

A fragile watermark algorithm is proposed, based on SPIHT coding, which can recover the primary image itself. The novelty of the algorithm is that it can tamper location and Self-restoration. The recovery has been very good effect. The first, utilizing the zero-tree structure, the algorithm compresses and encodes the image itself, and then gained self correlative watermark data, so as to greatly reduce the quantity of embedding watermark. Then the watermark data is encoded by error correcting code, and the check bits and watermark bits are scrambled and embedded to enhance the recovery ability. At the same time, by embedding watermark into the latter two bit place of gray level image's bit-plane code, the image after embedded watermark can gain nicer visual effect. The experiment results show that the proposed algorithm may not only detect various processing such as noise adding, cropping, and filtering, but also recover tampered image and realize blind-detection. Peak signal-to-noise ratios of the watermark image were higher than other similar algorithm. The attack capability of the algorithm was enhanced.

Enhanced resolution imaging of ultrathin ZnO layers on Ag(111) by multiple hydrogen molecules in a scanning tunneling microscope junction

NASA Astrophysics Data System (ADS)

Liu, Shuyi; Shiotari, Akitoshi; Baugh, Delroy; Wolf, Martin; Kumagai, Takashi

2018-05-01

Molecular hydrogen in a scanning tunneling microscope (STM) junction has been found to enhance the lateral spatial resolution of the STM imaging, referred to as scanning tunneling hydrogen microscopy (STHM). Here we report atomic resolution imaging of 2- and 3-monolayer (ML) thick ZnO layers epitaxially grown on Ag(111) using STHM. The enhanced resolution can be obtained at a relatively large tip to surface distance and resolves a more defective structure exhibiting dislocation defects for 3-ML-thick ZnO than for 2 ML. In order to elucidate the enhanced imaging mechanism, the electric and mechanical properties of the hydrogen molecular junction (HMJ) are investigated by a combination of STM and atomic force microscopy. It is found that the HMJ shows multiple kinklike features in the tip to surface distance dependence of the conductance and frequency shift curves, which are absent in a hydrogen-free junction. Based on a simple modeling, we propose that the junction contains several hydrogen molecules and sequential squeezing of the molecules out of the junction results in the kinklike features in the conductance and frequency shift curves. The model also qualitatively reproduces the enhanced resolution image of the ZnO films.

Investigation of image enhancement techniques for the development of a self-contained airborne radar navigation system

NASA Technical Reports Server (NTRS)

Phatak, A. V.; Karmali, M. S.

1983-01-01

This study was devoted to an investigation of the feasibility of applying advanced image processing techniques to enhance radar image characteristics that are pertinent to the pilot's navigation and guidance task. Millimeter (95 GHz) wave radar images for the overwater (i.e., offshore oil rigs) and overland (Heliport) scenario were used as a data base. The purpose of the study was to determine the applicability of image enhancement and scene analysis algorithms to detect and improve target characteristics (i.e., manmade objects such as buildings, parking lots, cars, roads, helicopters, towers, landing pads, etc.) that would be helpful to the pilot in determining his own position/orientation with respect to the outside world and assist him in the navigation task. Results of this study show that significant improvements in the raw radar image may be obtained using two dimensional image processing algorithms. In the overwater case, it is possible to remove the ocean clutter by thresholding the image data, and furthermore to extract the target boundary as well as the tower and catwalk locations using noise cleaning (e.g., median filter) and edge detection (e.g., Sobel operator) algorithms.

Temporal subtraction contrast-enhanced dedicated breast CT

PubMed Central

Gazi, Peymon M.; Aminololama-Shakeri, Shadi; Yang, Kai; Boone, John M.

2016-01-01

Purpose To develop a framework of deformable image registration and segmentation for the purpose of temporal subtraction contrast-enhanced breast CT is described. Methods An iterative histogram-based two-means clustering method was used for the segmentation. Dedicated breast CT images were segmented into background (air), adipose, fibroglandular and skin components. Fibroglandular tissue was classified as either normal or contrast-enhanced then divided into tiers for the purpose of categorizing degrees of contrast enhancement. A variant of the Demons deformable registration algorithm, Intensity Difference Adaptive Demons (IDAD), was developed to correct for the large deformation forces that stemmed from contrast enhancement. In this application, the accuracy of the proposed method was evaluated in both mathematically-simulated and physically-acquired phantom images. Clinical usage and accuracy of the temporal subtraction framework was demonstrated using contrast-enhanced breast CT datasets from five patients. Registration performance was quantified using Normalized Cross Correlation (NCC), Symmetric Uncertainty Coefficient (SUC), Normalized Mutual Information (NMI), Mean Square Error (MSE) and Target Registration Error (TRE). Results The proposed method outperformed conventional affine and other Demons variations in contrast enhanced breast CT image registration. In simulation studies, IDAD exhibited improvement in MSE(0–16%), NCC (0–6%), NMI (0–13%) and TRE (0–34%) compared to the conventional Demons approaches, depending on the size and intensity of the enhancing lesion. As lesion size and contrast enhancement levels increased, so did the improvement. The drop in the correlation between the pre- and post-contrast images for the largest enhancement levels in phantom studies is less than 1.2% (150 Hounsfield units). Registration error, measured by TRE, shows only submillimeter mismatches between the concordant anatomical target points in all patient studies. The algorithm was implemented using a parallel processing architecture resulting in rapid execution time for the iterative segmentation and intensity-adaptive registration techniques. Conclusion Characterization of contrast-enhanced lesions is improved using temporal subtraction contrast-enhanced dedicated breast CT. Adaptation of Demons registration forces as a function of contrast-enhancement levels provided a means to accurately align breast tissue in pre- and post-contrast image acquisitions, improving subtraction results. Spatial subtraction of the aligned images yields useful diagnostic information with respect to enhanced lesion morphology and uptake. PMID:27494376

Example-based super-resolution for single-image analysis from the Chang'e-1 Mission

NASA Astrophysics Data System (ADS)

Wu, Fan-Lu; Wang, Xiang-Jun

2016-11-01

Due to the low spatial resolution of images taken from the Chang'e-1 (CE-1) orbiter, the details of the lunar surface are blurred and lost. Considering the limited spatial resolution of image data obtained by a CCD camera on CE-1, an example-based super-resolution (SR) algorithm is employed to obtain high-resolution (HR) images. SR reconstruction is important for the application of image data to increase the resolution of images. In this article, a novel example-based algorithm is proposed to implement SR reconstruction by single-image analysis, and the computational cost is reduced compared to other example-based SR methods. The results show that this method can enhance the resolution of images using SR and recover detailed information about the lunar surface. Thus it can be used for surveying HR terrain and geological features. Moreover, the algorithm is significant for the HR processing of remotely sensed images obtained by other imaging systems.

Application of the EM algorithm to radiographic images.

PubMed

Brailean, J C; Little, D; Giger, M L; Chen, C T; Sullivan, B J

1992-01-01

The expectation maximization (EM) algorithm has received considerable attention in the area of positron emitted tomography (PET) as a restoration and reconstruction technique. In this paper, the restoration capabilities of the EM algorithm when applied to radiographic images is investigated. This application does not involve reconstruction. The performance of the EM algorithm is quantitatively evaluated using a "perceived" signal-to-noise ratio (SNR) as the image quality metric. This perceived SNR is based on statistical decision theory and includes both the observer's visual response function and a noise component internal to the eye-brain system. For a variety of processing parameters, the relative SNR (ratio of the processed SNR to the original SNR) is calculated and used as a metric to compare quantitatively the effects of the EM algorithm with two other image enhancement techniques: global contrast enhancement (windowing) and unsharp mask filtering. The results suggest that the EM algorithm's performance is superior when compared to unsharp mask filtering and global contrast enhancement for radiographic images which contain objects smaller than 4 mm.

Morphological rational operator for contrast enhancement.

PubMed

Peregrina-Barreto, Hayde; Herrera-Navarro, Ana M; Morales-Hernández, Luis A; Terol-Villalobos, Iván R

2011-03-01

Contrast enhancement is an important task in image processing that is commonly used as a preprocessing step to improve the images for other tasks such as segmentation. However, some methods for contrast improvement that work well in low-contrast regions affect good contrast regions as well. This occurs due to the fact that some elements may vanish. A method focused on images with different luminance conditions is introduced in the present work. The proposed method is based on morphological transformations by reconstruction and rational operations, which, altogether, allow a more accurate contrast enhancement resulting in regions that are in harmony with their environment. Furthermore, due to the properties of these morphological transformations, the creation of new elements on the image is avoided. The processing is carried out on luminance values in the u'v'Y color space, which avoids the creation of new colors. As a result of the previous considerations, the proposed method keeps the natural color appearance of the image.

Quantum image pseudocolor coding based on the density-stratified method

NASA Astrophysics Data System (ADS)

Jiang, Nan; Wu, Wenya; Wang, Luo; Zhao, Na

2015-05-01

Pseudocolor processing is a branch of image enhancement. It dyes grayscale images to color images to make the images more beautiful or to highlight some parts on the images. This paper proposes a quantum image pseudocolor coding scheme based on the density-stratified method which defines a colormap and changes the density value from gray to color parallel according to the colormap. Firstly, two data structures: quantum image GQIR and quantum colormap QCR are reviewed or proposed. Then, the quantum density-stratified algorithm is presented. Based on them, the quantum realization in the form of circuits is given. The main advantages of the quantum version for pseudocolor processing over the classical approach are that it needs less memory and can speed up the computation. Two kinds of examples help us to describe the scheme further. Finally, the future work are analyzed.

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.

Enhanced interfaces for web-based enterprise-wide image distribution.

PubMed

Jost, R Gilbert; Blaine, G James; Fritz, Kevin; Blume, Hartwig; Sadhra, Sarbjit

2002-01-01

Modern Web browsers support image distribution with two shortcomings: (1) image grayscale presentation at client workstations is often sub-optimal and generally inconsistent with the presentation state on diagnostic workstations and (2) an Electronic Patient Record (EPR) application usually cannot directly access images with an integrated viewer. We have modified our EPR and our Web-based image-distribution system to allow access to images from within the EPR. In addition, at the client workstation, a grayscale transformation is performed that consists of two components: a client-display-specific component based on the characteristic display function of the class of display system, and a modality-specific transformation that is downloaded with every image. The described techniques have been implemented in our institution and currently support enterprise-wide clinical image distribution. The effectiveness of the techniques is reviewed.

Task-based strategy for optimized contrast enhanced breast imaging: analysis of six imaging techniques for mammography and tomosynthesis

NASA Astrophysics Data System (ADS)

Ikejimba, Lynda; Kiarashi, Nooshin; Lin, Yuan; Chen, Baiyu; Ghate, Sujata V.; Zerhouni, Moustafa; Samei, Ehsan; Lo, Joseph Y.

2012-03-01

Digital breast tomosynthesis (DBT) is a novel x-ray imaging technique that provides 3D structural information of the breast. In contrast to 2D mammography, DBT minimizes tissue overlap potentially improving cancer detection and reducing number of unnecessary recalls. The addition of a contrast agent to DBT and mammography for lesion enhancement has the benefit of providing functional information of a lesion, as lesion contrast uptake and washout patterns may help differentiate between benign and malignant tumors. This study used a task-based method to determine the optimal imaging approach by analyzing six imaging paradigms in terms of their ability to resolve iodine at a given dose: contrast enhanced mammography and tomosynthesis, temporal subtraction mammography and tomosynthesis, and dual energy subtraction mammography and tomosynthesis. Imaging performance was characterized using a detectability index d', derived from the system task transfer function (TTF), an imaging task, iodine contrast, and the noise power spectrum (NPS). The task modeled a 5 mm lesion containing iodine concentrations between 2.1 mg/cc and 8.6 mg/cc. TTF was obtained using an edge phantom, and the NPS was measured over several exposure levels, energies, and target-filter combinations. Using a structured CIRS phantom, d' was generated as a function of dose and iodine concentration. In general, higher dose gave higher d', but for the lowest iodine concentration and lowest dose, dual energy subtraction tomosynthesis and temporal subtraction tomosynthesis demonstrated the highest performance.

Adaptive image contrast enhancement using generalizations of histogram equalization.

PubMed

Stark, J A

2000-01-01

This paper proposes a scheme for adaptive image-contrast enhancement based on a generalization of histogram equalization (HE). HE is a useful technique for improving image contrast, but its effect is too severe for many purposes. However, dramatically different results can be obtained with relatively minor modifications. A concise description of adaptive HE is set out, and this framework is used in a discussion of past suggestions for variations on HE. A key feature of this formalism is a "cumulation function," which is used to generate a grey level mapping from the local histogram. By choosing alternative forms of cumulation function one can achieve a wide variety of effects. A specific form is proposed. Through the variation of one or two parameters, the resulting process can produce a range of degrees of contrast enhancement, at one extreme leaving the image unchanged, at another yielding full adaptive equalization.

Enhancing atlas based segmentation with multiclass linear classifiers

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

Sdika, Michaël, E-mail: michael.sdika@creatis.insa-lyon.fr

Purpose: To present a method to enrich atlases for atlas based segmentation. Such enriched atlases can then be used as a single atlas or within a multiatlas framework. Methods: In this paper, machine learning techniques have been used to enhance the atlas based segmentation approach. The enhanced atlas defined in this work is a pair composed of a gray level image alongside an image of multiclass classifiers with one classifier per voxel. Each classifier embeds local information from the whole training dataset that allows for the correction of some systematic errors in the segmentation and accounts for the possible localmore » registration errors. The authors also propose to use these images of classifiers within a multiatlas framework: results produced by a set of such local classifier atlases can be combined using a label fusion method. Results: Experiments have been made on the in vivo images of the IBSR dataset and a comparison has been made with several state-of-the-art methods such as FreeSurfer and the multiatlas nonlocal patch based method of Coupé or Rousseau. These experiments show that their method is competitive with state-of-the-art methods while having a low computational cost. Further enhancement has also been obtained with a multiatlas version of their method. It is also shown that, in this case, nonlocal fusion is unnecessary. The multiatlas fusion can therefore be done efficiently. Conclusions: The single atlas version has similar quality as state-of-the-arts multiatlas methods but with the computational cost of a naive single atlas segmentation. The multiatlas version offers a improvement in quality and can be done efficiently without a nonlocal strategy.« less

Enhancing depth of focus in tilted microfluidics channels by digital holography.

PubMed

Matrecano, Marcella; Paturzo, Melania; Finizio, Andrea; Ferraro, Pietro

2013-03-15

In this Letter we propose a method to enhance the limited depth of field (DOF) in optical imaging systems, through digital holography. The proposed approach is based on the introduction of a cubic phase plate into the diffraction integral, analogous to what occurs in white-light imaging systems. By this approach we show that it is possible to improve the DOF and to recover the extended focus image of a tilted object in a single reconstruction step. Moreover, we demonstrate the possibility of obtaining well-focused biological cells flowing into a tilted microfluidic channel.

Efficient generalized cross-validation with applications to parametric image restoration and resolution enhancement.

PubMed

Nguyen, N; Milanfar, P; Golub, G

2001-01-01

In many image restoration/resolution enhancement applications, the blurring process, i.e., point spread function (PSF) of the imaging system, is not known or is known only to within a set of parameters. We estimate these PSF parameters for this ill-posed class of inverse problem from raw data, along with the regularization parameters required to stabilize the solution, using the generalized cross-validation method (GCV). We propose efficient approximation techniques based on the Lanczos algorithm and Gauss quadrature theory, reducing the computational complexity of the GCV. Data-driven PSF and regularization parameter estimation experiments with synthetic and real image sequences are presented to demonstrate the effectiveness and robustness of our method.

Verification and Validation of NASA-Supported Enhancements to Decision Support Tools of PECAD

NASA Technical Reports Server (NTRS)

Ross, Kenton W.; McKellip, Rodney; Moore, Roxzana F.; Fendley, Debbie

2005-01-01

This section of the evaluation report summarizes the verification and validation (V&V) of recently implemented, NASA-supported enhancements to the decision support tools of the Production Estimates and Crop Assessment Division (PECAD). The implemented enhancements include operationally tailored Moderate Resolution Imaging Spectroradiometer (MODIS) products and products of the Global Reservoir and Lake Monitor (GRLM). The MODIS products are currently made available through two separate decision support tools: the MODIS Image Gallery and the U.S. Department of Agriculture (USDA) Foreign Agricultural Service (FAS) MODIS Normalized Difference Vegetation Index (NDVI) Database. Both the Global Reservoir and Lake Monitor and MODIS Image Gallery provide near-real-time products through PECAD's CropExplorer. This discussion addresses two areas: 1. Assessments of the standard NASA products on which these enhancements are based. 2. Characterizations of the performance of the new operational products.

Differentiation of pre-ablation and post-ablation late gadolinium-enhanced cardiac MRI scans of longstanding persistent atrial fibrillation patients

NASA Astrophysics Data System (ADS)

Yang, Guang; Zhuang, Xiahai; Khan, Habib; Haldar, Shouvik; Nyktari, Eva; Li, Lei; Ye, Xujiong; Slabaugh, Greg; Wong, Tom; Mohiaddin, Raad; Keegan, Jennifer; Firmin, David

2017-03-01

Late Gadolinium-Enhanced Cardiac MRI (LGE CMRI) is an emerging non-invasive technique to image and quantify preablation native and post-ablation atrial scarring. Previous studies have reported that enhanced image intensities of the atrial scarring in the LGE CMRI inversely correlate with the left atrial endocardial voltage invasively obtained by electro-anatomical mapping. However, the reported reproducibility of using LGE CMRI to identify and quantify atrial scarring is variable. This may be due to two reasons: first, delineation of the left atrium (LA) and pulmonary veins (PVs) anatomy generally relies on manual operation that is highly subjective, and this could substantially affect the subsequent atrial scarring segmentation; second, simple intensity based image features may not be good enough to detect subtle changes in atrial scarring. In this study, we hypothesized that texture analysis can provide reliable image features for the LGE CMRI images subject to accurate and objective delineation of the heart anatomy based on a fully-automated whole heart segmentation (WHS) method. We tested the extracted texture features to differentiate between pre-ablation and post-ablation LGE CMRI studies in longstanding persistent atrial fibrillation patients. These patients often have extensive native scarring and differentiation from post-ablation scarring can be difficult. Quantification results showed that our method is capable of solving this classification task, and we can envisage further deployment of this texture analysis based method for other clinical problems using LGE CMRI.

TU-AB-BRA-11: Evaluation of Fully Automatic Volumetric GBM Segmentation in the TCGA-GBM Dataset: Prognosis and Correlation with VASARI Features

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

Rios Velazquez, E; Meier, R; Dunn, W

Purpose: Reproducible definition and quantification of imaging biomarkers is essential. We evaluated a fully automatic MR-based segmentation method by comparing it to manually defined sub-volumes by experienced radiologists in the TCGA-GBM dataset, in terms of sub-volume prognosis and association with VASARI features. Methods: MRI sets of 67 GBM patients were downloaded from the Cancer Imaging archive. GBM sub-compartments were defined manually and automatically using the Brain Tumor Image Analysis (BraTumIA), including necrosis, edema, contrast enhancing and non-enhancing tumor. Spearman’s correlation was used to evaluate the agreement with VASARI features. Prognostic significance was assessed using the C-index. Results: Auto-segmented sub-volumes showedmore » high agreement with manually delineated volumes (range (r): 0.65 – 0.91). Also showed higher correlation with VASARI features (auto r = 0.35, 0.60 and 0.59; manual r = 0.29, 0.50, 0.43, for contrast-enhancing, necrosis and edema, respectively). The contrast-enhancing volume and post-contrast abnormal volume showed the highest C-index (0.73 and 0.72), comparable to manually defined volumes (p = 0.22 and p = 0.07, respectively). The non-enhancing region defined by BraTumIA showed a significantly higher prognostic value (CI = 0.71) than the edema (CI = 0.60), both of which could not be distinguished by manual delineation. Conclusion: BraTumIA tumor sub-compartments showed higher correlation with VASARI data, and equivalent performance in terms of prognosis compared to manual sub-volumes. This method can enable more reproducible definition and quantification of imaging based biomarkers and has a large potential in high-throughput medical imaging research.« less

Gadolinium-enhanced MR images of the growing piglet skeleton: ionic versus nonionic contrast agent.

PubMed

Menezes, Nina M; Olear, Elizabeth A; Li, Xiaoming; Connolly, Susan A; Zurakowski, David; Foley, Mary; Shapiro, Frederic; Jaramillo, Diego

2006-05-01

To determine whether there are differences in the distribution of ionic and nonionic gadolinium-based contrast agents by evaluating contrast enhancement of the physis, epiphyseal cartilage, secondary ossification center, and metaphysis in the knees of normal piglets. Following approval from the Subcommittee on Research Animal Care, knees of 12 3-week-old piglets were imaged at 3-T magnetic resonance (MR) imaging after intravenous injection of gadoteridol (nonionic contrast agent; n = 6) or gadopentetate dimeglumine (ionic contrast agent; n = 6). Early enhancement evaluation with gradient-echo MR imaging was quantified and compared (Student t test) by means of enhancement ratios. Distribution of contrast material was assessed and compared (Student t test) by means of T1 measurements obtained before and at three 15-minute intervals after contrast agent administration. The relative visibility of the physis, epiphyseal cartilage, secondary ossification center, and metaphysis was qualitatively assessed by two observers and compared (Wilcoxon signed rank test). Differences in matrix content and cellularity that might explain the imaging findings were studied at histologic evaluation. Enhancement ratios were significantly higher for gadoteridol than for gadopentetate dimeglumine in the physis, epiphyseal cartilage, and secondary ossification center (P < .05). After contrast agent administration, T1 values decreased sharply for both agents-but more so for gadoteridol. Additionally, there was less variability in T1 values across structures with this contrast agent. Gadoteridol resulted in greater visibility of the physis, while gadopentetate dimeglumine resulted in greater contrast between the physis and metaphysis (P < .05). The results suggest different roles for the two gadolinium-based contrast agents: The nonionic contrast medium is better suited for evaluating perfusion and anatomic definition in the immature skeleton, while the ionic contrast medium is better for evaluating cartilage fixed-charge density. (c) RSNA, 2006.

Color Swapping to Enhance Breast Cancer Digital Images Qualities Using Stain Normalization

NASA Astrophysics Data System (ADS)

Muhimmah, Izzati; Puspasari Wijaya, Dhina; Indrayanti

2017-03-01

Histopathology is the disease diagnosis by means of the visual examination of tissues under the microscope. The virtually transparent tissue sections were prepared using a number of colored histochemical stains bound selectively to the cellular components. A variation of colors comes to be a problem in histopathology based upon the microscope lighting for the range of factors. This research aimed to investigate an image enhancement by applying a nonlinear mapping approach to stain normalization and histogram equalization for contrast enhancement. Validation was carried out in 59 datasets with 96.6% accordance and expert justification.

Carbon-Based Nanostructures as Advanced Contrast Agents for Magnetic Resonance Imaging

NASA Astrophysics Data System (ADS)

Ananta Narayanan, Jeyarama S.

2011-12-01

Superparamagnetic carbon-based nanostructures are presented as contrast agents (CAs) for advanced imaging applications such as cellular and molecular imaging using magnetic resonance imaging (MRI). Gadolinium-loaded, ultra-short single-walled carbon nanotubes (gadonanotubes; GNTs) are shown to have extremely high r1 relaxivities (contrast enhancement efficacy), especially at low-magnetic field strengths. The inherent lipophilicity of GNTs provides them the ability to image cells at low magnetic field strength. A carboxylated dextran-coated GNT (GadoDex) has been synthesized and proposed as a new biocompatible high-performance MRI CA. The r1 relaxivity is ca. 20 times greater than for other paramagnetic Gd-based CAs. This enhanced relaxivity for GadoDex is due to the synergistic effects of an increased molecular tumbling time (tauR) and a faster proton exchange rate (taum). GNTs also exhibit very large transverse relaxivities (r2) at high magnetic fields (≥ 3 T). The dependence of the transverse relaxation rates (especially R2*) of labeled cells on GNT concentration offers the possibility to quantify cell population in vivo using R2* mapping. The cell-labeling efficiency and high transverse relaxivities of GNTs has enabled the first non-iron oxide-based single-cell imaging using MRI. The residual metal catalyst particles of SWNT materials also have transverse relaxation properties. All of the SWNT materials exhibit superior transverse relaxation properties. However, purified SWNTs and US-tubes with less residual metal content exhibit better transverse relaxivities (r2), demonstrating the importance of the SWNT structure for enhanced MRI CA performance. A strategy to improve the r1 relaxivity of Gd-CAs by geometrically confining them within porous silicon particles (SiMPs) has been investigated. The enhancement in relaxivity is attributed to the slow diffusion of water molecules through the pores and the increase in the molecular tumbling time of the nanoconstruct. The universality of the strategy has been demonstrated for GNTs, gadofullerols and clinically-used MagnevistRTM. In summary, primary nanoscale confinement of Gd3+ ions in US-tubes has resulted in a new class of CAs which could revitalize low-field contrast-enhanced MRI, while extending and complementing current high-field MRI technology, as well. The observed boost in relaxivity upon a secondary nanoscale confinement of Gd-CAs within SiMPs suggests that additional unforeseen nanoscale effects may have the potential to further boost performance of MRI CAs.

Experimentally enhanced model-based deconvolution of propagation-based phase-contrast data

NASA Astrophysics Data System (ADS)

Pichotka, M.; Palma, K.; Hasn, S.; Jakubek, J.; Vavrik, D.

2016-12-01

In recent years phase-contrast has become a much investigated modality in radiographic imaging. The radiographic setups employed in phase-contrast imaging are typically rather costly and complex, e.g. high performance Talbot-Laue interferometers operated at synchrotron light sources. In-line phase-contrast imaging states the most pedestrian approach towards phase-contrast enhancement. Utilizing small angle deflection within the imaged sample and the entailed interference of the deflected and un-deflected beam during spatial propagation, in-line phase-contrast imaging only requires a well collimated X-ray source with a high contrast & high resolution detector. Employing high magnification the above conditions are intrinsically fulfilled in cone-beam micro-tomography. As opposed of 2D imaging, where contrast enhancement is generally considered beneficial, in tomographic modalities the in-line phase-contrast effect can be quite a nuisance since it renders the inverse problem posed by tomographic reconstruction inconsistent, thus causing reconstruction artifacts. We present an experimentally enhanced model-based approach to disentangle absorption and in-line phase-contrast. The approach employs comparison of transmission data to a system model computed iteratively on-line. By comparison of the forward model to absorption data acquired in continuous rotation strong local deviations of the data residual are successively identified as likely candidates for in-line phase-contrast. By inducing minimal vibrations (few mrad) to the sample around the peaks of such deviations the transmission signal can be decomposed into a constant absorptive fraction and an oscillating signal caused by phase-contrast which again allows to generate separate maps for absorption and phase-contrast. The contributions of phase-contrast and the corresponding artifacts are subsequently removed from the tomographic dataset. In principle, if a 3D handling of the sample is available, this method also allows to track discontinuities throughout the volume and therefore states a powerful tool in 3D defectoscopy.

Illuminant-adaptive color reproduction for mobile display

NASA Astrophysics Data System (ADS)

Kim, Jong-Man; Park, Kee-Hyon; Kwon, Oh-Seol; Cho, Yang-Ho; Ha, Yeong-Ho

2006-01-01

This paper proposes an illuminant-adaptive reproduction method using light adaptation and flare conditions for a mobile display. Mobile displays, such as PDAs and cellular phones, are viewed under various lighting conditions. In particular, images displayed in daylight are perceived as quite dark due to the light adaptation of the human visual system, as the luminance of a mobile display is considerably lower than that of an outdoor environment. In addition, flare phenomena decrease the color gamut of a mobile display by increasing the luminance of dark areas and de-saturating the chroma. Therefore, this paper presents an enhancement method composed of lightness enhancement and chroma compensation. First, the ambient light intensity is measured using a lux-sensor, then the flare is calculated based on the reflection ratio of the display device and the ambient light intensity. The relative cone response is nonlinear to the input luminance. This is also changed by the ambient light intensity. Thus, to improve the perceived image, the displayed luminance is enhanced by lightness linearization. In this paper, the image's luminance is transformed by linearization of the response to the input luminance according to the ambient light intensity. Next, the displayed image is compensated according to the physically reduced chroma, resulting from flare phenomena. The reduced chroma value is calculated according to the flare for each intensity. The chroma compensation method to maintain the original image's chroma is applied differently for each hue plane, as the flare affects each hue plane differently. At this time, the enhanced chroma also considers the gamut boundary. Based on experimental observations, the outer luminance-intensity generally ranges from 1,000 lux to 30,000 lux. Thus, in the case of an outdoor environment, i.e. greater than 1,000 lux, this study presents a color reproduction method based on an inverse cone response curve and flare condition. Consequently, the proposed algorithm improves the quality of the perceived image adaptive to an outdoor environment.

Infrared image segmentation method based on spatial coherence histogram and maximum entropy

NASA Astrophysics Data System (ADS)

Liu, Songtao; Shen, Tongsheng; Dai, Yao

2014-11-01

In order to segment the target well and suppress background noises effectively, an infrared image segmentation method based on spatial coherence histogram and maximum entropy is proposed. First, spatial coherence histogram is presented by weighting the importance of the different position of these pixels with the same gray-level, which is obtained by computing their local density. Then, after enhancing the image by spatial coherence histogram, 1D maximum entropy method is used to segment the image. The novel method can not only get better segmentation results, but also have a faster computation time than traditional 2D histogram-based segmentation methods.

X-ray spatial frequency heterodyne imaging of protein-based nanobubble contrast agents

PubMed Central

Rand, Danielle; Uchida, Masaki; Douglas, Trevor; Rose-Petruck, Christoph

2014-01-01

Spatial Frequency Heterodyne Imaging (SFHI) is a novel x-ray scatter imaging technique that utilizes nanoparticle contrast agents. The enhanced sensitivity of this new technique relative to traditional absorption-based x-ray radiography makes it promising for applications in biomedical and materials imaging. Although previous studies on SFHI have utilized only metal nanoparticle contrast agents, we show that nanomaterials with a much lower electron density are also suitable. We prepared protein-based “nanobubble” contrast agents that are comprised of protein cage architectures filled with gas. Results show that these nanobubbles provide contrast in SFHI comparable to that of gold nanoparticles of similar size. PMID:25321797

Machine Learning-based Texture Analysis of Contrast-enhanced MR Imaging to Differentiate between Glioblastoma and Primary Central Nervous System Lymphoma.

PubMed

Kunimatsu, Akira; Kunimatsu, Natsuko; Yasaka, Koichiro; Akai, Hiroyuki; Kamiya, Kouhei; Watadani, Takeyuki; Mori, Harushi; Abe, Osamu

2018-05-16

Although advanced MRI techniques are increasingly available, imaging differentiation between glioblastoma and primary central nervous system lymphoma (PCNSL) is sometimes confusing. We aimed to evaluate the performance of image classification by support vector machine, a method of traditional machine learning, using texture features computed from contrast-enhanced T 1 -weighted images. This retrospective study on preoperative brain tumor MRI included 76 consecutives, initially treated patients with glioblastoma (n = 55) or PCNSL (n = 21) from one institution, consisting of independent training group (n = 60: 44 glioblastomas and 16 PCNSLs) and test group (n = 16: 11 glioblastomas and 5 PCNSLs) sequentially separated by time periods. A total set of 67 texture features was computed on routine contrast-enhanced T 1 -weighted images of the training group, and the top four most discriminating features were selected as input variables to train support vector machine classifiers. These features were then evaluated on the test group with subsequent image classification. The area under the receiver operating characteristic curves on the training data was calculated at 0.99 (95% confidence interval [CI]: 0.96-1.00) for the classifier with a Gaussian kernel and 0.87 (95% CI: 0.77-0.95) for the classifier with a linear kernel. On the test data, both of the classifiers showed prediction accuracy of 75% (12/16) of the test images. Although further improvement is needed, our preliminary results suggest that machine learning-based image classification may provide complementary diagnostic information on routine brain MRI.

In Vivo Application of Proton-Electron Double-Resonance Imaging

PubMed Central

Kishimoto, Shun; Krishna, Murali C.; Khramtsov, Valery V.; Utsumi, Hideo

2018-01-01

Abstract Significance: Proton-electron double-resonance imaging (PEDRI) employs electron paramagnetic resonance irradiation with low-field magnetic resonance imaging so that the electron spin polarization is transferred to nearby protons, resulting in higher signals. PEDRI provides information about free radical distribution and, indirectly, about the local microenvironment such as partial pressure of oxygen (pO2), tissue permeability, redox status, and acid-base balance. Recent Advances: Local acid-base balance can be imaged by exploiting the different resonance frequency of radical probes between R and RH+ forms. Redox status can also be imaged by using the loss of radical-related signal after reduction. These methods require optimized radical probes and pulse sequences. Critical Issues: High-power radio frequency irradiation is needed for optimum signal enhancement, which may be harmful to living tissue by unwanted heat deposition. Free radical probes differ depending on the purpose of PEDRI. Some probes are less effective for enhancing signal than others, which can reduce image quality. It is so far not possible to image endogenous radicals by PEDRI because low concentrations and broad line widths of the radicals lead to negligible signal enhancement. Future Directions: PEDRI has similarities with electron paramagnetic resonance imaging (EPRI) because both techniques observe the EPR signal, directly in the case of EPRI and indirectly with PEDRI. PEDRI provides information that is vital to research on homeostasis, development of diseases, or treatment responses in vivo. It is expected that the development of new EPR techniques will give insights into novel PEDRI applications and vice versa. Antioxid. Redox Signal. 28, 1345–1364. PMID:28990406

Window classification of brain CT images in biomedical articles.

PubMed

Xue, Zhiyun; Antani, Sameer; Long, L Rodney; Demner-Fushman, Dina; Thoma, George R

2012-01-01

Effective capability to search biomedical articles based on visual properties of article images may significantly augment information retrieval in the future. In this paper, we present a new method to classify the window setting types of brain CT images. Windowing is a technique frequently used in the evaluation of CT scans, and is used to enhance contrast for the particular tissue or abnormality type being evaluated. In particular, it provides radiologists with an enhanced view of certain types of cranial abnormalities, such as the skull lesions and bone dysplasia which are usually examined using the " bone window" setting and illustrated in biomedical articles using "bone window images". Due to the inherent large variations of images among articles, it is important that the proposed method is robust. Our algorithm attained 90% accuracy in classifying images as bone window or non-bone window in a 210 image data set.

IRIS family of IRCCD thermal imagers integrating long-life cryogenic coolers, sophisticated algorithms for image enhancement, and hot points detection

NASA Astrophysics Data System (ADS)

Dupuy, Pascal; Harter, Jean

1995-09-01

Iris is a modular infrared thermal image developed by SAGEM since 1988, based on a 288 by 4 IRCCD detector. The first section of the presentation gives a description of the different modules of the IRIS thermal imager and their evolution in recent years. The second section covers the description of the major evolution, namely the integrated detector cooler assembly (IDCA), using a SOFRADIR 288 by 4 detector and a SAGEM microcooler, now integrated in the IRIS thermal imagers. The third section gives the description of two functions integrated in the IRIS thermal imager: (1) image enhancement, using a digital convolution filter, and (2) automatic hot points detection and tracking, offering an assistance to surveillance and automatic detection. The last section presents several programs for navy, air forces, and land applications for which IRIS has already been selected and achieved.

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.

Infrared variation reduction by simultaneous background suppression and target contrast enhancement for deep convolutional neural network-based automatic target recognition

NASA Astrophysics Data System (ADS)

Kim, Sungho

2017-06-01

Automatic target recognition (ATR) is a traditionally challenging problem in military applications because of the wide range of infrared (IR) image variations and the limited number of training images. IR variations are caused by various three-dimensional target poses, noncooperative weather conditions (fog and rain), and difficult target acquisition environments. Recently, deep convolutional neural network-based approaches for RGB images (RGB-CNN) showed breakthrough performance in computer vision problems, such as object detection and classification. The direct use of RGB-CNN to the IR ATR problem fails to work because of the IR database problems (limited database size and IR image variations). An IR variation-reduced deep CNN (IVR-CNN) to cope with the problems is presented. The problem of limited IR database size is solved by a commercial thermal simulator (OKTAL-SE). The second problem of IR variations is mitigated by the proposed shifted ramp function-based intensity transformation. This can suppress the background and enhance the target contrast simultaneously. The experimental results on the synthesized IR images generated by the thermal simulator (OKTAL-SE) validated the feasibility of IVR-CNN for military ATR applications.

The ability of computed tomography to diagnose placental abruption in the trauma patient.

PubMed

Kopelman, Tammy R; Berardoni, Nicole E; Manriquez, Maria; Gridley, Daniel; Vail, Sydney J; Pieri, Paola G; O'Neill; Pressman, Melissa A

2013-01-01

Fetal demise following trauma remains a devastating complication largely owing to placental injury and abruption. Our objective was to determine if abdominopelvic computed tomographic (CT) imaging can assess for placental abruption (PA) when obtained to exclude associated maternal injuries. Retrospective review of pregnant trauma patients of 20-week gestation or longer presenting to a trauma center during a 7-year period who underwent CT imaging as part of their initial evaluation. Radiographic images were reviewed by a radiologist for evidence of PA and classified based on percentage of visualized placental enhancement. Blinded to CT results, charts were reviewed by an obstetrician for clinical evidence of PA and classified as strongly positive, possibly positive, or no evidence. A total of 176 patients met inclusion criteria. CT imaging revealed evidence of PA in 61 patients (35%). As the percentage of placental enhancement decreased, patients were more likely to have strong clinical manifestations of PA, reaching statistical significance when enhancement was less than 50%. CT imaging evidence of PA was apparent in all patients who required delivery for nonassuring fetal heart tones. CT imaging evaluation of the placenta can accurately identify PA and therefore can help stratify patients at risk for fetal complications. The likelihood of requiring delivery increased as placental enhancement declined to less than 25%. Diagnostic study, level III.

Lung cancer mimicking lung abscess formation on CT images.

PubMed

Taira, Naohiro; Kawabata, Tsutomu; Gabe, Atsushi; Ichi, Takaharu; Kushi, Kazuaki; Yohena, Tomofumi; Kawasaki, Hidenori; Yamashiro, Toshimitsu; Ishikawa, Kiyoshi

2014-01-01

Male, 64 FINAL DIAGNOSIS: Lung pleomorphic carcinoma Symptoms: Cough • fever - Clinical Procedure: - Specialty: Oncology. Unusual clinical course. The diagnosis of lung cancer is often made based on computed tomography (CT) image findings if it cannot be confirmed on pathological examinations, such as bronchoscopy. However, the CT image findings of cancerous lesions are similar to those of abscesses.We herein report a case of lung cancer that resembled a lung abscess on CT. We herein describe the case of 64-year-old male who was diagnosed with lung cancer using surgery. In this case, it was quite difficult to distinguish between the lung cancer and a lung abscess on CT images, and a lung abscess was initially suspected due to symptoms, such as fever and coughing, contrast-enhanced CT image findings showing a ring-enhancing mass in the right upper lobe and the patient's laboratory test results. However, a pathological diagnosis of lung cancer was confirmed according to the results of a rapid frozen section biopsy of the lesion. This case suggests that physicians should not suspect both a lung abscesses and malignancy in cases involving masses presenting as ring-enhancing lesions on contrast-enhanced CT.

SU-D-207-01: Markerless Respiratory Motion Tracking with Contrast Enhanced Thoracic Cone Beam CT Projections

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

Chao, M; Yuan, Y; Rosenzweig, K

2015-06-15

Purpose: To develop a novel technique to enhance the image contrast of clinical cone beam CT projections and extract respiratory signals based on anatomical motion using the modified Amsterdam Shroud (AS) method to benefit image guided radiation therapy. Methods: Thoracic cone beam CT projections acquired prior to treatment were preprocessed to increase their contrast for better respiratory signal extraction. Air intensity on raw images was firstly estimated and then applied to correct the projections to generate new attenuation images that were subsequently improved with deeper anatomy feature enhancement through taking logarithm operation, derivative along superior-inferior direction, respectively. All pixels onmore » individual post-processed two dimensional images were horizontally summed to one column and all projections were combined side by side to create an AS image from which patient’s respiratory signal was extracted. The impact of gantry rotation on the breathing signal rendering was also investigated. Ten projection image sets from five lung cancer patients acquired with the Varian Onboard Imager on 21iX Clinac (Varian Medical Systems, Palo Alto, CA) were employed to assess the proposed technique. Results: Application of the air correction on raw projections showed that more than an order of magnitude of contrast enhancement was achievable. The typical contrast on the raw projections is around 0.02 while that on attenuation images could greater than 0.5. Clear and stable breathing signal can be reliably extracted from the new images while the uncorrected projection sets failed to yield clear signals most of the time. Conclusion: Anatomy feature plays a key role in yielding breathing signal from the projection images using the AS technique. The air correction process facilitated the contrast enhancement significantly and attenuation images thus obtained provides a practical solution to obtaining markerless breathing motion tracking.« less

High Resolution X-Ray Phase Contrast Imaging with Acoustic Tissue-Selective Contrast Enhancement

DTIC Science & Technology

2005-06-01

Ultrasonics Symp 1319 (1999). 17. Sarvazyan, A. P. Shear Wave Elasticity Imaging: A New Ultrasonic Technology of Medical Diagnostics. Ultrasound in...samples using acoustically modulated X-ray phase contrast imaging. 15. SUBJECT TERMS x-ray, ultrasound, phase contrast, imaging, elastography 16...x-rays, phase contrast imaging is based on phase changes as x-rays traverse a body resulting in wave interference that result in intensity changes in

A Framework for Reproducible Latent Fingerprint Enhancements.

PubMed

Carasso, Alfred S

2014-01-01

Photoshop processing of latent fingerprints is the preferred methodology among law enforcement forensic experts, but that appproach is not fully reproducible and may lead to questionable enhancements. Alternative, independent, fully reproducible enhancements, using IDL Histogram Equalization and IDL Adaptive Histogram Equalization, can produce better-defined ridge structures, along with considerable background information. Applying a systematic slow motion smoothing procedure to such IDL enhancements, based on the rapid FFT solution of a Lévy stable fractional diffusion equation, can attenuate background detail while preserving ridge information. The resulting smoothed latent print enhancements are comparable to, but distinct from, forensic Photoshop images suitable for input into automated fingerprint identification systems, (AFIS). In addition, this progressive smoothing procedure can be reexamined by displaying the suite of progressively smoother IDL images. That suite can be stored, providing an audit trail that allows monitoring for possible loss of useful information, in transit to the user-selected optimal image. Such independent and fully reproducible enhancements provide a valuable frame of reference that may be helpful in informing, complementing, and possibly validating the forensic Photoshop methodology.

A Framework for Reproducible Latent Fingerprint Enhancements

PubMed Central

Carasso, Alfred S.

2014-01-01

Photoshop processing1 of latent fingerprints is the preferred methodology among law enforcement forensic experts, but that appproach is not fully reproducible and may lead to questionable enhancements. Alternative, independent, fully reproducible enhancements, using IDL Histogram Equalization and IDL Adaptive Histogram Equalization, can produce better-defined ridge structures, along with considerable background information. Applying a systematic slow motion smoothing procedure to such IDL enhancements, based on the rapid FFT solution of a Lévy stable fractional diffusion equation, can attenuate background detail while preserving ridge information. The resulting smoothed latent print enhancements are comparable to, but distinct from, forensic Photoshop images suitable for input into automated fingerprint identification systems, (AFIS). In addition, this progressive smoothing procedure can be reexamined by displaying the suite of progressively smoother IDL images. That suite can be stored, providing an audit trail that allows monitoring for possible loss of useful information, in transit to the user-selected optimal image. Such independent and fully reproducible enhancements provide a valuable frame of reference that may be helpful in informing, complementing, and possibly validating the forensic Photoshop methodology. PMID:26601028

Comparative study of conventional US, contrast enhanced US and enhanced MR for the follow-up of prostatic radiofrequency ablation.

PubMed

Feng, Chao; Hu, Bin; Hu, Bing; Chen, Lei; Li, Jia; Huang, Jin

2017-06-01

The aim of the present study was to evaluate and compare the effectiveness of different imaging methods during follow-up of prostatic radiofrequency ablation. Prostatic radiofrequency ablation (RFA) was performed in 20 healthy beagle dogs. Various imaging examinations were used to monitor the results of RFA, including conventional ultrasound (US), contrast enhanced ultrasound (CEUS) and enhanced magnetic resonance (MR). Imaging exams were performed at five phases: Immediately following RFA, one week later, one month later, three months later and six months later. The morphology for each imaging test and histological results were recorded and compared in each phase. Based on the actual results from autopsy, the accuracy of those imaging exams was evaluated. The canine prostate gland demonstrated typical coagulative necrosis immediately following RFA. The lesion would develop into stable cyst if no other complications occurred within the six-month follow-up. Regarding the RFA lesion volume measurement and the reflection of pathological changes, conventional US was not able to accurately measure the volume of RFA lesion and missed many more details concerning the RFA-treated area than CEUS and MR during the three months. The results from CEUS exhibited comparable accuracy to those from enhanced MR at each phase. However, there were no significant differences in the results from US, CEUS and MR at six months, which may contribute to the complete formation of lesion cyst. In the early phase, conventional US was not sufficient for evaluating the efficacy of RFA. Enhanced US and MR provided clear images and accurate information. However, CEUS has the advantage of being more economical, using more convenient equipment and faster scanning, thus identifying it as the more feasible choice. Furthermore, no notable advantages were observed among any image examinations in the long-term follow-up.

Quantum Color Image Encryption Algorithm Based on A Hyper-Chaotic System and Quantum Fourier Transform

NASA Astrophysics Data System (ADS)

Tan, Ru-Chao; Lei, Tong; Zhao, Qing-Min; Gong, Li-Hua; Zhou, Zhi-Hong

2016-12-01

To improve the slow processing speed of the classical image encryption algorithms and enhance the security of the private color images, a new quantum color image encryption algorithm based on a hyper-chaotic system is proposed, in which the sequences generated by the Chen's hyper-chaotic system are scrambled and diffused with three components of the original color image. Sequentially, the quantum Fourier transform is exploited to fulfill the encryption. Numerical simulations show that the presented quantum color image encryption algorithm possesses large key space to resist illegal attacks, sensitive dependence on initial keys, uniform distribution of gray values for the encrypted image and weak correlation between two adjacent pixels in the cipher-image.

Linearized inversion of multiple scattering seismic energy

NASA Astrophysics Data System (ADS)

Aldawood, Ali; Hoteit, Ibrahim; Zuberi, Mohammad

2014-05-01

Internal multiples deteriorate the quality of the migrated image obtained conventionally by imaging single scattering energy. So, imaging seismic data with the single-scattering assumption does not locate multiple bounces events in their actual subsurface positions. However, imaging internal multiples properly has the potential to enhance the migrated image because they illuminate zones in the subsurface that are poorly illuminated by single scattering energy such as nearly vertical faults. Standard migration of these multiples provides subsurface reflectivity distributions with low spatial resolution and migration artifacts due to the limited recording aperture, coarse sources and receivers sampling, and the band-limited nature of the source wavelet. The resultant image obtained by the adjoint operator is a smoothed depiction of the true subsurface reflectivity model and is heavily masked by migration artifacts and the source wavelet fingerprint that needs to be properly deconvolved. Hence, we proposed a linearized least-square inversion scheme to mitigate the effect of the migration artifacts, enhance the spatial resolution, and provide more accurate amplitude information when imaging internal multiples. The proposed algorithm uses the least-square image based on single-scattering assumption as a constraint to invert for the part of the image that is illuminated by internal scattering energy. Then, we posed the problem of imaging double-scattering energy as a least-square minimization problem that requires solving the normal equation of the following form: GTGv = GTd, (1) where G is a linearized forward modeling operator that predicts double-scattered seismic data. Also, GT is a linearized adjoint operator that image double-scattered seismic data. Gradient-based optimization algorithms solve this linear system. Hence, we used a quasi-Newton optimization technique to find the least-square minimizer. In this approach, an estimate of the Hessian matrix that contains curvature information is modified at every iteration by a low-rank update based on gradient changes at every step. At each iteration, the data residual is imaged using GT to determine the model update. Application of the linearized inversion to synthetic data to image a vertical fault plane demonstrate the effectiveness of this methodology to properly delineate the vertical fault plane and give better amplitude information than the standard migrated image using the adjoint operator that takes into account internal multiples. Thus, least-square imaging of multiple scattering enhances the spatial resolution of the events illuminated by internal scattering energy. It also deconvolves the source signature and helps remove the fingerprint of the acquisition geometry. The final image is obtained by the superposition of the least-square solution based on single scattering assumption and the least-square solution based on double scattering assumption.

Active imaging with the aids of polarization retrieve in turbid media system

NASA Astrophysics Data System (ADS)

Tao, Qiangqiang; Sun, Yongxuan; Shen, Fei; Xu, Qiang; Gao, Jun; Guo, Zhongyi

2016-01-01

We propose a novel active imaging based on the polarization retrieve (PR) method in turbid media system. In our simulations, the Monte Carlo (MC) algorithm has been used to investigate the scattering process between the incident photons and the scattering particles, and the visually concordant object but with different polarization characteristics in different regions, has been selected as the original target that is placed in the turbid media. Under linearly and circularly polarized illuminations, the simulation results demonstrate that the corresponding polarization properties can provide additional information for the imaging, and the contrast of the polarization image can also be enhanced greatly compared to the simplex intensity image in the turbid media. Besides, the polarization image adjusted by the PR method can further enhance the visibility and contrast. In addition, by PR imaging method, with the increasing particles' size in Mie's scale, the visibility can be enhanced, because of the increased forward scattering effect. In general, in the same circumstance, the circular polarization images can offer a better contrast and visibility than that of linear ones. The results indicate that the PR imaging method is more applicable to the scattering media system with relatively larger particles such as aerosols, heavy fog, cumulus, and seawater, as well as to biological tissues and blood media.

Robust algebraic image enhancement for intelligent control systems

NASA Technical Reports Server (NTRS)

Lerner, Bao-Ting; Morrelli, Michael

1993-01-01

Robust vision capability for intelligent control systems has been an elusive goal in image processing. The computationally intensive techniques a necessary for conventional image processing make real-time applications, such as object tracking and collision avoidance difficult. In order to endow an intelligent control system with the needed vision robustness, an adequate image enhancement subsystem capable of compensating for the wide variety of real-world degradations, must exist between the image capturing and the object recognition subsystems. This enhancement stage must be adaptive and must operate with consistency in the presence of both statistical and shape-based noise. To deal with this problem, we have developed an innovative algebraic approach which provides a sound mathematical framework for image representation and manipulation. Our image model provides a natural platform from which to pursue dynamic scene analysis, and its incorporation into a vision system would serve as the front-end to an intelligent control system. We have developed a unique polynomial representation of gray level imagery and applied this representation to develop polynomial operators on complex gray level scenes. This approach is highly advantageous since polynomials can be manipulated very easily, and are readily understood, thus providing a very convenient environment for image processing. Our model presents a highly structured and compact algebraic representation of grey-level images which can be viewed as fuzzy sets.

Exploring the use of memory colors for image enhancement

NASA Astrophysics Data System (ADS)

Xue, Su; Tan, Minghui; McNamara, Ann; Dorsey, Julie; Rushmeier, Holly

2014-02-01

Memory colors refer to those colors recalled in association with familiar objects. While some previous work introduces this concept to assist digital image enhancement, their basis, i.e., on-screen memory colors, are not appropriately investigated. In addition, the resulting adjustment methods developed are not evaluated from a perceptual view of point. In this paper, we first perform a context-free perceptual experiment to establish the overall distributions of screen memory colors for three pervasive objects. Then, we use a context-based experiment to locate the most representative memory colors; at the same time, we investigate the interactions of memory colors between different objects. Finally, we show a simple yet effective application using representative memory colors to enhance digital images. A user study is performed to evaluate the performance of our technique.

Hadamard-Encoded Multipulses for Contrast-Enhanced Ultrasound Imaging.

PubMed

Gong, Ping; Song, Pengfei; Chen, Shigao

2017-11-01

The development of contrast-enhanced ultrasound (CEUS) imaging offers great opportunities for new ultrasound clinical applications such as myocardial perfusion imaging and abdominal lesion characterization. In CEUS imaging, the contrast agents (i.e., microbubbles) are utilized to improve the contrast between blood and tissue based on their high nonlinearity under low ultrasound pressure. In this paper, we propose a new CEUS pulse sequence by combining Hadamard-encoded multipulses (HEM) with fundamental frequency bandpass filter (i.e., filter centered on transmit frequency). HEM consecutively emits multipulses encoded by a second-order Hadamard matrix in each of the two transmission events (i.e., pulse-echo events), as opposed to conventional CEUS methods which emit individual pulses in two separate transmission events (i.e., pulse inversion (PI), amplitude modulation (AM), and PIAM). In HEM imaging, the microbubble responses can be improved by the longer transmit pulse, and the tissue harmonics can be suppressed by the fundamental frequency filter, leading to significantly improved contrast-to-tissue ratio (CTR) and signal-to-noise ratio (SNR). In addition, the fast polarity change between consecutive coded pulse emissions excites strong nonlinear microbubble echoes, further enhancing the CEUS image quality. The spatial resolution of HEM image is compromised as compared to other microbubble imaging methods due to the longer transmit pulses and the lower imaging frequency (i.e., fundamental frequency). However, the resolution loss was shown to be negligible and could be offset by the significantly enhanced CTR, SNR, and penetration depth. These properties of HEM can potentially facilitate robust CEUS imaging for many clinical applications, especially for deep abdominal organs and heart.

Depth-enhanced three-dimensional-two-dimensional convertible display based on modified integral imaging.

PubMed

Park, Jae-Hyeung; Kim, Hak-Rin; Kim, Yunhee; Kim, Joohwan; Hong, Jisoo; Lee, Sin-Doo; Lee, Byoungho

2004-12-01

A depth-enhanced three-dimensional-two-dimensional convertible display that uses a polymer-dispersed liquid crystal based on the principle of integral imaging is proposed. In the proposed method, a lens array is located behind a transmission-type display panel to form an array of point-light sources, and a polymer-dispersed liquid crystal is electrically controlled to pass or to scatter light coming from these point-light sources. Therefore, three-dimensional-two-dimensional conversion is accomplished electrically without any mechanical movement. Moreover, the nonimaging structure of the proposed method increases the expressible depth range considerably. We explain the method of operation and present experimental results.

Noise Enhanced Sensory Signal Processing

DTIC Science & Technology

2012-01-31

Moreover, a contrast sensitivity function (CSF), as an object feature enhancer , was employed for further improving the segmentation performance, which...Digital mammography work appeared in ACM Tech News on Feb. 3, 2010. 8. Interactions/Transitions Invited talks: • P.K. Varshney, “Noise Enhanced ... mammography machines with regard to our work on image enhancement based on SR. • Lectures at Lockheed Martin in Syracuse and SRC that included discussion

Applications of two-photon fluorescence microscopy in deep-tissue imaging

NASA Astrophysics Data System (ADS)

Dong, Chen-Yuan; Yu, Betty; Hsu, Lily L.; Kaplan, Peter D.; Blankschstein, D.; Langer, Robert; So, Peter T. C.

2000-07-01

Based on the non-linear excitation of fluorescence molecules, two-photon fluorescence microscopy has become a significant new tool for biological imaging. The point-like excitation characteristic of this technique enhances image quality by the virtual elimination of off-focal fluorescence. Furthermore, sample photodamage is greatly reduced because fluorescence excitation is limited to the focal region. For deep tissue imaging, two-photon microscopy has the additional benefit in the greatly improved imaging depth penetration. Since the near- infrared laser sources used in two-photon microscopy scatter less than their UV/glue-green counterparts, in-depth imaging of highly scattering specimen can be greatly improved. In this work, we will present data characterizing both the imaging characteristics (point-spread-functions) and tissue samples (skin) images using this novel technology. In particular, we will demonstrate how blind deconvolution can be used further improve two-photon image quality and how this technique can be used to study mechanisms of chemically-enhanced, transdermal drug delivery.

Recent Design Development in Molecular Imaging for Breast Cancer Detection Using Nanometer CMOS Based Sensors.

PubMed

Nguyen, Dung C; Ma, Dongsheng Brian; Roveda, Janet M W

2012-01-01

As one of the key clinical imaging methods, the computed X-ray tomography can be further improved using new nanometer CMOS sensors. This will enhance the current technique's ability in terms of cancer detection size, position, and detection accuracy on the anatomical structures. The current paper reviewed designs of SOI-based CMOS sensors and their architectural design in mammography systems. Based on the existing experimental results, using the SOI technology can provide a low-noise (SNR around 87.8 db) and high-gain (30 v/v) CMOS imager. It is also expected that, together with the fast data acquisition designs, the new type of imagers may play important roles in the near-future high-dimensional images in additional to today's 2D imagers.

Radiometric and geometric characteristics of Pleiades images

NASA Astrophysics Data System (ADS)

Jacobsen, K.; Topan, H.; Cam, A.; Özendi, M.; Oruc, M.

2014-11-01

Pleiades images are distributed with 50 cm ground sampling distance (GSD) even if the physical resolution for nadir images is just 70 cm. By theory this should influence the effective GSD determined by means of point spread function at image edges. Nevertheless by edge enhancement the effective GSD can be improved, but this should cause enlarged image noise. Again image noise can be reduced by image restoration. Finally even optimized image restoration cannot improve the image information from 70 cm to 50 cm without loss of details, requiring a comparison of Pleiades image details with other very high resolution space images. The image noise has been determined by analysis of the whole images for any sub-area with 5 pixels times 5 pixels. Based on the standard deviation of grey values in the small sub-areas the image noise has been determined by frequency analysis. This leads to realistic results, checked by test targets. On the other hand the visual determination of image noise based on apparently homogenous sub-areas results in too high values because the human eye is not able to identify small grey value differences - it is limited to just approximately 40 grey value steps over the available gray value range, so small difference in grey values cannot be seen, enlarging results of a manual noise determination. A tri-stereo combination of Pleiades 1A in a mountainous, but partially urban, area has been analyzed and compared with images of the same area from WorldView-1, QuickBird and IKONOS. The image restoration of the Pleiades images is very good, so the effective image resolution resulted in a factor 1.0, meaning that the effective resolution corresponds to the nominal resolution of 50 cm. This does not correspond to the physical resolution of 70 cm, but by edge enhancement the steepness of the grey value profile across the edge can be enlarged, reducing the width of the point spread function. Without additional filtering edge enhancement enlarges the image noise, but the average image noise of approximately 1.0 grey values related to 8 bit images is very small, not indicating the edge enhancement and the down sampling of the GSD from 70 cm to 50 cm. So the direct comparison with the other images has to give the answer if the image quality of Pleiades images is on similar level as corresponding to the nominal resolution. As expected with the image geometry there is no problem. This is the case for all used space images in the test area, where the point identification limits the accuracy of the scene orientation.

A NOISE ADAPTIVE FUZZY EQUALIZATION METHOD FOR PROCESSING SOLAR EXTREME ULTRAVIOLET IMAGES

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

Druckmueller, M., E-mail: druckmuller@fme.vutbr.cz

A new image enhancement tool ideally suited for the visualization of fine structures in extreme ultraviolet images of the corona is presented in this paper. The Noise Adaptive Fuzzy Equalization method is particularly suited for the exceptionally high dynamic range images from the Atmospheric Imaging Assembly instrument on the Solar Dynamics Observatory. This method produces artifact-free images and gives significantly better results than methods based on convolution or Fourier transform which are often used for that purpose.

Perceptual Contrast Enhancement with Dynamic Range Adjustment

PubMed Central

Zhang, Hong; Li, Yuecheng; Chen, Hao; Yuan, Ding; Sun, Mingui

2013-01-01

Recent years, although great efforts have been made to improve its performance, few Histogram equalization (HE) methods take human visual perception (HVP) into account explicitly. The human visual system (HVS) is more sensitive to edges than brightness. This paper proposes to take use of this nature intuitively and develops a perceptual contrast enhancement approach with dynamic range adjustment through histogram modification. The use of perceptual contrast connects the image enhancement problem with the HVS. To pre-condition the input image before the HE procedure is implemented, a perceptual contrast map (PCM) is constructed based on the modified Difference of Gaussian (DOG) algorithm. As a result, the contrast of the image is sharpened and high frequency noise is suppressed. A modified Clipped Histogram Equalization (CHE) is also developed which improves visual quality by automatically detecting the dynamic range of the image with improved perceptual contrast. Experimental results show that the new HE algorithm outperforms several state-of-the-art algorithms in improving perceptual contrast and enhancing details. In addition, the new algorithm is simple to implement, making it suitable for real-time applications. PMID:24339452

Contrast-enhanced magnetic resonance imaging of pulmonary lesions: description of a technique aiming clinical practice.

PubMed

Koenigkam-Santos, Marcel; Optazaite, Elzbieta; Sommer, Gregor; Safi, Seyer; Heussel, Claus Peter; Kauczor, Hans-Ulrich; Puderbach, Michael

2015-01-01

To propose a technique for evaluation of pulmonary lesions using contrast-enhanced MRI; to assess morphological patterns of enhancement and correlate quantitative analysis with histopathology. Thirty-six patients were prospectively studied. Volumetric-interpolated T1W images were obtained during consecutive breath holds after bolus triggered contrast injection. Volume coverage of first three acquisitions was limited (higher temporal resolution) and last acquisition obtained at 4th min. Two radiologists individually evaluated the patterns of enhancement. Region-of-interest-based signal intensity (SI)-time curves were created to assess quantitative parameters. Readers agreed moderately to substantially concerning lesions' enhancement pattern. SI-time curves could be created for all lesions. In comparison to benign, malignant lesions showed higher values of maximum enhancement, early peak, slope and 4th min enhancement. Early peak >15% showed 100% sensitivity to detect malignancy, maximum enhancement >40% showed 100% specificity. The proposed technique is robust, simple to perform and can be applied in clinical scenario. It allows visual evaluation of enhancement pattern/progression together with creation of SI-time curves and assessment of derived quantitative parameters. Perfusion analysis was highly sensitive to detect malignancy, in accordance to what is recommended by most recent guidelines on imaging evaluation of pulmonary lesions. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Bone marrow with diffuse tumor infiltration in patients with lymphoproliferative diseases: dynamic gadolinium-enhanced MR imaging.

PubMed

Rahmouni, Alain; Montazel, Jean-Luc; Divine, Marine; Lepage, Eric; Belhadj, Karim; Gaulard, Philippe; Bouanane, Mohamed; Golli, Mondher; Kobeiter, Hicham

2003-12-01

To evaluate gadolinium enhancement of bone marrow in patients with lymphoproliferative diseases and diffuse bone marrow involvement. Dynamic contrast material-enhanced magnetic resonance (MR) imaging of the thoracolumbar spine was performed in 42 patients with histologically proved diffuse bone marrow involvement and newly diagnosed myeloma (n = 31), non-Hodgkin lymphoma (n = 8), or Hodgkin disease (n = 3). The maximum percentage of enhancement (Emax), enhancement slope, and enhancement washout were determined from enhancement time curves (ETCs). A three-grade system for scoring bone marrow involvement was based on the percentage of neoplastic cells in bone marrow samples. Quantitative ETC values for the 42 patients were compared with ETC values for healthy subjects and with grades of bone marrow involvement by using mean t test comparisons. Receiver operating characteristic (ROC) analysis was conducted by comparing Emax values between patients with and those without bone marrow involvement. Baseline and follow-up MR imaging findings were compared in nine patients. Significant differences in Emax (P <.001), slope (P <.001), and washout (P =.005) were found between subjects with normal bone marrow and patients with diffuse bone marrow involvement. ROC analysis results showed Emax values to have a diagnostic accuracy of 99%. Emax, slope, and washout values increased with increasing bone marrow involvement grade. The mean Emax increased from 339% to 737%. Contrast enhancement decreased after treatment in all six patients who responded to treatment but not in two of three patients who did not respond to treatment. Dynamic contrast-enhanced MR images can demonstrate increased bone marrow enhancement in patients with lymphoproliferative diseases and marrow involvement.

Quantitative differential phase contrast imaging at high resolution with radially asymmetric illumination.

PubMed

Lin, Yu-Zi; Huang, Kuang-Yuh; Luo, Yuan

2018-06-15

Half-circle illumination-based differential phase contrast (DPC) microscopy has been utilized to recover phase images through a pair of images along multiple axes. Recently, the half-circle based DPC using 12-axis measurements significantly provides a circularly symmetric phase transfer function to improve accuracy for more stable phase recovery. Instead of using half-circle-based DPC, we propose a new scheme of DPC under radially asymmetric illumination to achieve circularly symmetric phase transfer function and enhance the accuracy of phase recovery in a more stable and efficient fashion. We present the design, implementation, and experimental image data demonstrating the ability of our method to obtain quantitative phase images of microspheres, as well as live fibroblast cell samples.

An improved feature extraction algorithm based on KAZE for multi-spectral image

NASA Astrophysics Data System (ADS)

Yang, Jianping; Li, Jun

2018-02-01

Multi-spectral image contains abundant spectral information, which is widely used in all fields like resource exploration, meteorological observation and modern military. Image preprocessing, such as image feature extraction and matching, is indispensable while dealing with multi-spectral remote sensing image. Although the feature matching algorithm based on linear scale such as SIFT and SURF performs strong on robustness, the local accuracy cannot be guaranteed. Therefore, this paper proposes an improved KAZE algorithm, which is based on nonlinear scale, to raise the number of feature and to enhance the matching rate by using the adjusted-cosine vector. The experiment result shows that the number of feature and the matching rate of the improved KAZE are remarkably than the original KAZE algorithm.

The evolution of gadolinium based contrast agents: from single-modality to multi-modality

NASA Astrophysics Data System (ADS)

Zhang, Li; Liu, Ruiqing; Peng, Hui; Li, Penghui; Xu, Zushun; Whittaker, Andrew K.

2016-05-01

Gadolinium-based contrast agents are extensively used as magnetic resonance imaging (MRI) contrast agents due to their outstanding signal enhancement and ease of chemical modification. However, it is increasingly recognized that information obtained from single modal molecular imaging cannot satisfy the higher requirements on the efficiency and accuracy for clinical diagnosis and medical research, due to its limitation and default rooted in single molecular imaging technique itself. To compensate for the deficiencies of single function magnetic resonance imaging contrast agents, the combination of multi-modality imaging has turned to be the research hotpot in recent years. This review presents an overview on the recent developments of the functionalization of gadolinium-based contrast agents, and their application in biomedicine applications.

Uav-Based 3d Urban Environment Monitoring

NASA Astrophysics Data System (ADS)

Boonpook, Wuttichai; Tan, Yumin; Liu, Huaqing; Zhao, Binbin; He, Lingfeng

2018-04-01

Unmanned Aerial Vehicle (UAV) based remote sensing can be used to make three-dimensions (3D) mapping with great flexibility, besides the ability to provide high resolution images. In this paper we propose a quick-change detection method on UAV images by combining altitude from Digital Surface Model (DSM) and texture analysis from images. Cases of UAV images with and without georeferencing are both considered. Research results show that the accuracy of change detection can be enhanced with georeferencing procedure, and the accuracy and precision of change detection on UAV images which are collected both vertically and obliquely but without georeferencing also have a good performance.

Comparison of Low-Dose Higher-Relaxivity and Standard-Dose Lower-Relaxivity Contrast Media for Delayed-Enhancement MRI: A Blinded Randomized Crossover Study.

PubMed

Cheong, Benjamin Y C; Duran, Cihan; Preventza, Ourania A; Muthupillai, Raja

2015-09-01

The gadolinium-based MRI contrast agent gadobenate dimeglumine has nearly twice the MR relaxivity of gadopentetate dimeglumine at 1.5 T. The purpose of this study was to determine whether a lower dose (0.1 mmol/kg) of gadobenate dimeglumine can be used to obtain delayed-enhancement MR images comparable to those obtained with a standard dose (0.2 mmol/kg) of gadopentetate dimeglumine. In this blinded randomized crossover study, 20 patients with known myocardial infarction underwent two separate delayed-enhancement MRI examinations after receiving 0.1 mmol/kg gadobenate dimeglumine and 0.2 mmol/kg gadopentetate dimeglumine (random administration). The conspicuity of lesion enhancement 5, 10, and 20 minutes after contrast administration was quantified as relative enhancement ratio (RER). With either gadolinium-based contrast agent, damaged myocardium had higher signal intensity than normal remote myocardium (RER > 4) on delayed-enhancement MR images, and the blood RER declined over time after contrast administration. The blood RER was not significantly higher for gadobenate dimeglumine than for gadopentetate dimeglumine at 5 and 10 minutes. Nevertheless, there was a larger reduction in blood RER for gadobenate dimeglumine than for gadopentetate dimeglumine between 5 and 10 minutes and between 10 and 20 minutes. The volumes of enhancement were similar for gadobenate dimeglumine (13.6 ± 8.8 cm(3)) and gadopentetate dimeglumine (13.5 ± 8.9 cm(3)) (p = 0.98). The mean difference in Bland-Altman analysis for delayed-enhancement volume between the agents was 0.1 cm(3). Qualitatively and quantitatively, delayed-enhancement MR images of ischemic myocardium obtained with 0.1 mmol/kg gadobenate dimeglumine are comparable to those obtained with 0.2 mmol/kg gadopentetate dimeglumine 5, 10, and 20 minutes after contrast administration.

Image enhancements of Landsat 8 (OLI) and SAR data for preliminary landslide identification and mapping applied to the central region of Kenya

NASA Astrophysics Data System (ADS)

Mwaniki, M. W.; Kuria, D. N.; Boitt, M. K.; Ngigi, T. G.

2017-04-01

Image enhancements lead to improved performance and increased accuracy of feature extraction, recognition, identification, classification and hence change detection. This increases the utility of remote sensing to suit environmental applications and aid disaster monitoring of geohazards involving large areas. The main aim of this study was to compare the effect of image enhancement applied to synthetic aperture radar (SAR) data and Landsat 8 imagery in landslide identification and mapping. The methodology involved pre-processing Landsat 8 imagery, image co-registration, despeckling of the SAR data, after which Landsat 8 imagery was enhanced by Principal and Independent Component Analysis (PCA and ICA), a spectral index involving bands 7 and 4, and using a False Colour Composite (FCC) with the components bearing the most geologic information. The SAR data were processed using textural and edge filters, and computation of SAR incoherence. The enhanced spatial, textural and edge information from the SAR data was incorporated to the spectral information from Landsat 8 imagery during the knowledge based classification. The methodology was tested in the central highlands of Kenya, characterized by rugged terrain and frequent rainfall induced landslides. The results showed that the SAR data complemented Landsat 8 data which had enriched spectral information afforded by the FCC with enhanced geologic information. The SAR classification depicted landslides along the ridges and lineaments, important information lacking in the Landsat 8 image classification. The success of landslide identification and classification was attributed to the enhanced geologic features by spectral, textural and roughness properties.

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

Chen, L; Shen, C; Wang, J

Purpose: To reduce cone beam CT (CBCT) imaging dose, we previously proposed a progressive dose control (PDC) scheme to employ temporal correlation between CBCT images at different fractions for image quality enhancement. A temporal non-local means (TNLM) method was developed to enhance quality of a new low-dose CBCT using existing high-quality CBCT. To enhance a voxel value, the TNLM method searches for similar voxels in a window. Due to patient deformation among the two CBCTs, a large searching window was required, reducing image quality and computational efficiency. This abstract proposes a deformation-assisted TNLM (DA-TNLM) method to solve this problem. Methods:more » For a low-dose CBCT to be enhanced using a high-quality CBCT, we first performed deformable image registration between the low-dose CBCT and the high-quality CBCT to approximately establish voxel correspondence between the two. A searching window for a voxel was then set based on the deformation vector field. Specifically, the search window for each voxel was shifted by the deformation vector. A TNLM step was then applied using only voxels within this determined window to correct image intensity at the low-dose CBCT. Results: We have tested the proposed scheme on simulated CIRS phantom data and real patient data. The CITS phantom was scanned on Varian onboard imaging CBCT system with coach shifting and dose reducing for each time. The real patient data was acquired in four fractions with dose reduced from standard CBCT dose to 12.5% of standard dose. It was found that the DA-TNLM method can reduce total dose by over 75% on average in the first four fractions. Conclusion: We have developed a PDC scheme which can enhance the quality of image scanned at low dose using a DA-TNLM method. Tests in phantom and patient studies demonstrated promising results.« less

Resolution enhancement in a double-helix phase engineered scanning microscope (RESCH microscope) (Presentation Recording)

NASA Astrophysics Data System (ADS)

Jesacher, Alexander; Ritsch-Marte, Monika; Piestun, Rafael

2015-08-01

Recently we introduced RESCH microscopy [1] - a scanning microscope that allows slightly refocusing the sample after the acquisition has been performed, solely by performing appropriate data post-processing. The microscope features a double-helix phase-engineered emission point spread function in combination with camera-based detection. Based on the principle of transverse resolution enhancement in Image Scanning Microscopy [2,3], we demonstrate similar resolution improvement in RESCH. Furthermore, we outline a pathway for how the collected 3D sample information can be used to construct sharper optical sections. [1] A. Jesacher, M. Ritsch-Marte and R. Piestun, accepted for Optica. [2] C.J.R. Sheppard, "Super-resolution in Confocal imaging," Optik, 80, 53-54 (1988). [3] C.B. Müller and J. Enderlein "Image Scanning Microscopy," Phys. Rev. Lett. 104, 198101 (2010).

Detection of small surface defects using DCT based enhancement approach in machine vision systems

NASA Astrophysics Data System (ADS)

He, Fuqiang; Wang, Wen; Chen, Zichen

2005-12-01

Utilizing DCT based enhancement approach, an improved small defect detection algorithm for real-time leather surface inspection was developed. A two-stage decomposition procedure was proposed to extract an odd-odd frequency matrix after a digital image has been transformed to DCT domain. Then, the reverse cumulative sum algorithm was proposed to detect the transition points of the gentle curves plotted from the odd-odd frequency matrix. The best radius of the cutting sector was computed in terms of the transition points and the high-pass filtering operation was implemented. The filtered image was then inversed and transformed back to the spatial domain. Finally, the restored image was segmented by an entropy method and some defect features are calculated. Experimental results show the proposed small defect detection method can reach the small defect detection rate by 94%.

Accurate Image Analysis of the Retina Using Hessian Matrix and Binarisation of Thresholded Entropy with Application of Texture Mapping

PubMed Central

Yin, Xiaoxia; Ng, Brian W-H; He, Jing; Zhang, Yanchun; Abbott, Derek

2014-01-01

In this paper, we demonstrate a comprehensive method for segmenting the retinal vasculature in camera images of the fundus. This is of interest in the area of diagnostics for eye diseases that affect the blood vessels in the eye. In a departure from other state-of-the-art methods, vessels are first pre-grouped together with graph partitioning, using a spectral clustering technique based on morphological features. Local curvature is estimated over the whole image using eigenvalues of Hessian matrix in order to enhance the vessels, which appear as ridges in images of the retina. The result is combined with a binarized image, obtained using a threshold that maximizes entropy, to extract the retinal vessels from the background. Speckle type noise is reduced by applying a connectivity constraint on the extracted curvature based enhanced image. This constraint is varied over the image according to each region's predominant blood vessel size. The resultant image exhibits the central light reflex of retinal arteries and veins, which prevents the segmentation of whole vessels. To address this, the earlier entropy-based binarization technique is repeated on the original image, but crucially, with a different threshold to incorporate the central reflex vessels. The final segmentation is achieved by combining the segmented vessels with and without central light reflex. We carry out our approach on DRIVE and REVIEW, two publicly available collections of retinal images for research purposes. The obtained results are compared with state-of-the-art methods in the literature using metrics such as sensitivity (true positive rate), selectivity (false positive rate) and accuracy rates for the DRIVE images and measured vessel widths for the REVIEW images. Our approach out-performs the methods in the literature. PMID:24781033

EIT image regularization by a new Multi-Objective Simulated Annealing algorithm.

PubMed

Castro Martins, Thiago; Sales Guerra Tsuzuki, Marcos

2015-01-01

Multi-Objective Optimization can be used to produce regularized Electrical Impedance Tomography (EIT) images where the weight of the regularization term is not known a priori. This paper proposes a novel Multi-Objective Optimization algorithm based on Simulated Annealing tailored for EIT image reconstruction. Images are reconstructed from experimental data and compared with images from other Multi and Single Objective optimization methods. A significant performance enhancement from traditional techniques can be inferred from the results.

Novel medical image enhancement algorithms

NASA Astrophysics Data System (ADS)

Agaian, Sos; McClendon, Stephen A.

2010-01-01

In this paper, we present two novel medical image enhancement algorithms. The first, a global image enhancement algorithm, utilizes an alpha-trimmed mean filter as its backbone to sharpen images. The second algorithm uses a cascaded unsharp masking technique to separate the high frequency components of an image in order for them to be enhanced using a modified adaptive contrast enhancement algorithm. Experimental results from enhancing electron microscopy, radiological, CT scan and MRI scan images, using the MATLAB environment, are then compared to the original images as well as other enhancement methods, such as histogram equalization and two forms of adaptive contrast enhancement. An image processing scheme for electron microscopy images of Purkinje cells will also be implemented and utilized as a comparison tool to evaluate the performance of our algorithm.

Content Based Image Retrieval based on Wavelet Transform coefficients distribution

PubMed Central

Lamard, Mathieu; Cazuguel, Guy; Quellec, Gwénolé; Bekri, Lynda; Roux, Christian; Cochener, Béatrice

2007-01-01

In this paper we propose a content based image retrieval method for diagnosis aid in medical fields. We characterize images without extracting significant features by using distribution of coefficients obtained by building signatures from the distribution of wavelet transform. The research is carried out by computing signature distances between the query and database images. Several signatures are proposed; they use a model of wavelet coefficient distribution. To enhance results, a weighted distance between signatures is used and an adapted wavelet base is proposed. Retrieval efficiency is given for different databases including a diabetic retinopathy, a mammography and a face database. Results are promising: the retrieval efficiency is higher than 95% for some cases using an optimization process. PMID:18003013

Image Analysis via Fuzzy-Reasoning Approach: Prototype Applications at NASA

NASA Technical Reports Server (NTRS)

Dominguez, Jesus A.; Klinko, Steven J.

2004-01-01

A set of imaging techniques based on Fuzzy Reasoning (FR) approach was built for NASA at Kennedy Space Center (KSC) to perform complex real-time visual-related safety prototype tasks, such as detection and tracking of moving Foreign Objects Debris (FOD) during the NASA Space Shuttle liftoff and visual anomaly detection on slidewires used in the emergency egress system for Space Shuttle at the launch pad. The system has also proved its prospective in enhancing X-ray images used to screen hard-covered items leading to a better visualization. The system capability was used as well during the imaging analysis of the Space Shuttle Columbia accident. These FR-based imaging techniques include novel proprietary adaptive image segmentation, image edge extraction, and image enhancement. Probabilistic Neural Network (PNN) scheme available from NeuroShell(TM) Classifier and optimized via Genetic Algorithm (GA) was also used along with this set of novel imaging techniques to add powerful learning and image classification capabilities. Prototype applications built using these techniques have received NASA Space Awards, including a Board Action Award, and are currently being filed for patents by NASA; they are being offered for commercialization through the Research Triangle Institute (RTI), an internationally recognized corporation in scientific research and technology development. Companies from different fields, including security, medical, text digitalization, and aerospace, are currently in the process of licensing these technologies from NASA.

Enhanced Line Integral Convolution with Flow Feature Detection

NASA Technical Reports Server (NTRS)

Lane, David; Okada, Arthur

1996-01-01

The Line Integral Convolution (LIC) method, which blurs white noise textures along a vector field, is an effective way to visualize overall flow patterns in a 2D domain. The method produces a flow texture image based on the input velocity field defined in the domain. Because of the nature of the algorithm, the texture image tends to be blurry. This sometimes makes it difficult to identify boundaries where flow separation and reattachments occur. We present techniques to enhance LIC texture images and use colored texture images to highlight flow separation and reattachment boundaries. Our techniques have been applied to several flow fields defined in 3D curvilinear multi-block grids and scientists have found the results to be very useful.

Contrast enhancement in EIT imaging of the brain.

PubMed

Nissinen, A; Kaipio, J P; Vauhkonen, M; Kolehmainen, V

2016-01-01

We consider electrical impedance tomography (EIT) imaging of the brain. The brain is surrounded by the poorly conducting skull which has low conductivity compared to the brain. The skull layer causes a partial shielding effect which leads to weak sensitivity for the imaging of the brain tissue. In this paper we propose an approach based on the Bayesian approximation error approach, to enhance the contrast in brain imaging. With this approach, both the (uninteresting) geometry and the conductivity of the skull are embedded in the approximation error statistics, which leads to a computationally efficient algorithm that is able to detect features such as internal haemorrhage with significantly increased sensitivity and specificity. We evaluate the approach with simulations and phantom data.

Processing Digital Imagery to Enhance Perceptions of Realism

NASA Technical Reports Server (NTRS)

Woodell, Glenn A.; Jobson, Daniel J.; Rahman, Zia-ur

2003-01-01

Multi-scale retinex with color restoration (MSRCR) is a method of processing digital image data based on Edwin Land s retinex (retina + cortex) theory of human color vision. An outgrowth of basic scientific research and its application to NASA s remote-sensing mission, MSRCR is embodied in a general-purpose algorithm that greatly improves the perception of visual realism and the quantity and quality of perceived information in a digitized image. In addition, the MSRCR algorithm includes provisions for automatic corrections to accelerate and facilitate what could otherwise be a tedious image-editing process. The MSRCR algorithm has been, and is expected to continue to be, the basis for development of commercial image-enhancement software designed to extend and refine its capabilities for diverse applications.

Overhauser enhanced magnetic resonance imaging for tumor oximetry: Coregistration of tumor anatomy and tissue oxygen concentration

NASA Astrophysics Data System (ADS)

Krishna, Murali C.; English, Sean; Yamada, Kenichi; Yoo, John; Murugesan, Ramachandran; Devasahayam, Nallathamby; Cook, John A.; Golman, Klaes; Ardenkjaer-Larsen, Jan Henrik; Subramanian, Sankaran; Mitchell, James B.

2002-02-01

An efficient noninvasive method for in vivo imaging of tumor oxygenation by using a low-field magnetic resonance scanner and a paramagnetic contrast agent is described. The methodology is based on Overhauser enhanced magnetic resonance imaging (OMRI), a functional imaging technique. OMRI experiments were performed on tumor-bearing mice (squamous cell carcinoma) by i.v. administration of the contrast agent Oxo63 (a highly derivatized triarylmethyl radical) at nontoxic doses in the range of 2-7 mmol/kg either as a bolus or as a continuous infusion. Spatially resolved pO2 (oxygen concentration) images from OMRI experiments of tumor-bearing mice exhibited heterogeneous oxygenation profiles and revealed regions of hypoxia in tumors (<10 mmHg; 1 mmHg = 133 Pa). Oxygenation of tumors was enhanced on carbogen (95% O2/5% CO2) inhalation. The pO2 measurements from OMRI were found to be in agreement with those obtained by independent polarographic measurements using a pO2 Eppendorf electrode. This work illustrates that anatomically coregistered pO2 maps of tumors can be readily obtained by combining the good anatomical resolution of water proton-based MRI, and the superior pO2 sensitivity of EPR. OMRI affords the opportunity to perform noninvasive and repeated pO2 measurements of the same animal with useful spatial (≈1 mm) and temporal (2 min) resolution, making this method a powerful imaging modality for small animal research to understand tumor physiology and potentially for human applications.

Label-Free Molecular Imaging of Biological Cells and Tissues by Linear and Nonlinear Raman Spectroscopic Approaches.

PubMed

Krafft, Christoph; Schmitt, Michael; Schie, Iwan W; Cialla-May, Dana; Matthäus, Christian; Bocklitz, Thomas; Popp, Jürgen

2017-04-10

Raman spectroscopy is an emerging technique in bioanalysis and imaging of biomaterials owing to its unique capability of generating spectroscopic fingerprints. Imaging cells and tissues by Raman microspectroscopy represents a nondestructive and label-free approach. All components of cells or tissues contribute to the Raman signals, giving rise to complex spectral signatures. Resonance Raman scattering and surface-enhanced Raman scattering can be used to enhance the signals and reduce the spectral complexity. Raman-active labels can be introduced to increase specificity and multimodality. In addition, nonlinear coherent Raman scattering methods offer higher sensitivities, which enable the rapid imaging of larger sampling areas. Finally, fiber-based imaging techniques pave the way towards in vivo applications of Raman spectroscopy. This Review summarizes the basic principles behind medical Raman imaging and its progress since 2012. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

A depth enhancement strategy for kinect depth image

NASA Astrophysics Data System (ADS)

Quan, Wei; Li, Hua; Han, Cheng; Xue, Yaohong; Zhang, Chao; Hu, Hanping; Jiang, Zhengang

2018-03-01

Kinect is a motion sensing input device which is widely used in computer vision and other related fields. However, there are many inaccurate depth data in Kinect depth images even Kinect v2. In this paper, an algorithm is proposed to enhance Kinect v2 depth images. According to the principle of its depth measuring, the foreground and the background are considered separately. As to the background, the holes are filled according to the depth data in the neighborhood. And as to the foreground, a filling algorithm, based on the color image concerning about both space and color information, is proposed. An adaptive joint bilateral filtering method is used to reduce noise. Experimental results show that the processed depth images have clean background and clear edges. The results are better than ones of traditional Strategies. It can be applied in 3D reconstruction fields to pretreat depth image in real time and obtain accurate results.

Stochastic HKMDHE: A multi-objective contrast enhancement algorithm

NASA Astrophysics Data System (ADS)

Pratiher, Sawon; Mukhopadhyay, Sabyasachi; Maity, Srideep; Pradhan, Asima; Ghosh, Nirmalya; Panigrahi, Prasanta K.

2018-02-01

This contribution proposes a novel extension of the existing `Hyper Kurtosis based Modified Duo-Histogram Equalization' (HKMDHE) algorithm, for multi-objective contrast enhancement of biomedical images. A novel modified objective function has been formulated by joint optimization of the individual histogram equalization objectives. The optimal adequacy of the proposed methodology with respect to image quality metrics such as brightness preserving abilities, peak signal-to-noise ratio (PSNR), Structural Similarity Index (SSIM) and universal image quality metric has been experimentally validated. The performance analysis of the proposed Stochastic HKMDHE with existing histogram equalization methodologies like Global Histogram Equalization (GHE) and Contrast Limited Adaptive Histogram Equalization (CLAHE) has been given for comparative evaluation.

Fast estimate of Hartley entropy in image sharpening

NASA Astrophysics Data System (ADS)

Krbcová, Zuzana; Kukal, Jaromír.; Svihlik, Jan; Fliegel, Karel

2016-09-01

Two classes of linear IIR filters: Laplacian of Gaussian (LoG) and Difference of Gaussians (DoG) are frequently used as high pass filters for contextual vision and edge detection. They are also used for image sharpening when linearly combined with the original image. Resulting sharpening filters are radially symmetric in spatial and frequency domains. Our approach is based on the radial approximation of unknown optimal filter, which is designed as a weighted sum of Gaussian filters with various radii. The novel filter is designed for MRI image enhancement where the image intensity represents anatomical structure plus additive noise. We prefer the gradient norm of Hartley entropy of whole image intensity as a measure which has to be maximized for the best sharpening. The entropy estimation procedure is as fast as FFT included in the filter but this estimate is a continuous function of enhanced image intensities. Physically motivated heuristic is used for optimum sharpening filter design by its parameter tuning. Our approach is compared with Wiener filter on MRI images.

Enhanced encrypted reversible data hiding algorithm with minimum distortion through homomorphic encryption

NASA Astrophysics Data System (ADS)

Bhardwaj, Rupali

2018-03-01

Reversible data hiding means embedding a secret message in a cover image in such a manner, to the point that in the midst of extraction of the secret message, the cover image and, furthermore, the secret message are recovered with no error. The goal of by far most of the reversible data hiding algorithms is to have improved the embedding rate and enhanced visual quality of stego image. An improved encrypted-domain-based reversible data hiding algorithm to embed two binary bits in each gray pixel of original cover image with minimum distortion of stego-pixels is employed in this paper. Highlights of the proposed algorithm are minimum distortion of pixel's value, elimination of underflow and overflow problem, and equivalence of stego image and cover image with a PSNR of ∞ (for Lena, Goldhill, and Barbara image). The experimental outcomes reveal that in terms of average PSNR and embedding rate, for natural images, the proposed algorithm performed better than other conventional ones.

Contrast-enhanced intravascular ultrasound pulse sequences for bandwidth-limited transducers.

PubMed

Maresca, David; Renaud, Guillaume; van Soest, Gijs; Li, Xiang; Zhou, Qifa; Shung, K Kirk; de Jong, Nico; van der Steen, Antonius F W

2013-04-01

We demonstrate two methods for vasa vasorum imaging using contrast-enhanced intravascular ultrasound, which can be performed using commercial catheters. Plaque neovascularization was recognized as an independent marker of coronary artery plaque vulnerability. IVUS-based methods to image the microvessels available to date require high bandwidth (-6 dB relative frequency bandwidth >70%), which are not routinely available commercially. We explored the potential of ultraharmonic imaging and chirp reversal imaging for vasa vasorum imaging. In vitro recordings were performed on a tissue-mimicking phantom using a commercial ultrasound contrast agent and a transducer with a center frequency of 34 MHz and a -6 dB relative bandwidth of 56%. Acoustic peak pressures <500 kPa were used. A tissue-mimicking phantom with channels down to 200 μm in diameter was successfully imaged by the two contrast detection sequences while the smallest channel stayed invisible in conventional intravascular ultrasound images. Ultraharmonic imaging provided the best contrast agent detection. Copyright © 2013 World Federation for Ultrasound in Medicine & Biology. All rights reserved.

Adaptive enhancement for nonuniform illumination images via nonlinear mapping

NASA Astrophysics Data System (ADS)

Wang, Yanfang; Huang, Qian; Hu, Jing

2017-09-01

Nonuniform illumination images suffer from degenerated details because of underexposure, overexposure, or a combination of both. To improve the visual quality of color images, underexposure regions should be lightened, whereas overexposure areas need to be dimmed properly. However, discriminating between underexposure and overexposure is troublesome. Compared with traditional methods that produce a fixed demarcation value throughout an image, the proposed demarcation changes as local luminance varies, thus is suitable for manipulating complicated illumination. Based on this locally adaptive demarcation, a nonlinear modification is applied to image luminance. Further, with the modified luminance, we propose a nonlinear process to reconstruct a luminance-enhanced color image. For every pixel, this nonlinear process takes the luminance change and the original chromaticity into account, thus trying to avoid exaggerated colors at dark areas and depressed colors at highly bright regions. Finally, to improve image contrast, a local and image-dependent exponential technique is designed and applied to the RGB channels of the obtained color image. Experimental results demonstrate that our method produces good contrast and vivid color for both nonuniform illumination images and images with normal illumination.

Dendrimer probes for enhanced photostability and localization in fluorescence imaging.

PubMed

Kim, Younghoon; Kim, Sung Hoon; Tanyeri, Melikhan; Katzenellenbogen, John A; Schroeder, Charles M

2013-04-02

Recent advances in fluorescence microscopy have enabled high-resolution imaging and tracking of single proteins and biomolecules in cells. To achieve high spatial resolutions in the nanometer range, bright and photostable fluorescent probes are critically required. From this view, there is a strong need for development of advanced fluorescent probes with molecular-scale dimensions for fluorescence imaging. Polymer-based dendrimer nanoconjugates hold strong potential to serve as versatile fluorescent probes due to an intrinsic capacity for tailored spectral properties such as brightness and emission wavelength. In this work, we report a new, to our knowledge, class of molecular probes based on dye-conjugated dendrimers for fluorescence imaging and single-molecule fluorescence microscopy. We engineered fluorescent dendritic nanoprobes (FDNs) to contain multiple organic dyes and reactive groups for target-specific biomolecule labeling. The photophysical properties of dye-conjugated FDNs (Cy5-FDNs and Cy3-FDNs) were characterized using single-molecule fluorescence microscopy, which revealed greatly enhanced photostability, increased probe brightness, and improved localization precision in high-resolution fluorescence imaging compared to single organic dyes. As proof-of-principle demonstration, Cy5-FDNs were used to assay single-molecule nucleic acid hybridization and for immunofluorescence imaging of microtubules in cytoskeletal networks. In addition, Cy5-FDNs were used as reporter probes in a single-molecule protein pull-down assay to characterize antibody binding and target protein capture. In all cases, the photophysical properties of FDNs resulted in enhanced fluorescence imaging via improved brightness and/or photostability. Copyright © 2013 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Optimization of a double inversion recovery sequence for noninvasive synovium imaging of joint effusion in the knee.

PubMed

Jahng, Geon-Ho; Jin, Wook; Yang, Dal Mo; Ryu, Kyung Nam

2011-05-01

We wanted to optimize a double inversion recovery (DIR) sequence to image joint effusion regions of the knee, especially intracapsular or intrasynovial imaging in the suprapatellar bursa and patellofemoral joint space. Computer simulations were performed to determine the optimum inversion times (TI) for suppressing both fat and water signals, and a DIR sequence was optimized based on the simulations for distinguishing synovitis from fluid. In vivo studies were also performed on individuals who showed joint effusion on routine knee MR images to demonstrate the feasibility of using the DIR sequence with a 3T whole-body MR scanner. To compare intracapsular or intrasynovial signals on the DIR images, intermediate density-weighted images and/or post-enhanced T1-weighted images were acquired. The timings to enhance the synovial contrast from the fluid components were TI1 = 2830 ms and TI2 = 254 ms for suppressing the water and fat signals, respectively. Improved contrast for the intrasynovial area in the knees was observed with the DIR turbo spin-echo pulse sequence compared to the intermediate density-weighted sequence. Imaging contrast obtained noninvasively with the DIR sequence was similar to that of the post-enhanced T1-weighted sequence. The DIR sequence may be useful for delineating synovium without using contrast materials.

Characteristic CT and MR imaging findings of cerebral paragonimiasis.

PubMed

Xia, Yong; Chen, Jing; Ju, Yan; You, Chao

2016-06-01

The early diagnosis of cerebral paragonimiasis (CP) is essential for a good prognosis. We seek to provide references for early diagnosis by analyzing the imaging characteristics of cerebral paragonimiasis. Images of 27 patients with CP (22 males and 5 females; median age 20.3 years; range: 4 to 47 years) were retrospectively evaluated. All patients underwent head computed tomography (CT) scans; 22 patients underwent conventional magnetic resonance imaging (MRI) sequences, including contrast-enhanced MRI for 20 patients and diffusion-weighted-imaging (DWI) for 1 patient. The diagnosis was confirmed based on a positive antibody test using enzyme-linked immunosorbent assay (ELISA) for paragonimiasis in the serum. The most common imaging findings of CP were isodense or hypodense lesions combined with extensive hypodense areas of perilesional edema on CT scans and a large mass composed of multiple ring-shaped lesions with surrounding edema on MRI images. The conglomeration of multiple ring-shaped lesions (n=11 patients), "tunnel signs" (n=12 patients) and worm-eaten signs (n=5 patients) were characteristic of most CP images. In 14 patients, contrast-enhanced MRI showed varying degrees of contrast enhancement combined with adjacent meningeal enhancement (n=10). A large mass comprising multiple ring-shaped lesions of different sizes, "tunnel signs" and worm-eaten signs with surrounding edema are the most characteristic features of CP. Extensive invasions of the adjacent meninges and ventricular wall (19 patients), multiple intracerebral lesions, bilateral hemispheric involvement, and lesion migration are other noteworthy imaging characteristics. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Enhanced Automated Guidance System for Horizontal Auger Boring Based on Image Processing

PubMed Central

Wu, Lingling; Wen, Guojun; Wang, Yudan; Huang, Lei; Zhou, Jiang

2018-01-01

Horizontal auger boring (HAB) is a widely used trenchless technology for the high-accuracy installation of gravity or pressure pipelines on line and grade. Differing from other pipeline installations, HAB requires a more precise and automated guidance system for use in a practical project. This paper proposes an economic and enhanced automated optical guidance system, based on optimization research of light-emitting diode (LED) light target and five automated image processing bore-path deviation algorithms. An LED target was optimized for many qualities, including light color, filter plate color, luminous intensity, and LED layout. The image preprocessing algorithm, feature extraction algorithm, angle measurement algorithm, deflection detection algorithm, and auto-focus algorithm, compiled in MATLAB, are used to automate image processing for deflection computing and judging. After multiple indoor experiments, this guidance system is applied in a project of hot water pipeline installation, with accuracy controlled within 2 mm in 48-m distance, providing accurate line and grade controls and verifying the feasibility and reliability of the guidance system. PMID:29462855

Super-resolution of fluorescence-free plasmonic nanoparticles using enhanced dark-field illumination based on wavelength-modulation

DOE PAGES

Zhang, Peng; Lee, Seungah; Yu, Hyunung; ...

2015-06-15

Super-resolution imaging of fluorescence-free plasmonic nanoparticles (NPs) was achieved using enhanced dark-field (EDF) illumination based on wavelength-modulation. Indistinguishable adjacent EDF images of 103-nm gold nanoparticles (GNPs), 40-nm gold nanorods (GNRs), and 80-nm silver nanoparticles (SNPs) were modulated at their wavelengths of specific localized surface plasmon scattering. The coordinates (x, y) of each NP were resolved by fitting their point spread functions with a two-dimensional Gaussian. The measured localization precisions of GNPs, GNRs, and SNPs were 2.5 nm, 5.0 nm, and 2.9 nm, respectively. From the resolved coordinates of NPs and the corresponding localization precisions, super-resolution images were reconstructed. Depending onmore » the spontaneous polarization of GNR scattering, the orientation angle of GNRs in two-dimensions was resolved and provided more elaborate localization information. This novel fluorescence-free super-resolution method was applied to live HeLa cells to resolve NPs and provided remarkable subdiffraction limit images.« less

Enhanced Automated Guidance System for Horizontal Auger Boring Based on Image Processing.

PubMed

Wu, Lingling; Wen, Guojun; Wang, Yudan; Huang, Lei; Zhou, Jiang

2018-02-15

Horizontal auger boring (HAB) is a widely used trenchless technology for the high-accuracy installation of gravity or pressure pipelines on line and grade. Differing from other pipeline installations, HAB requires a more precise and automated guidance system for use in a practical project. This paper proposes an economic and enhanced automated optical guidance system, based on optimization research of light-emitting diode (LED) light target and five automated image processing bore-path deviation algorithms. An LED light target was optimized for many qualities, including light color, filter plate color, luminous intensity, and LED layout. The image preprocessing algorithm, direction location algorithm, angle measurement algorithm, deflection detection algorithm, and auto-focus algorithm, compiled in MATLAB, are used to automate image processing for deflection computing and judging. After multiple indoor experiments, this guidance system is applied in a project of hot water pipeline installation, with accuracy controlled within 2 mm in 48-m distance, providing accurate line and grade controls and verifying the feasibility and reliability of the guidance system.

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.

Methods in quantitative image analysis.

PubMed

Oberholzer, M; Ostreicher, M; Christen, H; Brühlmann, M

1996-05-01

The main steps of image analysis are image capturing, image storage (compression), correcting imaging defects (e.g. non-uniform illumination, electronic-noise, glare effect), image enhancement, segmentation of objects in the image and image measurements. Digitisation is made by a camera. The most modern types include a frame-grabber, converting the analog-to-digital signal into digital (numerical) information. The numerical information consists of the grey values describing the brightness of every point within the image, named a pixel. The information is stored in bits. Eight bits are summarised in one byte. Therefore, grey values can have a value between 0 and 256 (2(8)). The human eye seems to be quite content with a display of 5-bit images (corresponding to 64 different grey values). In a digitised image, the pixel grey values can vary within regions that are uniform in the original scene: the image is noisy. The noise is mainly manifested in the background of the image. For an optimal discrimination between different objects or features in an image, uniformity of illumination in the whole image is required. These defects can be minimised by shading correction [subtraction of a background (white) image from the original image, pixel per pixel, or division of the original image by the background image]. The brightness of an image represented by its grey values can be analysed for every single pixel or for a group of pixels. The most frequently used pixel-based image descriptors are optical density, integrated optical density, the histogram of the grey values, mean grey value and entropy. The distribution of the grey values existing within an image is one of the most important characteristics of the image. However, the histogram gives no information about the texture of the image. The simplest way to improve the contrast of an image is to expand the brightness scale by spreading the histogram out to the full available range. Rules for transforming the grey value histogram of an existing image (input image) into a new grey value histogram (output image) are most quickly handled by a look-up table (LUT). The histogram of an image can be influenced by gain, offset and gamma of the camera. Gain defines the voltage range, offset defines the reference voltage and gamma the slope of the regression line between the light intensity and the voltage of the camera. A very important descriptor of neighbourhood relations in an image is the co-occurrence matrix. The distance between the pixels (original pixel and its neighbouring pixel) can influence the various parameters calculated from the co-occurrence matrix. The main goals of image enhancement are elimination of surface roughness in an image (smoothing), correction of defects (e.g. noise), extraction of edges, identification of points, strengthening texture elements and improving contrast. In enhancement, two types of operations can be distinguished: pixel-based (point operations) and neighbourhood-based (matrix operations). The most important pixel-based operations are linear stretching of grey values, application of pre-stored LUTs and histogram equalisation. The neighbourhood-based operations work with so-called filters. These are organising elements with an original or initial point in their centre. Filters can be used to accentuate or to suppress specific structures within the image. Filters can work either in the spatial or in the frequency domain. The method used for analysing alterations of grey value intensities in the frequency domain is the Hartley transform. Filter operations in the spatial domain can be based on averaging or ranking the grey values occurring in the organising element. The most important filters, which are usually applied, are the Gaussian filter and the Laplace filter (both averaging filters), and the median filter, the top hat filter and the range operator (all ranking filters). Segmentation of objects is traditionally based on threshold grey values. (AB

Lung dynamic MRI deblurring using low-rank decomposition and dictionary learning.

PubMed

Gou, Shuiping; Wang, Yueyue; Wu, Jiaolong; Lee, Percy; Sheng, Ke

2015-04-01

Lung dynamic MRI (dMRI) has emerged to be an appealing tool to quantify lung motion for both planning and treatment guidance purposes. However, this modality can result in blurry images due to intrinsically low signal-to-noise ratio in the lung and spatial/temporal interpolation. The image blurring could adversely affect the image processing that depends on the availability of fine landmarks. The purpose of this study is to reduce dMRI blurring using image postprocessing. To enhance the image quality and exploit the spatiotemporal continuity of dMRI sequences, a low-rank decomposition and dictionary learning (LDDL) method was employed to deblur lung dMRI and enhance the conspicuity of lung blood vessels. Fifty frames of continuous 2D coronal dMRI frames using a steady state free precession sequence were obtained from five subjects including two healthy volunteer and three lung cancer patients. In LDDL, the lung dMRI was decomposed into sparse and low-rank components. Dictionary learning was employed to estimate the blurring kernel based on the whole image, low-rank or sparse component of the first image in the lung MRI sequence. Deblurring was performed on the whole image sequences using deconvolution based on the estimated blur kernel. The deblurring results were quantified using an automated blood vessel extraction method based on the classification of Hessian matrix filtered images. Accuracy of automated extraction was calculated using manual segmentation of the blood vessels as the ground truth. In the pilot study, LDDL based on the blurring kernel estimated from the sparse component led to performance superior to the other ways of kernel estimation. LDDL consistently improved image contrast and fine feature conspicuity of the original MRI without introducing artifacts. The accuracy of automated blood vessel extraction was on average increased by 16% using manual segmentation as the ground truth. Image blurring in dMRI images can be effectively reduced using a low-rank decomposition and dictionary learning method using kernels estimated by the sparse component.

Beyond Frangi: an improved multiscale vesselness filter

NASA Astrophysics Data System (ADS)

Jerman, Tim; Pernuš, Franjo; Likar, Boštjan; Špiclin, Žiga

2015-03-01

Vascular diseases are among the top three causes of death in the developed countries. Effective diagnosis of vascular pathologies from angiographic images is therefore very important and usually relies on segmentation and visualization of vascular structures. To enhance the vascular structures prior to their segmentation and visualization, and to suppress non-vascular structures and image noise, the filters enhancing vascular structures are used extensively. Even though several enhancement filters are widely used, the responses of these filters are typically not uniform between vessels of different radii and, compared to the response in the central part of vessels, their response is lower at vessels' edges and bifurcations, and vascular pathologies like aneurysm. In this paper, we propose a novel enhancement filter based on ratio of multiscale Hessian eigenvalues, which yields a close-to-uniform response in all vascular structures and accurately enhances the border between the vascular structures and the background. The proposed and four state-of-the-art enhancement filters were evaluated and compared on a 3D synthetic image containing tubular structures and a clinical dataset of 15 cerebral 3D digitally subtracted angiograms with manual expert segmentations. The evaluation was based on quantitative metrics of segmentation performance, computed as area under the precision-recall curve, signal-to-noise ratio of the vessel enhancement and the response uniformity within vascular structures. The proposed filter achieved the best scores in all three metrics and thus has a high potential to further improve the performance of existing or encourage the development of more advanced methods for segmentation and visualization of vascular structures.

Gadolinium chloride as a contrast agent for imaging wood composite components by magnetic resonance

Treesearch

Thomas L. Eberhardt; Chi-Leung So; Andrea Protti; Po-Wah So

2009-01-01

Although paramagnetic contrast agents have an established track record in medical uses of magnetic resonance imaging (MRI), only recently has a contrast agent been used for enhancing MRI images of solid wood specimens. Expanding on this concept, wood veneers were treated with a gadolinium-based contrast agent and used in a model system comprising three-ply plywood...

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

Computers are stepping stones to improved imaging.

PubMed

Freiherr, G

1991-02-01

Never before has the radiology industry embraced the computer with such enthusiasm. Graphics supercomputers as well as UNIX- and RISC-based computing platforms are turning up in every digital imaging modality and especially in systems designed to enhance and transmit images, says author Greg Freiherr on assignment for Computers in Healthcare at the Radiological Society of North America conference in Chicago.

Combining image-processing and image compression schemes

NASA Technical Reports Server (NTRS)

Greenspan, H.; Lee, M.-C.

1995-01-01

An investigation into the combining of image-processing schemes, specifically an image enhancement scheme, with existing compression schemes is discussed. Results are presented on the pyramid coding scheme, the subband coding scheme, and progressive transmission. Encouraging results are demonstrated for the combination of image enhancement and pyramid image coding schemes, especially at low bit rates. Adding the enhancement scheme to progressive image transmission allows enhanced visual perception at low resolutions. In addition, further progressing of the transmitted images, such as edge detection schemes, can gain from the added image resolution via the enhancement.

Optical tomography of fluorophores in dense scattering media based on ultrasound-enhanced chemiluminescence

NASA Astrophysics Data System (ADS)

Kobayashi, Masaki; Kikuchi, Naoto; Sato, Akihiro

2015-01-01

This letter proposes and demonstrates ultrasound-combined optical imaging in dense scattering media. A peroxyoxalate chemiluminescence system that includes fluorophores to chemically excite the pigment is stimulated by ultrasound irradiation with power of less than 0.14 W/cm2. Using focused ultrasound, the chemiluminescence is selectively spatially enhanced, which leads to imaging of the pigment when embedded in a light-scattering medium via scanning of the focal point. The ultrasonically enhanced intensity of the chemiluminescence depends on the base intensity of the chemiluminescence without the applied ultrasound irradiation, which thereby enables quantitative determination of the fluorophore concentration. The authors demonstrate the potential of this method to resolve chemiluminescent targets in a dense scattering medium that is comparable to biological tissue. An image was acquired of a chemiluminescent target that included indocyanine green as the fluorophore embedded at a depth of 20 mm in an Intralipid-10% 200 ml/l solution scattering medium (the reduced scattering coefficient was estimated to be approximately 1.3 mm-1), indicating the potential for expansion of this technique for use in biological applications.

Color edges extraction using statistical features and automatic threshold technique: application to the breast cancer cells.

PubMed

Ben Chaabane, Salim; Fnaiech, Farhat

2014-01-23

Color image segmentation has been so far applied in many areas; hence, recently many different techniques have been developed and proposed. In the medical imaging area, the image segmentation may be helpful to provide assistance to doctor in order to follow-up the disease of a certain patient from the breast cancer processed images. The main objective of this work is to rebuild and also to enhance each cell from the three component images provided by an input image. Indeed, from an initial segmentation obtained using the statistical features and histogram threshold techniques, the resulting segmentation may represent accurately the non complete and pasted cells and enhance them. This allows real help to doctors, and consequently, these cells become clear and easy to be counted. A novel method for color edges extraction based on statistical features and automatic threshold is presented. The traditional edge detector, based on the first and the second order neighborhood, describing the relationship between the current pixel and its neighbors, is extended to the statistical domain. Hence, color edges in an image are obtained by combining the statistical features and the automatic threshold techniques. Finally, on the obtained color edges with specific primitive color, a combination rule is used to integrate the edge results over the three color components. Breast cancer cell images were used to evaluate the performance of the proposed method both quantitatively and qualitatively. Hence, a visual and a numerical assessment based on the probability of correct classification (PC), the false classification (Pf), and the classification accuracy (Sens(%)) are presented and compared with existing techniques. The proposed method shows its superiority in the detection of points which really belong to the cells, and also the facility of counting the number of the processed cells. Computer simulations highlight that the proposed method substantially enhances the segmented image with smaller error rates better than other existing algorithms under the same settings (patterns and parameters). Moreover, it provides high classification accuracy, reaching the rate of 97.94%. Additionally, the segmentation method may be extended to other medical imaging types having similar properties.

Adaptive gamma correction-based expert system for nonuniform illumination face enhancement

NASA Astrophysics Data System (ADS)

Abdelhamid, Iratni; Mustapha, Aouache; Adel, Oulefki

2018-03-01

The image quality of a face recognition system suffers under severe lighting conditions. Thus, this study aims to develop an approach for nonuniform illumination adjustment based on an adaptive gamma correction (AdaptGC) filter that can solve the aforementioned issue. An approach for adaptive gain factor prediction was developed via neural network model-based cross-validation (NN-CV). To achieve this objective, a gamma correction function and its effects on the face image quality with different gain values were examined first. Second, an orientation histogram (OH) algorithm was assessed as a face's feature descriptor. Subsequently, a density histogram module was developed for face label generation. During the NN-CV construction, the model was assessed to recognize the OH descriptor and predict the face label. The performance of the NN-CV model was evaluated by examining the statistical measures of root mean square error and coefficient of efficiency. Third, to evaluate the AdaptGC enhancement approach, an image quality metric was adopted using enhancement by entropy, contrast per pixel, second-derivative-like measure of enhancement, and sharpness, then supported by visual inspection. The experiment results were examined using five face's databases, namely, extended Yale-B, Carnegie Mellon University-Pose, Illumination, and Expression, Mobio, FERET, and Oulu-CASIA-NIR-VIS. The final results prove that AdaptGC filter implementation compared with state-of-the-art methods is the best choice in terms of contrast and nonuniform illumination adjustment. In summary, the benefits attained prove that AdaptGC is driven by a profitable enhancement rate, which provides satisfying features for high rate face recognition systems.

Motion Estimation Utilizing Range Detection-Enhanced Visual Odometry

NASA Technical Reports Server (NTRS)

Morris, Daniel Dale (Inventor); Chang, Hong (Inventor); Friend, Paul Russell (Inventor); Chen, Qi (Inventor); Graf, Jodi Seaborn (Inventor)

2016-01-01

A motion determination system is disclosed. The system may receive a first and a second camera image from a camera, the first camera image received earlier than the second camera image. The system may identify corresponding features in the first and second camera images. The system may receive range data comprising at least one of a first and a second range data from a range detection unit, corresponding to the first and second camera images, respectively. The system may determine first positions and the second positions of the corresponding features using the first camera image and the second camera image. The first positions or the second positions may be determined by also using the range data. The system may determine a change in position of the machine based on differences between the first and second positions, and a VO-based velocity of the machine based on the determined change in position.

Raster Scan Computer Image Generation (CIG) System Based On Refresh Memory

NASA Astrophysics Data System (ADS)

Dichter, W.; Doris, K.; Conkling, C.

1982-06-01

A full color, Computer Image Generation (CIG) raster visual system has been developed which provides a high level of training sophistication by utilizing advanced semiconductor technology and innovative hardware and firmware techniques. Double buffered refresh memory and efficient algorithms eliminate the problem of conventional raster line ordering by allowing the generated image to be stored in a random fashion. Modular design techniques and simplified architecture provide significant advantages in reduced system cost, standardization of parts, and high reliability. The major system components are a general purpose computer to perform interfacing and data base functions; a geometric processor to define the instantaneous scene image; a display generator to convert the image to a video signal; an illumination control unit which provides final image processing; and a CRT monitor for display of the completed image. Additional optional enhancements include texture generators, increased edge and occultation capability, curved surface shading, and data base extensions.

Correction of motion artifacts in endoscopic optical coherence tomography and autofluorescence images based on azimuthal en face image registration.

PubMed

Abouei, Elham; Lee, Anthony M D; Pahlevaninezhad, Hamid; Hohert, Geoffrey; Cua, Michelle; Lane, Pierre; Lam, Stephen; MacAulay, Calum

2018-01-01

We present a method for the correction of motion artifacts present in two- and three-dimensional in vivo endoscopic images produced by rotary-pullback catheters. This method can correct for cardiac/breathing-based motion artifacts and catheter-based motion artifacts such as nonuniform rotational distortion (NURD). This method assumes that en face tissue imaging contains slowly varying structures that are roughly parallel to the pullback axis. The method reduces motion artifacts using a dynamic time warping solution through a cost matrix that measures similarities between adjacent frames in en face images. We optimize and demonstrate the suitability of this method using a real and simulated NURD phantom and in vivo endoscopic pulmonary optical coherence tomography and autofluorescence images. Qualitative and quantitative evaluations of the method show an enhancement of the image quality. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Fast Acquisition and Reconstruction of Optical Coherence Tomography Images via Sparse Representation

PubMed Central

Li, Shutao; McNabb, Ryan P.; Nie, Qing; Kuo, Anthony N.; Toth, Cynthia A.; Izatt, Joseph A.; Farsiu, Sina

2014-01-01

In this paper, we present a novel technique, based on compressive sensing principles, for reconstruction and enhancement of multi-dimensional image data. Our method is a major improvement and generalization of the multi-scale sparsity based tomographic denoising (MSBTD) algorithm we recently introduced for reducing speckle noise. Our new technique exhibits several advantages over MSBTD, including its capability to simultaneously reduce noise and interpolate missing data. Unlike MSBTD, our new method does not require an a priori high-quality image from the target imaging subject and thus offers the potential to shorten clinical imaging sessions. This novel image restoration method, which we termed sparsity based simultaneous denoising and interpolation (SBSDI), utilizes sparse representation dictionaries constructed from previously collected datasets. We tested the SBSDI algorithm on retinal spectral domain optical coherence tomography images captured in the clinic. Experiments showed that the SBSDI algorithm qualitatively and quantitatively outperforms other state-of-the-art methods. PMID:23846467

A Novel Defect Inspection Method for Semiconductor Wafer Based on Magneto-Optic Imaging

NASA Astrophysics Data System (ADS)

Pan, Z.; Chen, L.; Li, W.; Zhang, G.; Wu, P.

2013-03-01

The defects of semiconductor wafer may be generated from the manufacturing processes. A novel defect inspection method of semiconductor wafer is presented in this paper. The method is based on magneto-optic imaging, which involves inducing eddy current into the wafer under test, and detecting the magnetic flux associated with eddy current distribution in the wafer by exploiting the Faraday rotation effect. The magneto-optic image being generated may contain some noises that degrade the overall image quality, therefore, in this paper, in order to remove the unwanted noise present in the magneto-optic image, the image enhancement approach using multi-scale wavelet is presented, and the image segmentation approach based on the integration of watershed algorithm and clustering strategy is given. The experimental results show that many types of defects in wafer such as hole and scratch etc. can be detected by the method proposed in this paper.

Multiple image encryption scheme based on pixel exchange operation and vector decomposition

NASA Astrophysics Data System (ADS)

Xiong, Y.; Quan, C.; Tay, C. J.

2018-02-01

We propose a new multiple image encryption scheme based on a pixel exchange operation and a basic vector decomposition in Fourier domain. In this algorithm, original images are imported via a pixel exchange operator, from which scrambled images and pixel position matrices are obtained. Scrambled images encrypted into phase information are imported using the proposed algorithm and phase keys are obtained from the difference between scrambled images and synthesized vectors in a charge-coupled device (CCD) plane. The final synthesized vector is used as an input in a random phase encoding (DRPE) scheme. In the proposed encryption scheme, pixel position matrices and phase keys serve as additional private keys to enhance the security of the cryptosystem which is based on a 4-f system. Numerical simulations are presented to demonstrate the feasibility and robustness of the proposed encryption scheme.

[Current practice in MR imaging of the liver].

PubMed

Kanematsu, M; Kondo, H; Matsuo, M; Hoshi, H

2001-12-01

MR imaging, which is able to evaluate T1- and T2-relaxation time, fat, hemorrhage, metal deposition, blood flow, perfusion, diffusion, and so on, has offered more information for the diagnosis of diffuse and focal hepatic diseases than CT. The spoiled-GRE sequence with high contrast resolution and ease of the aimed contrast capture derived from the k-space property, with the use of a phased-array multicoil, have remarkably increased the value of gadolinium-enhanced dynamic MR diagnosis of the liver. In recent years, the clinical use of ferumoxide has begun, and issues concerning the superiority or inferiority and combination of contrast media are being debated. This paper describes the value, role, and clinical practice of unenhanced, gadolinium-enhanced, and ferumoxide-enhanced MR imaging of the liver based on knowledge obtained in our institution, with some reference to the literature.

GADOLINIUM(Gd)-BASED and Ion Oxide Nanoparticle Contrast Agents for Pre-Clinical and Clinical Magnetic Resonance Imaging (mri) Research

NASA Astrophysics Data System (ADS)

Ng, Thian C.

2012-06-01

It is known that one strength of MRI is its excellent soft tissue discrimination. It naturally provides sufficient contrast between the structural differences of normal and pathological tissues, their spatial extent and progression. However, to further extend its applications and enhance even more contrast for clinical studies, various Gadolinium (Gd)-based contrast agents have been developed for different organs (brain strokes, cancer, cardio-MRI, etc). These Gd-based contrast agents are paramagnetic compounds that have strong T1-effect for enhancing the contrast between tissue types. Gd-contrast can also enhance magnetic resonance angiography (CE-MRA) for studying stenosis and for measuring perfusion, vascular susceptibility, interstitial space, etc. Another class of contrast agents makes use of ferrite iron oxide nanoparticles (including Superparamagnetic Ion Oxide (SPIO) and Ultrasmall Superparamagnetic Iron Oxide (USPIO)). These nanoparticles have superior magnetic susceptibility effect and produce a drop in signal, namely in T2*-weighted images, useful for the determination of lymph nodes metastases, angiogenesis and arteriosclerosis plaques.

Comparison of Skylab and LANDSAT images for geologic mapping in Northern Arizona. [Shivwits Plateau, Verde Valley, Coconino Plateau, and Red Lake in Arizona

NASA Technical Reports Server (NTRS)

Goetz, A. F. H. (Principal Investigator); Abrams, M. J.; Gillespie, A. R.; Siegal, B. S.; Elston, D. P.; Lucchitta, I.; Wu, S. S. C.; Sanchez, A.; Dipaola, W. D.; Schafer, F. J.

1976-01-01

The author has identified the following significant results. It was found that based on resolution, the Skylab S190A products were superior to LANDSAT images. Based on measurements of shoreline features in Lake Mead S190A images had 1.5 - 3 times greater resolution than LANDSAT. In general, the higher resolution of the Skylab data yielded better discrimination among rock units, but in the case of structural features, lower sun angle LANDSAT images (50 deg) were superior to higher sun angle Skylab images (77 deg). The most valuable advantage of the Skylab over the LANDSAT image products is the capability of producing stereo images. Field spectral reflectance measurements on the Coconino Plateau were made in an effort to determine the best spectral band for discrimination of the six geologic units in question, and these bands were 1.3, 1.2, 1.0, and 0.5 microns. The EREP multispectral scanner yielded data with a low signal to noise ratio which limited its usefulness for image enhancement work. Sites that were studied in Arizona were Shivwits Plateau, Verde Valley, Coconino Plateau, and Red Lake. Thematic maps produced by the three classification algorithms analyzed were not as accurate as the maps produced by photointerpretation of composites of enhanced images.

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.

A novel method for real-time edge-enhancement and its application to pattern recognition

NASA Astrophysics Data System (ADS)

Ge, Huayong; Bai, Enjian; Fan, Hong

2010-11-01

The coupling gain coefficient g is redefined and deduced based on coupling theory, the variant of coupling gain coefficient g for different ΓL and r is analyzed. A new optical system is proposed for image edge-enhancement. It recycles the back signal to amplify the edge signal, which has the advantages of high throughput efficiency and brightness. The optical system is designed and built, and the edge-enhanced image of hand bone is captured electronically by CCD camera. The principle of optical correlation is demonstrated, 3-D correlation distribution of letter H with and without edge-enhancement is simulated, the discrimination capability Iac and the full-width at half maximum intensity (FWHM) are compared for two kinds of correlators. The analysis shows that edge-enhancement preprocessing can improve the performance of correlator effectively.

A Novel 24 Ghz One-Shot Rapid and Portable Microwave Imaging System (Camera)

NASA Technical Reports Server (NTRS)

Ghasr, M.T.; Abou-Khousa, M.A.; Kharkovsky, S.; Zoughi, R.; Pommerenke, D.

2008-01-01

A novel 2D microwave imaging system at 24 GHz based on MST techniques. Enhanced sensitivity and SNR by utilizing PIN diode-loaded resonant slots. Specific slot and array design to increase transmission and reduce cross -coupling. Real-time imaging at a rate in excess of 30 images per second. Reflection as well transmission mode capabilities. Utility and application for electric field distribution mapping related to: Nondestructive Testing (NDT), imaging applications (SAR, Holography), and antenna pattern measurements.

Power spectral ensity of markov texture fields

NASA Technical Reports Server (NTRS)

Shanmugan, K. S.; Holtzman, J. C.

1984-01-01

Texture is an important image characteristic. A variety of spatial domain techniques were proposed for extracting and utilizing textural features for segmenting and classifying images. for the most part, these spatial domain techniques are ad hos in nature. A markov random field model for image texture is discussed. A frequency domain description of image texture is derived in terms of the power spectral density. This model is used for designing optimum frequency domain filters for enhancing, restoring and segmenting images based on their textural properties.

Liver Masses: What Physicians Need to Know About Ordering and Interpreting Liver Imaging.

PubMed

Sheybani, Arman; Gaba, Ron C; Lokken, R Peter; Berggruen, Senta M; Mar, Winnie A

2017-10-18

This paper reviews diagnostic imaging techniques used to characterize liver masses and the imaging characteristics of the most common liver masses. The role of recently adopted ultrasound and magnetic resonance imaging contrast agents will be emphasized. Contrast-enhanced ultrasound is an inexpensive exam which can confirm benignity of certain liver masses without ionizing radiation. Magnetic resonance imaging using hepatocyte-specific gadolinium-based contrast agents can help confirm or narrow the differential diagnosis of liver masses.

Enhancing Deep-Water Low-Resolution Gridded Bathymetry Using Single Image Super-Resolution

NASA Astrophysics Data System (ADS)

Elmore, P. A.; Nock, K.; Bonanno, D.; Smith, L.; Ferrini, V. L.; Petry, F. E.

2017-12-01

We present research to employ single-image super-resolution (SISR) algorithms to enhance knowledge of the seafloor using the 1-minute GEBCO 2014 grid when 100m grids from high-resolution sonar systems are available for training. Our numerical upscaling experiments of x15 upscaling of the GEBCO grid along three areas of the Eastern Pacific Ocean along mid-ocean ridge systems where we have these 100m gridded bathymetry data sets, which we accept as ground-truth. We show that four SISR algorithms can enhance this low-resolution knowledge of bathymetry versus bicubic or Spline-In-Tension algorithms through upscaling under these conditions: 1) rough topography is present in both training and testing areas and 2) the range of depths and features in the training area contains the range of depths in the enhancement area. We quantitatively judged successful SISR enhancement versus bicubic interpolation when Student's hypothesis testing show significant improvement of the root-mean squared error (RMSE) between upscaled bathymetry and 100m gridded ground-truth bathymetry at p < 0.05. In addition, we found evidence that random forest based SISR methods may provide more robust enhancements versus non-forest based SISR algorithms.

Quantitative subsurface analysis using frequency modulated thermal wave imaging

NASA Astrophysics Data System (ADS)

Subhani, S. K.; Suresh, B.; Ghali, V. S.

2018-01-01

Quantitative depth analysis of the anomaly with an enhanced depth resolution is a challenging task towards the estimation of depth of the subsurface anomaly using thermography. Frequency modulated thermal wave imaging introduced earlier provides a complete depth scanning of the object by stimulating it with a suitable band of frequencies and further analyzing the subsequent thermal response using a suitable post processing approach to resolve subsurface details. But conventional Fourier transform based methods used for post processing unscramble the frequencies with a limited frequency resolution and contribute for a finite depth resolution. Spectral zooming provided by chirp z transform facilitates enhanced frequency resolution which can further improves the depth resolution to axially explore finest subsurface features. Quantitative depth analysis with this augmented depth resolution is proposed to provide a closest estimate to the actual depth of subsurface anomaly. This manuscript experimentally validates this enhanced depth resolution using non stationary thermal wave imaging and offers an ever first and unique solution for quantitative depth estimation in frequency modulated thermal wave imaging.

Face recognition using tridiagonal matrix enhanced multivariance products representation

NASA Astrophysics Data System (ADS)

Ã-zay, Evrim Korkmaz

2017-01-01

This study aims to retrieve face images from a database according to a target face image. For this purpose, Tridiagonal Matrix Enhanced Multivariance Products Representation (TMEMPR) is taken into consideration. TMEMPR is a recursive algorithm based on Enhanced Multivariance Products Representation (EMPR). TMEMPR decomposes a matrix into three components which are a matrix of left support terms, a tridiagonal matrix of weight parameters for each recursion, and a matrix of right support terms, respectively. In this sense, there is an analogy between Singular Value Decomposition (SVD) and TMEMPR. However TMEMPR is a more flexible algorithm since its initial support terms (or vectors) can be chosen as desired. Low computational complexity is another advantage of TMEMPR because the algorithm has been constructed with recursions of certain arithmetic operations without requiring any iteration. The algorithm has been trained and tested with ORL face image database with 400 different grayscale images of 40 different people. TMEMPR's performance has been compared with SVD's performance as a result.

Measurement of absorption spectrum of deuterium oxide (D{sub 2}O) and its application to signal enhancement in multiphoton microscopy at the 1700-nm window

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

Wang, Yuxin; Wen, Wenhui; Wang, Kai

2016-01-11

1700-nm window has been demonstrated to be a promising excitation window for deep-tissue multiphoton microscopy (MPM). Long working-distance water immersion objective lenses are typically used for deep-tissue imaging. However, absorption due to immersion water at 1700 nm is still high and leads to dramatic decrease in signals. In this paper, we demonstrate measurement of absorption spectrum of deuterium oxide (D{sub 2}O) from 1200 nm to 2600 nm, covering the three low water-absorption windows potentially applicable for deep-tissue imaging (1300 nm, 1700 nm, and 2200 nm). We apply this measured result to signal enhancement in MPM at the 1700-nm window. Compared with water immersion, D{sub 2}O immersionmore » enhances signal levels in second-harmonic generation imaging, 3-photon fluorescence imaging, and third-harmonic generation imaging by 8.1, 24.8, and 24.7 times with 1662-nm excitation, in good agreement with theoretical calculation based on our absorption measurement. This suggests D{sub 2}O a promising immersion medium for deep-tissue imaging.« less

In vitro near-infrared imaging of occlusal dental caries using a germanium-enhanced CMOS camera

NASA Astrophysics Data System (ADS)

Lee, Chulsung; Darling, Cynthia L.; Fried, Daniel

2010-02-01

The high transparency of dental enamel in the near-infrared (NIR) at 1310-nm can be exploited for imaging dental caries without the use of ionizing radiation. The objective of this study was to determine whether the lesion contrast derived from NIR transillumination can be used to estimate lesion severity. Another aim was to compare the performance of a new Ge enhanced complementary metal-oxide-semiconductor (CMOS) based NIR imaging camera with the InGaAs focal plane array (FPA). Extracted human teeth (n=52) with natural occlusal caries were imaged with both cameras at 1310-nm and the image contrast between sound and carious regions was calculated. After NIR imaging, teeth were sectioned and examined using more established methods, namely polarized light microscopy (PLM) and transverse microradiography (TMR) to calculate lesion severity. Lesions were then classified into 4 categories according to the lesion severity. Lesion contrast increased significantly with lesion severity for both cameras (p<0.05). The Ge enhanced CMOS camera equipped with the larger array and smaller pixels yielded higher contrast values compared with the smaller InGaAs FPA (p<0.01). Results demonstrate that NIR lesion contrast can be used to estimate lesion severity.

In vitro near-infrared imaging of occlusal dental caries using germanium enhanced CMOS camera.

PubMed

Lee, Chulsung; Darling, Cynthia L; Fried, Daniel

2010-03-01

The high transparency of dental enamel in the near-infrared (NIR) at 1310-nm can be exploited for imaging dental caries without the use of ionizing radiation. The objective of this study was to determine whether the lesion contrast derived from NIR transillumination can be used to estimate lesion severity. Another aim was to compare the performance of a new Ge enhanced complementary metal-oxide-semiconductor (CMOS) based NIR imaging camera with the InGaAs focal plane array (FPA). Extracted human teeth (n=52) with natural occlusal caries were imaged with both cameras at 1310-nm and the image contrast between sound and carious regions was calculated. After NIR imaging, teeth were sectioned and examined using more established methods, namely polarized light microscopy (PLM) and transverse microradiography (TMR) to calculate lesion severity. Lesions were then classified into 4 categories according to the lesion severity. Lesion contrast increased significantly with lesion severity for both cameras (p<0.05). The Ge enhanced CMOS camera equipped with the larger array and smaller pixels yielded higher contrast values compared with the smaller InGaAs FPA (p<0.01). Results demonstrate that NIR lesion contrast can be used to estimate lesion severity.

Identifying the association between contrast enhancement pattern, surgical resection, and prognosis in anaplastic glioma patients.

PubMed

Wang, Yinyan; Wang, Kai; Wang, Jiangfei; Li, Shaowu; Ma, Jun; Dai, Jianping; Jiang, Tao

2016-04-01

Contrast enhancement observable on magnetic resonance (MR) images reflects the destructive features of malignant gliomas. This study aimed to investigate the relationship between radiologic patterns of tumor enhancement, extent of resection, and prognosis in patients with anaplastic gliomas (AGs). Clinical data from 268 patients with histologically confirmed AGs were retrospectively analyzed. Contrast enhancement patterns were classified based on preoperative T1-contrast MR images. Univariate and multivariate analyses were performed to evaluate the prognostic value of MR enhancement patterns on progression-free survival (PFS) and overall survival (OS). The pattern of tumor contrast enhancement was associated with the extent of surgical resection in AGs. A gross total resection was more likely to be achieved for AGs with focal enhancement than those with diffuse (p = 0.001) or ring-like (p = 0.024) enhancement. Additionally, patients with focal-enhanced AGs had a significantly longer PFS and OS than those with diffuse (log-rank, p = 0.025 and p = 0.031, respectively) or ring-like (log-rank, p = 0.008 and p = 0.011, respectively) enhanced AGs. Furthermore, multivariate analysis identified the pattern of tumor enhancement as a significant predictor of PFS (p = 0.016, hazard ratio [HR] = 1.485) and OS (p = 0.030, HR = 1.446). Our results suggested that the contrast enhancement pattern on preoperative MR images was associated with the extent of resection and predictive of survival outcomes in AG patients.

High Resolution Near Real Time Image Processing and Support for MSSS Modernization

NASA Astrophysics Data System (ADS)

Duncan, R. B.; Sabol, C.; Borelli, K.; Spetka, S.; Addison, J.; Mallo, A.; Farnsworth, B.; Viloria, R.

2012-09-01

This paper describes image enhancement software applications engineering development work that has been performed in support of Maui Space Surveillance System (MSSS) Modernization. It also includes R&D and transition activity that has been performed over the past few years with the objective of providing increased space situational awareness (SSA) capabilities. This includes Air Force Research Laboratory (AFRL) use of an FY10 Dedicated High Performance Investment (DHPI) cluster award -- and our selection and planned use for an FY12 DHPI award. We provide an introduction to image processing of electro optical (EO) telescope sensors data; and a high resolution image enhancement and near real time processing and summary status overview. We then describe recent image enhancement applications development and support for MSSS Modernization, results to date, and end with a discussion of desired future development work and conclusions. Significant improvements to image processing enhancement have been realized over the past several years, including a key application that has realized more than a 10,000-times speedup compared to the original R&D code -- and a greater than 72-times speedup over the past few years. The latest version of this code maintains software efficiency for post-mission processing while providing optimization for image processing of data from a new EO sensor at MSSS. Additional work has also been performed to develop low latency, near real time processing of data that is collected by the ground-based sensor during overhead passes of space objects.

Image-enhanced endoscopy for diagnosis of colorectal tumors in view of endoscopic treatment

PubMed Central

Yoshida, Naohisa; Yagi, Nobuaki; Yanagisawa, Akio; Naito, Yuji

2012-01-01

Recently, image-enhanced endoscopy (IEE) has been used to diagnose gastrointestinal tumors. This method is a change from conventional white-light (WL) endoscopy without dyeing solution, requiring only the push of a button. In IEE, there are many advantages in diagnosis of neoplastic tumors, evaluation of invasion depth for cancerous lesions, and detection of neoplastic lesions. In narrow band imaging (NBI) systems (Olympus Medical Co., Tokyo, Japan), optical filters that allow narrow-band light to pass at wavelengths of 415 and 540 nm are used. Mucosal surface blood vessels are seen most clearly at 415 nm, which is the wavelength that corresponds to the hemoglobin absorption band, while vessels in the deep layer of the mucosa can be detected at 540 nm. Thus, NBI also can detect pit-like structures named surface pattern. The flexible spectral imaging color enhancement (FICE) system (Fujifilm Medical Co., Tokyo, Japan) is also an IEE but different to NBI. FICE depends on the use of spectral-estimation technology to reconstruct images at different wavelengths based on WL images. FICE can enhance vascular and surface patterns. The autofluorescence imaging (AFI) video endoscope system (Olympus Medical Co., Tokyo, Japan) is a new illumination method that uses the difference in intensity of autofluorescence between the normal area and neoplastic lesions. AFI light comprises a blue light for emitting and a green light for hemoglobin absorption. The aim of this review is to highlight the efficacy of IEE for diagnosis of colorectal tumors for endoscopic treatment. PMID:23293724

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.

X-ray computed tomography imaging of a tumor with high sensitivity using gold nanoparticles conjugated to a cancer-specific antibody via polyethylene glycol chains on their surface

NASA Astrophysics Data System (ADS)

Nakagawa, Tomohiko; Gonda, Kohsuke; Kamei, Takashi; Cong, Liman; Hamada, Yoh; Kitamura, Narufumi; Tada, Hiroshi; Ishida, Takanori; Aimiya, Takuji; Furusawa, Naoko; Nakano, Yasushi; Ohuchi, Noriaki

2016-01-01

Contrast agents are often used to enhance the contrast of X-ray computed tomography (CT) imaging of tumors to improve diagnostic accuracy. However, because the iodine-based contrast agents currently used in hospitals are of low molecular weight, the agent is rapidly excreted from the kidney or moves to extravascular tissues through the capillary vessels, depending on its concentration gradient. This leads to nonspecific enhancement of contrast images for tissues. Here, we created gold (Au) nanoparticles as a new contrast agent to specifically image tumors with CT using an enhanced permeability and retention (EPR) effect. Au has a higher X-ray absorption coefficient than does iodine. Au nanoparticles were supported with polyethylene glycol (PEG) chains on their surface to increase the blood retention and were conjugated with a cancer-specific antibody via terminal PEG chains. The developed Au nanoparticles were injected into tumor-bearing mice, and the distribution of Au was examined with CT imaging, transmission electron microscopy, and elemental analysis using inductively coupled plasma optical emission spectrometry. The results show that specific localization of the developed Au nanoparticles in the tumor is affected by a slight difference in particle size and enhanced by the conjugation of a specific antibody against the tumor.

Adaptive Enhancement of X-Band Marine Radar Imagery to Detect Oil Spill Segments

PubMed Central

Liu, Peng; Li, Ying; Xu, Jin; Zhu, Xueyuan

2017-01-01

Oil spills generate a large cost in environmental and economic terms. Their identification plays an important role in oil-spill response. We propose an oil spill detection method with improved adaptive enhancement on X-band marine radar systems. The radar images used in this paper were acquired on 21 July 2010, from the teaching-training ship “YUKUN” of the Dalian Maritime University. According to the shape characteristic of co-channel interference, two convolutional filters are used to detect the location of the interference, followed by a mean filter to erase the interference. Small objects, such as bright speckles, are taken as a mask in the radar image and improved by the Fields-of-Experts model. The region marked by strong reflected signals from the sea’s surface is selected to identify oil spills. The selected region is subject to improved adaptive enhancement designed based on features of radar images. With the proposed adaptive enhancement technique, calculated oil spill detection is comparable to visual interpretation in accuracy. PMID:29036892

Automated segmentation of middle hepatic vein in non-contrast x-ray CT images based on an atlas-driven approach

NASA Astrophysics Data System (ADS)

Kitagawa, Teruhiko; Zhou, Xiangrong; Hara, Takeshi; Fujita, Hiroshi; Yokoyama, Ryujiro; Kondo, Hiroshi; Kanematsu, Masayuki; Hoshi, Hiroaki

2008-03-01

In order to support the diagnosis of hepatic diseases, understanding the anatomical structures of hepatic lobes and hepatic vessels is necessary. Although viewing and understanding the hepatic vessels in contrast media-enhanced CT images is easy, the observation of the hepatic vessels in non-contrast X-ray CT images that are widely used for the screening purpose is difficult. We are developing a computer-aided diagnosis (CAD) system to support the liver diagnosis based on non-contrast X-ray CT images. This paper proposes a new approach to segment the middle hepatic vein (MHV), a key structure (landmark) for separating the liver region into left and right lobes. Extraction and classification of hepatic vessels are difficult in non-contrast X-ray CT images because the contrast between hepatic vessels and other liver tissues is low. Our approach uses an atlas-driven method by the following three stages. (1) Construction of liver atlases of left and right hepatic lobes using a learning datasets. (2) Fully-automated enhancement and extraction of hepatic vessels in liver regions. (3) Extraction of MHV based on the results of (1) and (2). The proposed approach was applied to 22 normal liver cases of non-contrast X-ray CT images. The preliminary results show that the proposed approach achieves the success in 14 cases for MHV extraction.

In Vivo Targeted, Responsive, and Synergistic Cancer Nanotheranostics by Magnetic Resonance Imaging-Guided Synergistic High-Intensity Focused Ultrasound Ablation and Chemotherapy.

PubMed

Tang, Hailin; Guo, Yuan; Peng, Li; Fang, Hui; Wang, Zhigang; Zheng, Yuanyi; Ran, Haitao; Chen, Yu

2018-05-09

As one of the most representative noninvasive therapeutic modalities, high-intensity focused ultrasound (HIFU) has shown great promise for cancer therapy, but its low therapeutic efficacy and biosafety significantly hinder further extensive clinical translation and application. In this work, we report on the construction of a multifunctional theranostic nanoplatform to synergistically enhance the HIFU-therapeutic efficacy based on nanomedicine. A targeted and temperature-responsive theranostic nanoplatform (PFH/DOX@PLGA/Fe 3 O 4 -FA) has been designed and fabricated for efficient ultrasound/magnetic resonance dual-modality imaging-guided HIFU/chemo synergistic therapy. Especially, the folate was conjugated onto the surface of the nanoplatform for achieving active targeting to hepatoma cells by receptor-ligand interaction, which facilitates accumulation of the nanoplatforms into the tumor site. The integrated superparamagnetic iron oxide nanoparticles could generate the contrast enhancement in T 2 -weighted magnetic resonance imaging. By virtue of the thermal effect as generated by HIFU, liquid-gas phase transition of perfluorohexane (PFH) in nanocomposites was induced to generate PFH microbubbles, which achieved the contrast-enhanced ultrasound imaging and significantly improved the HIFU ablation efficacy. The loaded anticancer drugs could be released from the nanocomposites in a controllable manner (both pH and HIFU responsiveness). These multifunctional nanocomposites have been demonstrated to efficiently suppress the tumor growth based on the enhanced and synergistic chemotherapy and HIFU ablation, providing an efficient theranostic nanoplatform for cancer treatment.

Digital radiographic imaging: is the dental practice ready?

PubMed

Parks, Edwin T

2008-04-01

Digital radiographic imaging is slowly, but surely, replacing film-based imaging. It has many advantages over traditional imaging, but the technology also has some drawbacks. The author presents an overview of the types of digital image receptors available, image enhancement software and the range of costs for the new technology. PRACTICE IMPLICATIONS. The expenses associated with converting to digital radiographic imaging are considerable. The purpose of this article is to provide the clinician with an overview of digital radiographic imaging technology so that he or she can be an informed consumer when evaluating the numerous digital systems in the marketplace.

A robust technique based on VLM and Frangi filter for retinal vessel extraction and denoising.

PubMed

Khan, Khan Bahadar; Khaliq, Amir A; Jalil, Abdul; Shahid, Muhammad

2018-01-01

The exploration of retinal vessel structure is colossally important on account of numerous diseases including stroke, Diabetic Retinopathy (DR) and coronary heart diseases, which can damage the retinal vessel structure. The retinal vascular network is very hard to be extracted due to its spreading and diminishing geometry and contrast variation in an image. The proposed technique consists of unique parallel processes for denoising and extraction of blood vessels in retinal images. In the preprocessing section, an adaptive histogram equalization enhances dissimilarity between the vessels and the background and morphological top-hat filters are employed to eliminate macula and optic disc, etc. To remove local noise, the difference of images is computed from the top-hat filtered image and the high-boost filtered image. Frangi filter is applied at multi scale for the enhancement of vessels possessing diverse widths. Segmentation is performed by using improved Otsu thresholding on the high-boost filtered image and Frangi's enhanced image, separately. In the postprocessing steps, a Vessel Location Map (VLM) is extracted by using raster to vector transformation. Postprocessing steps are employed in a novel way to reject misclassified vessel pixels. The final segmented image is obtained by using pixel-by-pixel AND operation between VLM and Frangi output image. The method has been rigorously analyzed on the STARE, DRIVE and HRF datasets.

Assessment of Pansharpening Methods Applied to WorldView-2 Imagery Fusion.

PubMed

Li, Hui; Jing, Linhai; Tang, Yunwei

2017-01-05

Since WorldView-2 (WV-2) images are widely used in various fields, there is a high demand for the use of high-quality pansharpened WV-2 images for different application purposes. With respect to the novelty of the WV-2 multispectral (MS) and panchromatic (PAN) bands, the performances of eight state-of-art pan-sharpening methods for WV-2 imagery including six datasets from three WV-2 scenes were assessed in this study using both quality indices and information indices, along with visual inspection. The normalized difference vegetation index, normalized difference water index, and morphological building index, which are widely used in applications related to land cover classification, the extraction of vegetation areas, buildings, and water bodies, were employed in this work to evaluate the performance of different pansharpening methods in terms of information presentation ability. The experimental results show that the Haze- and Ratio-based, adaptive Gram-Schmidt, Generalized Laplacian pyramids (GLP) methods using enhanced spectral distortion minimal model and enhanced context-based decision model methods are good choices for producing fused WV-2 images used for image interpretation and the extraction of urban buildings. The two GLP-based methods are better choices than the other methods, if the fused images will be used for applications related to vegetation and water-bodies.

Assessment of Pansharpening Methods Applied to WorldView-2 Imagery Fusion

PubMed Central

Li, Hui; Jing, Linhai; Tang, Yunwei

2017-01-01

Since WorldView-2 (WV-2) images are widely used in various fields, there is a high demand for the use of high-quality pansharpened WV-2 images for different application purposes. With respect to the novelty of the WV-2 multispectral (MS) and panchromatic (PAN) bands, the performances of eight state-of-art pan-sharpening methods for WV-2 imagery including six datasets from three WV-2 scenes were assessed in this study using both quality indices and information indices, along with visual inspection. The normalized difference vegetation index, normalized difference water index, and morphological building index, which are widely used in applications related to land cover classification, the extraction of vegetation areas, buildings, and water bodies, were employed in this work to evaluate the performance of different pansharpening methods in terms of information presentation ability. The experimental results show that the Haze- and Ratio-based, adaptive Gram-Schmidt, Generalized Laplacian pyramids (GLP) methods using enhanced spectral distortion minimal model and enhanced context-based decision model methods are good choices for producing fused WV-2 images used for image interpretation and the extraction of urban buildings. The two GLP-based methods are better choices than the other methods, if the fused images will be used for applications related to vegetation and water-bodies. PMID:28067770

HALO: a reconfigurable image enhancement and multisensor fusion system

NASA Astrophysics Data System (ADS)

Wu, F.; Hickman, D. L.; Parker, Steve J.

2014-06-01

Contemporary high definition (HD) cameras and affordable infrared (IR) imagers are set to dramatically improve the effectiveness of security, surveillance and military vision systems. However, the quality of imagery is often compromised by camera shake, or poor scene visibility due to inadequate illumination or bad atmospheric conditions. A versatile vision processing system called HALO™ is presented that can address these issues, by providing flexible image processing functionality on a low size, weight and power (SWaP) platform. Example processing functions include video distortion correction, stabilisation, multi-sensor fusion and image contrast enhancement (ICE). The system is based around an all-programmable system-on-a-chip (SoC), which combines the computational power of a field-programmable gate array (FPGA) with the flexibility of a CPU. The FPGA accelerates computationally intensive real-time processes, whereas the CPU provides management and decision making functions that can automatically reconfigure the platform based on user input and scene content. These capabilities enable a HALO™ equipped reconnaissance or surveillance system to operate in poor visibility, providing potentially critical operational advantages in visually complex and challenging usage scenarios. The choice of an FPGA based SoC is discussed, and the HALO™ architecture and its implementation are described. The capabilities of image distortion correction, stabilisation, fusion and ICE are illustrated using laboratory and trials data.

[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.

Automatic segmentation of invasive breast carcinomas from dynamic contrast-enhanced MRI using time series analysis.

PubMed

Jayender, Jagadaeesan; Chikarmane, Sona; Jolesz, Ferenc A; Gombos, Eva

2014-08-01

To accurately segment invasive ductal carcinomas (IDCs) from dynamic contrast-enhanced MRI (DCE-MRI) using time series analysis based on linear dynamic system (LDS) modeling. Quantitative segmentation methods based on black-box modeling and pharmacokinetic modeling are highly dependent on imaging pulse sequence, timing of bolus injection, arterial input function, imaging noise, and fitting algorithms. We modeled the underlying dynamics of the tumor by an LDS and used the system parameters to segment the carcinoma on the DCE-MRI. Twenty-four patients with biopsy-proven IDCs were analyzed. The lesions segmented by the algorithm were compared with an expert radiologist's segmentation and the output of a commercial software, CADstream. The results are quantified in terms of the accuracy and sensitivity of detecting the lesion and the amount of overlap, measured in terms of the Dice similarity coefficient (DSC). The segmentation algorithm detected the tumor with 90% accuracy and 100% sensitivity when compared with the radiologist's segmentation and 82.1% accuracy and 100% sensitivity when compared with the CADstream output. The overlap of the algorithm output with the radiologist's segmentation and CADstream output, computed in terms of the DSC was 0.77 and 0.72, respectively. The algorithm also shows robust stability to imaging noise. Simulated imaging noise with zero mean and standard deviation equal to 25% of the base signal intensity was added to the DCE-MRI series. The amount of overlap between the tumor maps generated by the LDS-based algorithm from the noisy and original DCE-MRI was DSC = 0.95. The time-series analysis based segmentation algorithm provides high accuracy and sensitivity in delineating the regions of enhanced perfusion corresponding to tumor from DCE-MRI. © 2013 Wiley Periodicals, Inc.

Method for enhancing cell penetration of Gd3+-based MRI contrast agents by conjugation with hydrophobic fluorescent dyes.

PubMed

Yamane, Takehiro; Hanaoka, Kenjiro; Muramatsu, Yasuaki; Tamura, Keita; Adachi, Yusuke; Miyashita, Yasushi; Hirata, Yasunobu; Nagano, Tetsuo

2011-11-16

Gadolinium ion (Gd(3+)) complexes are commonly used as magnetic resonance imaging (MRI) contrast agents to enhance signals in T(1)-weighted MR images. Recently, several methods to achieve cell-permeation of Gd(3+) complexes have been reported, but more general and efficient methodology is needed. In this report, we describe a novel method to achieve cell permeation of Gd(3+) complexes by using hydrophobic fluorescent dyes as a cell-permeability-enhancing unit. We synthesized Gd(3+) complexes conjugated with boron dipyrromethene (BDP-Gd) and Cy7 dye (Cy7-Gd), and showed that these conjugates can be introduced efficiently into cells. To examine the relationship between cell permeability and dye structure, we further synthesized a series of Cy7-Gd derivatives. On the basis of MR imaging, flow cytometry, and ICP-MS analysis of cells loaded with Cy7-Gd derivatives, highly hydrophobic and nonanionic dyes were effective for enhancing cell permeation of Gd(3+) complexes. Furthermore, the behavior of these Cy7-Gd derivatives was examined in mice. Thus, conjugation of hydrophobic fluorescent dyes appears to be an effective approach to improve the cell permeability of Gd(3+) complexes, and should be applicable for further development of Gd(3+)-based MRI contrast agents.

Readout-segmented multi-shot diffusion-weighted MRI of the knee joint in patients with juvenile idiopathic arthritis.

PubMed

Sauer, Alexander; Li, Mengxia; Holl-Wieden, Annette; Pabst, Thomas; Neubauer, Henning

2017-10-12

Diffusion-weighted MRI has been proposed as a new technique for imaging synovitis without intravenous contrast application. We investigated diagnostic utility of multi-shot readout-segmented diffusion-weighted MRI (multi-shot DWI) for synovial imaging of the knee joint in patients with juvenile idiopathic arthritis (JIA). Thirty-two consecutive patients with confirmed or suspected JIA (21 girls, median age 13 years) underwent routine 1.5 T MRI with contrast-enhanced T1w imaging (contrast-enhanced MRI) and with multi-shot DWI (RESOLVE, b-values 0-50 and 800 s/mm 2 ). Contrast-enhanced MRI, representing the diagnostic standard, and diffusion-weighted images at b = 800 s/mm 2 were separately rated by three independent blinded readers at different levels of expertise for the presence and the degree of synovitis on a modified 5-item Likert scale along with the level of subjective diagnostic confidence. Fourteen (44%) patients had active synovitis and joint effusion, nine (28%) patients showed mild synovial enhancement not qualifying for arthritis and another nine (28%) patients had no synovial signal alterations on contrast-enhanced imaging. Ratings by the 1st reader on contrast-enhanced MRI and on DWI showed substantial agreement (κ = 0.74). Inter-observer-agreement was high for diagnosing, or ruling out, active arthritis of the knee joint on contrast-enhanced MRI and on DWI, showing full agreement between 1st and 2nd reader and disagreement in one case (3%) between 1st and 3rd reader. In contrast, ratings in cases of absent vs. little synovial inflammation were markedly inconsistent on DWI. Diagnostic confidence was lower on DWI, compared to contrast-enhanced imaging. Multi-shot DWI of the knee joint is feasible in routine imaging and reliably diagnoses, or rules out, active arthritis of the knee joint in paediatric patients without the need of gadolinium-based i.v. contrast injection. Possibly due to "T2w shine-through" artifacts, DWI does not reliably differentiate non-inflamed joints from knee joints with mild synovial irritation.

Dynamic cone beam CT angiography of carotid and cerebral arteries using canine model

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

Cai Weixing; Zhao Binghui; Conover, David

2012-01-15

Purpose: This research is designed to develop and evaluate a flat-panel detector-based dynamic cone beam CT system for dynamic angiography imaging, which is able to provide both dynamic functional information and dynamic anatomic information from one multirevolution cone beam CT scan. Methods: A dynamic cone beam CT scan acquired projections over four revolutions within a time window of 40 s after contrast agent injection through a femoral vein to cover the entire wash-in and wash-out phases. A dynamic cone beam CT reconstruction algorithm was utilized and a novel recovery method was developed to correct the time-enhancement curve of contrast flow.more » From the same data set, both projection-based subtraction and reconstruction-based subtraction approaches were utilized and compared to remove the background tissues and visualize the 3D vascular structure to provide the dynamic anatomic information. Results: Through computer simulations, the new recovery algorithm for dynamic time-enhancement curves was optimized and showed excellent accuracy to recover the actual contrast flow. Canine model experiments also indicated that the recovered time-enhancement curves from dynamic cone beam CT imaging agreed well with that of an IV-digital subtraction angiography (DSA) study. The dynamic vascular structures reconstructed using both projection-based subtraction and reconstruction-based subtraction were almost identical as the differences between them were comparable to the background noise level. At the enhancement peak, all the major carotid and cerebral arteries and the Circle of Willis could be clearly observed. Conclusions: The proposed dynamic cone beam CT approach can accurately recover the actual contrast flow, and dynamic anatomic imaging can be obtained with high isotropic 3D resolution. This approach is promising for diagnosis and treatment planning of vascular diseases and strokes.« less

Improved Interactive Medical-Imaging System

NASA Technical Reports Server (NTRS)

Ross, Muriel D.; Twombly, Ian A.; Senger, Steven

2003-01-01

An improved computational-simulation system for interactive medical imaging has been invented. The system displays high-resolution, three-dimensional-appearing images of anatomical objects based on data acquired by such techniques as computed tomography (CT) and magnetic-resonance imaging (MRI). The system enables users to manipulate the data to obtain a variety of views for example, to display cross sections in specified planes or to rotate images about specified axes. Relative to prior such systems, this system offers enhanced capabilities for synthesizing images of surgical cuts and for collaboration by users at multiple, remote computing sites.

Reduction in respiratory motion artefacts on gadoxetate-enhanced MRI after training technicians to apply a simple and more patient-adapted breathing command.

PubMed

Gutzeit, Andreas; Matoori, Simon; Froehlich, Johannes M; von Weymarn, Constantin; Reischauer, Carolin; Kolokythas, Orpheus; Goyen, Matthias; Hergan, Klaus; Meissnitzer, Matthias; Forstner, Rosemarie; Soyka, Jan D; Doert, Aleksis; Koh, Dow-Mu

2016-08-01

To investigate whether a trained group of technicians using a modified breathing command during gadoxetate-enhanced liver MRI reduces respiratory motion artefacts compared to non-trained technicians using a traditional breathing command. The gadoxetate-enhanced liver MR images of 30 patients acquired using the traditional breathing command and the subsequent 30 patients after training the technicians to use a modified breathing command were analyzed. A subgroup of patients (n = 8) underwent scans both by trained and untrained technicians. Images obtained using the traditional and modified breathing command were compared for the presence of breathing artefacts [respiratory artefact-based image quality scores from 1 (best) to 5 (non-diagnostic)]. There was a highly significant improvement in the arterial phase image quality scores in patients using the modified breathing command compared to the traditional one (P < 0.001). The percentage of patients with severe and extensive breathing artefacts in the arterial phase decreased from 33.3 % to 6.7 % after introducing the modified breathing command (P = 0.021). In the subgroup that underwent MRI using both breathing commands, arterial phase image quality improved significantly (P = 0.008) using the modified breathing command. Training technicians to use a modified breathing command significantly improved arterial phase image quality of gadoxetate-enhanced liver MRI. • A modified breathing command reduced respiratory artefacts on arterial-phase gadoxetate-enhanced MRI (P < 0.001). • The modified command decreased severe and extensive arterial-phase breathing artefacts (P = 0.021). • Training technicians to use a modified breathing command improved arterial-phase images.

Standardized processing of MALDI imaging raw data for enhancement of weak analyte signals in mouse models of gastric cancer and Alzheimer's disease.

PubMed

Schwartz, Matthias; Meyer, Björn; Wirnitzer, Bernhard; Hopf, Carsten

2015-03-01

Conventional mass spectrometry image preprocessing methods used for denoising, such as the Savitzky-Golay smoothing or discrete wavelet transformation, typically do not only remove noise but also weak signals. Recently, memory-efficient principal component analysis (PCA) in conjunction with random projections (RP) has been proposed for reversible compression and analysis of large mass spectrometry imaging datasets. It considers single-pixel spectra in their local context and consequently offers the prospect of using information from the spectra of adjacent pixels for denoising or signal enhancement. However, little systematic analysis of key RP-PCA parameters has been reported so far, and the utility and validity of this method for context-dependent enhancement of known medically or pharmacologically relevant weak analyte signals in linear-mode matrix-assisted laser desorption/ionization (MALDI) mass spectra has not been explored yet. Here, we investigate MALDI imaging datasets from mouse models of Alzheimer's disease and gastric cancer to systematically assess the importance of selecting the right number of random projections k and of principal components (PCs) L for reconstructing reproducibly denoised images after compression. We provide detailed quantitative data for comparison of RP-PCA-denoising with the Savitzky-Golay and wavelet-based denoising in these mouse models as a resource for the mass spectrometry imaging community. Most importantly, we demonstrate that RP-PCA preprocessing can enhance signals of low-intensity amyloid-β peptide isoforms such as Aβ1-26 even in sparsely distributed Alzheimer's β-amyloid plaques and that it enables enhanced imaging of multiply acetylated histone H4 isoforms in response to pharmacological histone deacetylase inhibition in vivo. We conclude that RP-PCA denoising may be a useful preprocessing step in biomarker discovery workflows.

Renal Cyst Pseudoenhancement: Intraindividual Comparison Between Virtual Monochromatic Spectral Images and Conventional Polychromatic 120-kVp Images Obtained During the Same CT Examination and Comparisons Among Images Reconstructed Using Filtered Back Projection, Adaptive Statistical Iterative Reconstruction, and Model-Based Iterative Reconstruction

PubMed Central

Yamada, Yoshitake; Yamada, Minoru; Sugisawa, Koichi; Akita, Hirotaka; Shiomi, Eisuke; Abe, Takayuki; Okuda, Shigeo; Jinzaki, Masahiro

2015-01-01

Abstract The purpose of this study was to compare renal cyst pseudoenhancement between virtual monochromatic spectral (VMS) and conventional polychromatic 120-kVp images obtained during the same abdominal computed tomography (CT) examination and among images reconstructed using filtered back projection (FBP), adaptive statistical iterative reconstruction (ASIR), and model-based iterative reconstruction (MBIR). Our institutional review board approved this prospective study; each participant provided written informed consent. Thirty-one patients (19 men, 12 women; age range, 59–85 years; mean age, 73.2 ± 5.5 years) with renal cysts underwent unenhanced 120-kVp CT followed by sequential fast kVp-switching dual-energy (80/140 kVp) and 120-kVp abdominal enhanced CT in the nephrographic phase over a 10-cm scan length with a random acquisition order and 4.5-second intervals. Fifty-one renal cysts (maximal diameter, 18.0 ± 14.7 mm [range, 4–61 mm]) were identified. The CT attenuation values of the cysts as well as of the kidneys were measured on the unenhanced images, enhanced VMS images (at 70 keV) reconstructed using FBP and ASIR from dual-energy data, and enhanced 120-kVp images reconstructed using FBP, ASIR, and MBIR. The results were analyzed using the mixed-effects model and paired t test with Bonferroni correction. The attenuation increases (pseudoenhancement) of the renal cysts on the VMS images reconstructed using FBP/ASIR (least square mean, 5.0/6.0 Hounsfield units [HU]; 95% confidence interval, 2.6–7.4/3.6–8.4 HU) were significantly lower than those on the conventional 120-kVp images reconstructed using FBP/ASIR/MBIR (least square mean, 12.1/12.8/11.8 HU; 95% confidence interval, 9.8–14.5/10.4–15.1/9.4–14.2 HU) (all P < .001); on the other hand, the CT attenuation values of the kidneys on the VMS images were comparable to those on the 120-kVp images. Regardless of the reconstruction algorithm, 70-keV VMS images showed a lower degree of pseudoenhancement of renal cysts than 120-kVp images, while maintaining kidney contrast enhancement comparable to that on 120-kVp images. PMID:25881852

Taking a Closer Look.

ERIC Educational Resources Information Center

Reynolds, Karen

1996-01-01

Outlines benefits of integrating optical instruments in computer-based instructional systems in a science classroom including budget, immediacy, pictorial records, and graphic enhancement. Presents examples of investigative activities involving optical instruments and images digitized for computer-based manipulation. (JRH)

Design of video processing and testing system based on DSP and FPGA

NASA Astrophysics Data System (ADS)

Xu, Hong; Lv, Jun; Chen, Xi'ai; Gong, Xuexia; Yang, Chen'na

2007-12-01

Based on high speed Digital Signal Processor (DSP) and Field Programmable Gate Array (FPGA), a video capture, processing and display system is presented, which is of miniaturization and low power. In this system, a triple buffering scheme was used for the capture and display, so that the application can always get a new buffer without waiting; The Digital Signal Processor has an image process ability and it can be used to test the boundary of workpiece's image. A video graduation technology is used to aim at the position which is about to be tested, also, it can enhance the system's flexibility. The character superposition technology realized by DSP is used to display the test result on the screen in character format. This system can process image information in real time, ensure test precision, and help to enhance product quality and quality management.

Wafer defect detection by a polarization-insensitive external differential interference contrast module.

PubMed

Nativ, Amit; Feldman, Haim; Shaked, Natan T

2018-05-01

We present a system that is based on a new external, polarization-insensitive differential interference contrast (DIC) module specifically adapted for detecting defects in semiconductor wafers. We obtained defect signal enhancement relative to the surrounding wafer pattern when compared with bright-field imaging. The new DIC module proposed is based on a shearing interferometer that connects externally at the output port of an optical microscope and enables imaging thin samples, such as wafer defects. This module does not require polarization optics (such as Wollaston or Nomarski prisms) and is insensitive to polarization, unlike traditional DIC techniques. In addition, it provides full control of the DIC shear and orientation, which allows obtaining a differential phase image directly on the camera (with no further digital processing) while enhancing defect detection capabilities, even if the size of the defect is smaller than the resolution limit. Our technique has the potential of future integration into semiconductor production lines.

Intratympanic Iodine Contrast Injection Diffuses Across the Round Window Membrane Allowing for Perilymphatic CT Volume Acquisition Imaging.

PubMed

Abt, Nicholas B; Lehar, Mohamed; Guajardo, Carolina Trevino; Penninger, Richard T; Ward, Bryan K; Pearl, Monica S; Carey, John P

2016-04-01

Whether the round window membrane (RWM) is permeable to iodine-based contrast agents (IBCA) is unknown; therefore, our goal was to determine if IBCAs could diffuse through the RWM using CT volume acquisition imaging. Imaging of hydrops in the living human ear has attracted recent interest. Intratympanic (IT) injection has shown gadolinium's ability to diffuse through the RWM, enhancing the perilymphatic space. Four unfixed human cadaver temporal bones underwent intratympanic IBCA injection using three sequentially studied methods. The first method was direct IT injection. The second method used direct RWM visualization via tympanomeatal flap for IBCA-soaked absorbable gelatin pledget placement. In the third method, the middle ear was filled with contrast after flap elevation. Volume acquisition CT images were obtained immediately postexposure, and at 1-, 6-, and 24-hour intervals. Postprocessing was accomplished using color ramping and subtraction imaging. After the third method, positive RWM and perilymphatic enhancement were observed with endolymph sparing. Gray scale and color ramp multiplanar reconstructions displayed increased signal within the cochlea compared with precontrast imaging. The cochlea was measured for attenuation differences compared with pure water, revealing a preinjection average of -1,103 HU and a postinjection average of 338 HU. Subtraction imaging shows enhancement remaining within the cochlear space, Eustachian tube, middle ear epithelial lining, and mastoid. Iohexol iodine contrast is able to diffuse across the RWM. Volume acquisition CT imaging was able to detect perilymphatic enhancement at 0.5-mm slice thickness. The clinical application of IBCA IT injection seems promising but requires further safety studies.

Hepatic reaction dose for parenchymal changes on Gd-EOB-DTPA-enhanced magnetic resonance images after stereotactic body radiation therapy for hepatocellular carcinoma.

PubMed

Jung, Jinhong; Yoon, Sang Min; Cho, Byungchul; Choi, Young Eun; Kwak, Jungwon; Kim, So Yeon; Lee, Sang-Wook; Ahn, Seung Do; Choi, Eun Kyung; Kim, Jong Hoon

2016-02-01

The present study evaluated the threshold dose for hepatic parenchymal changes on gadolinium ethoxybenzyl diethylenetriaminepentaacetic acid (Gd-EOB-DTPA)-enhanced magnetic resonance (MR) images after stereotactic body radiation therapy (SBRT) for hepatocellular carcinoma (HCC). Twenty patients with available data of follow-up MR images acquired 2-4 months after completion of SBRT were selected among the registered patients. SBRT was performed using multiple coplanar and non-coplanar beams with energies of 6 or 15 MV. All patients were treated with doses of 45 Gy administered in three fractions over 3 consecutive days. For image registration between planning computed tomography (CT) and MR images, landmark-based rigid body registration was performed using MIM software. Seventeen patients were included in the analysis. The median discrepancies between planning CT and MR images in the left-right, anterior-posterior and superior-inferior directions were 1.38 mm, 1.24 mm and 1.72 mm, respectively. The median D50 value for the defect in the hepatobiliary phase of Gd-EOB-DTPA-enhanced MR images after SBRT was 19.8 Gy (range, 14.2-28.7 Gy), with R(2) values ranging from 0.76 to 0.99. The threshold dose for parenchymal changes in the hepatobiliary phase of Gd-EOB-DTPA-enhanced MR images performed 2-4 months after 45 Gy of SBRT in three fractions was approximately 20 Gy. Our results provide the basis for further research on the functional loss of liver parenchyma after SBRT. © 2015 The Royal Australian and New Zealand College of Radiologists.

A content-based image retrieval method for optical colonoscopy images based on image recognition techniques

NASA Astrophysics Data System (ADS)

Nosato, Hirokazu; Sakanashi, Hidenori; Takahashi, Eiichi; Murakawa, Masahiro

2015-03-01

This paper proposes a content-based image retrieval method for optical colonoscopy images that can find images similar to ones being diagnosed. Optical colonoscopy is a method of direct observation for colons and rectums to diagnose bowel diseases. It is the most common procedure for screening, surveillance and treatment. However, diagnostic accuracy for intractable inflammatory bowel diseases, such as ulcerative colitis (UC), is highly dependent on the experience and knowledge of the medical doctor, because there is considerable variety in the appearances of colonic mucosa within inflammations with UC. In order to solve this issue, this paper proposes a content-based image retrieval method based on image recognition techniques. The proposed retrieval method can find similar images from a database of images diagnosed as UC, and can potentially furnish the medical records associated with the retrieved images to assist the UC diagnosis. Within the proposed method, color histogram features and higher order local auto-correlation (HLAC) features are adopted to represent the color information and geometrical information of optical colonoscopy images, respectively. Moreover, considering various characteristics of UC colonoscopy images, such as vascular patterns and the roughness of the colonic mucosa, we also propose an image enhancement method to highlight the appearances of colonic mucosa in UC. In an experiment using 161 UC images from 32 patients, we demonstrate that our method improves the accuracy of retrieving similar UC images.

Image degradation characteristics and restoration based on regularization for diffractive imaging

NASA Astrophysics Data System (ADS)

Zhi, Xiyang; Jiang, Shikai; Zhang, Wei; Wang, Dawei; Li, Yun

2017-11-01

The diffractive membrane optical imaging system is an important development trend of ultra large aperture and lightweight space camera. However, related investigations on physics-based diffractive imaging degradation characteristics and corresponding image restoration methods are less studied. In this paper, the model of image quality degradation for the diffraction imaging system is first deduced mathematically based on diffraction theory and then the degradation characteristics are analyzed. On this basis, a novel regularization model of image restoration that contains multiple prior constraints is established. After that, the solving approach of the equation with the multi-norm coexistence and multi-regularization parameters (prior's parameters) is presented. Subsequently, the space-variant PSF image restoration method for large aperture diffractive imaging system is proposed combined with block idea of isoplanatic region. Experimentally, the proposed algorithm demonstrates its capacity to achieve multi-objective improvement including MTF enhancing, dispersion correcting, noise and artifact suppressing as well as image's detail preserving, and produce satisfactory visual quality. This can provide scientific basis for applications and possesses potential application prospects on future space applications of diffractive membrane imaging technology.

Fuzzy pulmonary vessel segmentation in contrast enhanced CT data

NASA Astrophysics Data System (ADS)

Kaftan, Jens N.; Kiraly, Atilla P.; Bakai, Annemarie; Das, Marco; Novak, Carol L.; Aach, Til

2008-03-01

Pulmonary vascular tree segmentation has numerous applications in medical imaging and computer-aided diagnosis (CAD), including detection and visualization of pulmonary emboli (PE), improved lung nodule detection, and quantitative vessel analysis. We present a novel approach to pulmonary vessel segmentation based on a fuzzy segmentation concept, combining the strengths of both threshold and seed point based methods. The lungs of the original image are first segmented and a threshold-based approach identifies core vessel components with a high specificity. These components are then used to automatically identify reliable seed points for a fuzzy seed point based segmentation method, namely fuzzy connectedness. The output of the method consists of the probability of each voxel belonging to the vascular tree. Hence, our method provides the possibility to adjust the sensitivity/specificity of the segmentation result a posteriori according to application-specific requirements, through definition of a minimum vessel-probability required to classify a voxel as belonging to the vascular tree. The method has been evaluated on contrast-enhanced thoracic CT scans from clinical PE cases and demonstrates overall promising results. For quantitative validation we compare the segmentation results to randomly selected, semi-automatically segmented sub-volumes and present the resulting receiver operating characteristic (ROC) curves. Although we focus on contrast enhanced chest CT data, the method can be generalized to other regions of the body as well as to different imaging modalities.

Comparative study of protoporphyrin IX fluorescence image enhancement methods to improve an optical imaging system for oral cancer detection

NASA Astrophysics Data System (ADS)

Jiang, Ching-Fen; Wang, Chih-Yu; Chiang, Chun-Ping

2011-07-01

Optoelectronics techniques to induce protoporphyrin IX fluorescence with topically applied 5-aminolevulinic acid on the oral mucosa have been developed to noninvasively detect oral cancer. Fluorescence imaging enables wide-area screening for oral premalignancy, but the lack of an adequate fluorescence enhancement method restricts the clinical imaging application of these techniques. This study aimed to develop a reliable fluorescence enhancement method to improve PpIX fluorescence imaging systems for oral cancer detection. Three contrast features, red-green-blue reflectance difference, R/B ratio, and R/G ratio, were developed first based on the optical properties of the fluorescence images. A comparative study was then carried out with one negative control and four biopsy confirmed clinical cases to validate the optimal image processing method for the detection of the distribution of malignancy. The results showed the superiority of the R/G ratio in terms of yielding a better contrast between normal and neoplastic tissue, and this method was less prone to errors in detection. Quantitative comparison with the clinical diagnoses in the four neoplastic cases showed that the regions of premalignancy obtained using the proposed method accorded with the expert's determination, suggesting the potential clinical application of this method for the detection of oral cancer.

Image resolution enhancement via image restoration using neural network

NASA Astrophysics Data System (ADS)

Zhang, Shuangteng; Lu, Yihong

2011-04-01

Image super-resolution aims to obtain a high-quality image at a resolution that is higher than that of the original coarse one. This paper presents a new neural network-based method for image super-resolution. In this technique, the super-resolution is considered as an inverse problem. An observation model that closely follows the physical image acquisition process is established to solve the problem. Based on this model, a cost function is created and minimized by a Hopfield neural network to produce high-resolution images from the corresponding low-resolution ones. Not like some other single frame super-resolution techniques, this technique takes into consideration point spread function blurring as well as additive noise and therefore generates high-resolution images with more preserved or restored image details. Experimental results demonstrate that the high-resolution images obtained by this technique have a very high quality in terms of PSNR and visually look more pleasant.

Similarity measure and domain adaptation in multiple mixture model clustering: An application to image processing.

PubMed

Leong, Siow Hoo; Ong, Seng Huat

2017-01-01

This paper considers three crucial issues in processing scaled down image, the representation of partial image, similarity measure and domain adaptation. Two Gaussian mixture model based algorithms are proposed to effectively preserve image details and avoids image degradation. Multiple partial images are clustered separately through Gaussian mixture model clustering with a scan and select procedure to enhance the inclusion of small image details. The local image features, represented by maximum likelihood estimates of the mixture components, are classified by using the modified Bayes factor (MBF) as a similarity measure. The detection of novel local features from MBF will suggest domain adaptation, which is changing the number of components of the Gaussian mixture model. The performance of the proposed algorithms are evaluated with simulated data and real images and it is shown to perform much better than existing Gaussian mixture model based algorithms in reproducing images with higher structural similarity index.

Fuzzy Matching Based on Gray-scale Difference for Quantum Images

NASA Astrophysics Data System (ADS)

Luo, GaoFeng; Zhou, Ri-Gui; Liu, XingAo; Hu, WenWen; Luo, Jia

2018-05-01

Quantum image processing has recently emerged as an essential problem in practical tasks, e.g. real-time image matching. Previous studies have shown that the superposition and entanglement of quantum can greatly improve the efficiency of complex image processing. In this paper, a fuzzy quantum image matching scheme based on gray-scale difference is proposed to find out the target region in a reference image, which is very similar to the template image. Firstly, we employ the proposed enhanced quantum representation (NEQR) to store digital images. Then some certain quantum operations are used to evaluate the gray-scale difference between two quantum images by thresholding. If all of the obtained gray-scale differences are not greater than the threshold value, it indicates a successful fuzzy matching of quantum images. Theoretical analysis and experiments show that the proposed scheme performs fuzzy matching at a low cost and also enables exponentially significant speedup via quantum parallel computation.

Similarity measure and domain adaptation in multiple mixture model clustering: An application to image processing

PubMed Central

Leong, Siow Hoo

2017-01-01

This paper considers three crucial issues in processing scaled down image, the representation of partial image, similarity measure and domain adaptation. Two Gaussian mixture model based algorithms are proposed to effectively preserve image details and avoids image degradation. Multiple partial images are clustered separately through Gaussian mixture model clustering with a scan and select procedure to enhance the inclusion of small image details. The local image features, represented by maximum likelihood estimates of the mixture components, are classified by using the modified Bayes factor (MBF) as a similarity measure. The detection of novel local features from MBF will suggest domain adaptation, which is changing the number of components of the Gaussian mixture model. The performance of the proposed algorithms are evaluated with simulated data and real images and it is shown to perform much better than existing Gaussian mixture model based algorithms in reproducing images with higher structural similarity index. PMID:28686634

Task-oriented lossy compression of magnetic resonance images

NASA Astrophysics Data System (ADS)

Anderson, Mark C.; Atkins, M. Stella; Vaisey, Jacques

1996-04-01

A new task-oriented image quality metric is used to quantify the effects of distortion introduced into magnetic resonance images by lossy compression. This metric measures the similarity between a radiologist's manual segmentation of pathological features in the original images and the automated segmentations performed on the original and compressed images. The images are compressed using a general wavelet-based lossy image compression technique, embedded zerotree coding, and segmented using a three-dimensional stochastic model-based tissue segmentation algorithm. The performance of the compression system is then enhanced by compressing different regions of the image volume at different bit rates, guided by prior knowledge about the location of important anatomical regions in the image. Application of the new system to magnetic resonance images is shown to produce compression results superior to the conventional methods, both subjectively and with respect to the segmentation similarity metric.

AFM feature definition for neural cells on nanofibrillar tissue scaffolds.

PubMed

Tiryaki, Volkan M; Khan, Adeel A; Ayres, Virginia M

2012-01-01

A diagnostic approach is developed and implemented that provides clear feature definition in atomic force microscopy (AFM) images of neural cells on nanofibrillar tissue scaffolds. Because the cellular edges and processes are on the same order as the background nanofibers, this imaging situation presents a feature definition problem. The diagnostic approach is based on analysis of discrete Fourier transforms of standard AFM section measurements. The diagnostic conclusion that the combination of dynamic range enhancement with low-frequency component suppression enhances feature definition is shown to be correct and to lead to clear-featured images that could change previously held assumptions about the cell-cell interactions present. Clear feature definition of cells on scaffolds extends the usefulness of AFM imaging for use in regenerative medicine. © Wiley Periodicals, Inc.

CT-scout based, semi-automated vertebral morphometry after digital image enhancement.

PubMed

Glinkowski, Wojciech M; Narloch, Jerzy

2017-09-01

Radiographic diagnosis of osteoporotic vertebral fracture is necessary to reduce its substantial associated morbidity. Computed tomography (CT) scout has recently been demonstrated as a reliable technique for vertebral fracture diagnosis. Software assistance may help to overcome some limitations of that diagnostics. We aimed to evaluate whether digital image enhancement improved the capacity of one of the existing software to detect fractures semi-automatically. CT scanograms of patients suffering from osteoporosis, with or without vertebral fractures were analyzed. The original set of CT scanograms were triplicated and digitally modified to improve edge detection using three different techniques: SHARPENING, UNSHARP MASKING, and CONVOLUTION. The manual morphometric analysis identified 1485 vertebrae, 200 of which were classified as fractured. Unadjusted morphometry (AUTOMATED with no digital enhancement) found 63 fractures, 33 of which were true positive (i.e., it correctly identified 52% of the fractures); SHARPENING detected 57 fractures (30 true positives, 53%); UNSHARP MASKING yielded 30 (13 true positives, 43%); and CONVOLUTION found 24 fractures (9 true positives, 38%). The intra-reader reliability for height ratios did not significantly improve with image enhancement (kappa ranged 0.22-0.41 for adjusted measurements and 0.16-0.38 for unadjusted). Similarly, the inter-reader agreement for prevalent fractures did not significantly improve with image enhancement (kappa 0.29-0.56 and -0.01 to 0.23 for adjusted and unadjusted measurements, respectively). Our results suggest that digital image enhancement does not improve software-assisted vertebral fracture detection by CT scout. Copyright © 2017 Elsevier B.V. All rights reserved.

Quantum enhanced superresolution microscopy (Conference Presentation)

NASA Astrophysics Data System (ADS)

Oron, Dan; Tenne, Ron; Israel, Yonatan; Silberberg, Yaron

2017-02-01

Far-field optical microscopy beyond the Abbe diffraction limit, making use of nonlinear excitation (e.g. STED), or temporal fluctuations in fluorescence (PALM, STORM, SOFI) is already a reality. In contrast, overcoming the diffraction limit using non-classical properties of light is very difficult to achieve due to the fragility of quantum states of light. Here, we experimentally demonstrate superresolution microscopy based on quantum properties of light naturally emitted by fluorophores used as markers in fluorescence microscopy. Our approach is based on photon antibunching, the tendency of fluorophores to emit photons one by one rather than in bursts. Although a distinctively quantum phenomenon, antibunching is readily observed in most common fluorophores even at room temperature. This nonclassical resource can be utilized directly to enhance the imaging resolution, since the non-classical far-field intensity correlations induced by antibunching carry high spatial frequency information on the spatial distribution of emitters. Detecting photon statistics simultaneously in the entire field of view, we were able to detect non-classical correlations of the second and third order, and reconstructed images with resolution significantly beyond the diffraction limit. Alternatively, we demonstrate the utilization of antibunching for augmenting the capabilities of localization-based superresolution imaging in the presence of multiple emitters, using a novel detector comprised of an array of single photon detectors connected to a densely packed fiber bundle. These features allow us to enhance the spatial and temporal resolution with which multiple emitters can be imaged compared with other techniques that rely on CCD cameras.

Design and characterization of a dead-time regime enhanced early photon projection imaging system

NASA Astrophysics Data System (ADS)

Sinha, L.; Fogarty, M.; Zhou, W.; Giudice, A.; Brankov, J. G.; Tichauer, K. M.

2018-04-01

Scattering of visible and near-infrared light in biological tissue reduces spatial resolution for imaging of tissues thicker than 100 μm. In this study, an optical projection imaging system is presented and characterized that exploits the dead-time characteristics typical of photon counting modules based on single photon avalanche diodes (SPADs). With this system, it is possible to attenuate the detection of more scattered late-arriving photons, such that detection of less scattered early-arriving photons can be enhanced with increased light intensity, without being impeded by the maximum count rate of the SPADs. The system has the potential to provide transmittance-based anatomical information or fluorescence-based functional information (with slight modification in the instrumentation) of biological samples with improved resolution in the mesoscopic domain (0.1-2 cm). The system design, calibration, stability, and performance were evaluated using simulation and experimental phantom studies. The proposed system allows for the detection of very-rare early-photons at a higher frequency and with a better signal-to-noise ratio. The experimental results demonstrated over a 3.4-fold improvement in the spatial resolution using early photon detection vs. conventional detection, and a 1000-fold improvement in imaging time using enhanced early detection vs. conventional early photon detection in a 4-mm thick phantom with a tissue-equivalent absorption coefficient of μa = 0.05 mm-1 and a reduced scattering coefficient of μs' = 5 mm-1.

Optronic System Imaging Simulator (OSIS): imager simulation tool of the ECOMOS project

NASA Astrophysics Data System (ADS)

Wegner, D.; Repasi, E.

2018-04-01

ECOMOS is a multinational effort within the framework of an EDA Project Arrangement. Its aim is to provide a generally accepted and harmonized European computer model for computing nominal Target Acquisition (TA) ranges of optronic imagers operating in the Visible or thermal Infrared (IR). The project involves close co-operation of defense and security industry and public research institutes from France, Germany, Italy, The Netherlands and Sweden. ECOMOS uses two approaches to calculate Target Acquisition (TA) ranges, the analytical TRM4 model and the image-based Triangle Orientation Discrimination model (TOD). In this paper the IR imager simulation tool, Optronic System Imaging Simulator (OSIS), is presented. It produces virtual camera imagery required by the TOD approach. Pristine imagery is degraded by various effects caused by atmospheric attenuation, optics, detector footprint, sampling, fixed pattern noise, temporal noise and digital signal processing. Resulting images might be presented to observers or could be further processed for automatic image quality calculations. For convenience OSIS incorporates camera descriptions and intermediate results provided by TRM4. For input OSIS uses pristine imagery tied with meta information about scene content, its physical dimensions, and gray level interpretation. These images represent planar targets placed at specified distances to the imager. Furthermore, OSIS is extended by a plugin functionality that enables integration of advanced digital signal processing techniques in ECOMOS such as compression, local contrast enhancement, digital turbulence mitiga- tion, to name but a few. By means of this image-based approach image degradations and image enhancements can be investigated, which goes beyond the scope of the analytical TRM4 model.

Self-Referenced Smartphone-Based Nanoplasmonic Imaging Platform for Colorimetric Biochemical Sensing.

PubMed

Wang, Xinhao; Chang, Te-Wei; Lin, Guohong; Gartia, Manas Ranjan; Liu, Gang Logan

2017-01-03

Colorimetric sensors usually suffer due to errors from variation in light source intensity, the type of light source, the Bayer filter algorithm, and the sensitivity of the camera to incoming light. Here, we demonstrate a self-referenced portable smartphone-based plasmonic sensing platform integrated with an internal reference sample along with an image processing method to perform colorimetric sensing. Two sensing principles based on unique nanoplasmonics enabled phenomena from a nanostructured plasmonic sensor, named as nanoLCA (nano Lycurgus cup array), were demonstrated here for colorimetric biochemical sensing: liquid refractive index sensing and optical absorbance enhancement sensing. Refractive indices of colorless liquids were measured by simple smartphone imaging and color analysis. Optical absorbance enhancement in the colorimetric biochemical assay was achieved by matching the plasmon resonance wavelength with the chromophore's absorbance peak wavelength. Such a sensing mechanism improved the limit of detection (LoD) by 100 times in a microplate reader format. Compared with a traditional colorimetric assay such as urine testing strips, a smartphone plasmon enhanced colorimetric sensing system provided 30 times improvement in the LoD. The platform was applied for simulated urine testing to precisely identify the samples with higher protein concentration, which showed potential point-of-care and early detection of kidney disease with the smartphone plasmonic resonance sensing system.

Rational Design and Synthesis of γFe2 O3 @Au Magnetic Gold Nanoflowers for Efficient Cancer Theranostics.

PubMed

Huang, Jie; Guo, Miao; Ke, Hengte; Zong, Cheng; Ren, Bin; Liu, Gang; Shen, He; Ma, Yufei; Wang, Xiaoyong; Zhang, Hailu; Deng, Zongwu; Chen, Huabing; Zhang, Zhijun

2015-09-09

An γFe2 O3 @Au core/shell-type magnetic gold nanoflower-based theranostic nano-platform is developed. It is integrated with ultrasensitive surface-enhanced Raman scattering imaging, high-resolution photo-acoustics imaging, real-time magnetic resonance imaging, and photothermal therapy capabilities. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Resolution Enhancement Algorithm for Spaceborn SAR Based on Hanning Function Weighted Sidelobe Suppression

NASA Astrophysics Data System (ADS)

Li, C.; Zhou, X.; Tang, D.; Zhu, Z.

2018-04-01

Resolution and sidelobe are mutual restrict for SAR image. Usually sidelobe suppression is based on resolution reduction. This paper provide a method for resolution enchancement using sidelobe opposition speciality of hanning window and SAR image. The method can keep high resolution on the condition of sidelobe suppression. Compare to traditional method, this method can enchance 50 % resolution when sidelobe is -30dB.

Single image super resolution algorithm based on edge interpolation in NSCT domain

NASA Astrophysics Data System (ADS)

Zhang, Mengqun; Zhang, Wei; He, Xinyu

2017-11-01

In order to preserve the texture and edge information and to improve the space resolution of single frame, a superresolution algorithm based on Contourlet (NSCT) is proposed. The original low resolution image is transformed by NSCT, and the directional sub-band coefficients of the transform domain are obtained. According to the scale factor, the high frequency sub-band coefficients are amplified by the interpolation method based on the edge direction to the desired resolution. For high frequency sub-band coefficients with noise and weak targets, Bayesian shrinkage is used to calculate the threshold value. The coefficients below the threshold are determined by the correlation among the sub-bands of the same scale to determine whether it is noise and de-noising. The anisotropic diffusion filter is used to effectively enhance the weak target in the low contrast region of the target and background. Finally, the high-frequency sub-band is amplified by the bilinear interpolation method to the desired resolution, and then combined with the high-frequency subband coefficients after de-noising and small target enhancement, the NSCT inverse transform is used to obtain the desired resolution image. In order to verify the effectiveness of the proposed algorithm, the proposed algorithm and several common image reconstruction methods are used to test the synthetic image, motion blurred image and hyperspectral image, the experimental results show that compared with the traditional single resolution algorithm, the proposed algorithm can obtain smooth edges and good texture features, and the reconstructed image structure is well preserved and the noise is suppressed to some extent.

Multiple template-based image matching using alpha-rooted quaternion phase correlation

NASA Astrophysics Data System (ADS)

DelMarco, Stephen

2010-04-01

In computer vision applications, image matching performed on quality-degraded imagery is difficult due to image content distortion and noise effects. State-of-the art keypoint based matchers, such as SURF and SIFT, work very well on clean imagery. However, performance can degrade significantly in the presence of high noise and clutter levels. Noise and clutter cause the formation of false features which can degrade recognition performance. To address this problem, previously we developed an extension to the classical amplitude and phase correlation forms, which provides improved robustness and tolerance to image geometric misalignments and noise. This extension, called Alpha-Rooted Phase Correlation (ARPC), combines Fourier domain-based alpha-rooting enhancement with classical phase correlation. ARPC provides tunable parameters to control the alpha-rooting enhancement. These parameter values can be optimized to tradeoff between high narrow correlation peaks, and more robust wider, but smaller peaks. Previously, we applied ARPC in the radon transform domain for logo image recognition in the presence of rotational image misalignments. In this paper, we extend ARPC to incorporate quaternion Fourier transforms, thereby creating Alpha-Rooted Quaternion Phase Correlation (ARQPC). We apply ARQPC to the logo image recognition problem. We use ARQPC to perform multiple-reference logo template matching by representing multiple same-class reference templates as quaternion-valued images. We generate recognition performance results on publicly-available logo imagery, and compare recognition results to results generated from standard approaches. We show that small deviations in reference templates of sameclass logos can lead to improved recognition performance using the joint matching inherent in ARQPC.

A new CAD approach for improving efficacy of cancer screening

NASA Astrophysics Data System (ADS)

Zheng, Bin; Qian, Wei; Li, Lihua; Pu, Jiantao; Kang, Yan; Lure, Fleming; Tan, Maxine; Qiu, Yuchen

2015-03-01

Since performance and clinical utility of current computer-aided detection (CAD) schemes of detecting and classifying soft tissue lesions (e.g., breast masses and lung nodules) is not satisfactory, many researchers in CAD field call for new CAD research ideas and approaches. The purpose of presenting this opinion paper is to share our vision and stimulate more discussions of how to overcome or compensate the limitation of current lesion-detection based CAD schemes in the CAD research community. Since based on our observation that analyzing global image information plays an important role in radiologists' decision making, we hypothesized that using the targeted quantitative image features computed from global images could also provide highly discriminatory power, which are supplementary to the lesion-based information. To test our hypothesis, we recently performed a number of independent studies. Based on our published preliminary study results, we demonstrated that global mammographic image features and background parenchymal enhancement of breast MR images carried useful information to (1) predict near-term breast cancer risk based on negative screening mammograms, (2) distinguish between true- and false-positive recalls in mammography screening examinations, and (3) classify between malignant and benign breast MR examinations. The global case-based CAD scheme only warns a risk level of the cases without cueing a large number of false-positive lesions. It can also be applied to guide lesion-based CAD cueing to reduce false-positives but enhance clinically relevant true-positive cueing. However, before such a new CAD approach is clinically acceptable, more work is needed to optimize not only the scheme performance but also how to integrate with lesion-based CAD schemes in the clinical practice.

Efficacy of model-based iterative reconstruction technique in non-enhanced CT of the renal tracts for ureteric calculi.

PubMed

Tan, T J; Lau, Kenneth K; Jackson, Dana; Ardley, Nicholas; Borasu, Adina

2017-04-01

The purpose of this study was to assess the efficacy of model-based iterative reconstruction (MBIR), statistical iterative reconstruction (SIR), and filtered back projection (FBP) image reconstruction algorithms in the delineation of ureters and overall image quality on non-enhanced computed tomography of the renal tracts (NECT-KUB). This was a prospective study of 40 adult patients who underwent NECT-KUB for investigation of ureteric colic. Images were reconstructed using FBP, SIR, and MBIR techniques and individually and randomly assessed by two blinded radiologists. Parameters measured were overall image quality, presence of ureteric calculus, presence of hydronephrosis or hydroureters, image quality of each ureteric segment, total length of ureters unable to be visualized, attenuation values of image noise, and retroperitoneal fat content for each patient. There were no diagnostic discrepancies between image reconstruction modalities for urolithiasis. Overall image qualities and for each ureteric segment were superior using MBIR (67.5 % rated as 'Good to Excellent' vs. 25 % in SIR and 2.5 % in FBP). The lengths of non-visualized ureteric segments were shortest using MBIR (55.0 % measured 'less than 5 cm' vs. ASIR 33.8 % and FBP 10 %). MBIR was able to reduce overall image noise by up to 49.36 % over SIR and 71.02 % over FBP. MBIR technique improves overall image quality and visualization of ureters over FBP and SIR.

Performance assessment of multi-frequency processing of ICU chest images for enhanced visualization of tubes and catheters

NASA Astrophysics Data System (ADS)

Wang, Xiaohui; Couwenhoven, Mary E.; Foos, David H.; Doran, James; Yankelevitz, David F.; Henschke, Claudia I.

2008-03-01

An image-processing method has been developed to improve the visibility of tube and catheter features in portable chest x-ray (CXR) images captured in the intensive care unit (ICU). The image-processing method is based on a multi-frequency approach, wherein the input image is decomposed into different spatial frequency bands, and those bands that contain the tube and catheter signals are individually enhanced by nonlinear boosting functions. Using a random sampling strategy, 50 cases were retrospectively selected for the study from a large database of portable CXR images that had been collected from multiple institutions over a two-year period. All images used in the study were captured using photo-stimulable, storage phosphor computed radiography (CR) systems. Each image was processed two ways. The images were processed with default image processing parameters such as those used in clinical settings (control). The 50 images were then separately processed using the new tube and catheter enhancement algorithm (test). Three board-certified radiologists participated in a reader study to assess differences in both detection-confidence performance and diagnostic efficiency between the control and test images. Images were evaluated on a diagnostic-quality, 3-megapixel monochrome monitor. Two scenarios were studied: the baseline scenario, representative of today's workflow (a single-control image presented with the window/level adjustments enabled) vs. the test scenario (a control/test image pair presented with a toggle enabled and the window/level settings disabled). The radiologists were asked to read the images in each scenario as they normally would for clinical diagnosis. Trend analysis indicates that the test scenario offers improved reading efficiency while providing as good or better detection capability compared to the baseline scenario.

Maximum entropy method applied to deblurring images on a MasPar MP-1 computer

NASA Technical Reports Server (NTRS)

Bonavito, N. L.; Dorband, John; Busse, Tim

1991-01-01

A statistical inference method based on the principle of maximum entropy is developed for the purpose of enhancing and restoring satellite images. The proposed maximum entropy image restoration method is shown to overcome the difficulties associated with image restoration and provide the smoothest and most appropriate solution consistent with the measured data. An implementation of the method on the MP-1 computer is described, and results of tests on simulated data are presented.