Is it a normal phenomenon for pediatric patients to have brain leptomeningeal contrast enhancement on 3-tesla magnetic resonance imaging?

Determining whether sevoflurane sedation in children leads to“pseudo”prominent leptomeningeal contrast enhancement(pLMCE)on 3 Tesla magnetic resonance imaging will help reduce overdiagnosis by radiologists and clarify the pathophysiological changes of pLMCE.

An improved detail enhancement algorithm based on difference curvature and contrast field

The gradient image is always sensitive to noise in image detail enhancement. To overcome this shortage, an improved detail enhancement algorithm based on difference curvature and contrast field is proposed. Firstly, the difference curvature is utilized to determine the amplification coefficient instead of the gradient. This new amplification function of the difference curvature takes more neighboring points into account, it is therefore not sensitive to noise. Secondly, the contrast field is nonlinearly amplified according to the new amplification coefficient. And then, with the enhanced contrast field, we construct the energy functional. Finally, the enhanced image is reconstructed by the variational method. Experimental results of standard testing image and industrial X-ray image show that the proposed algorithm can perform well on increasing contrast and sharpening edges of images while suppressing noise at the same time.

Research on Wavelet-Based Algorithm for Image Contrast Enhancement

A novel wavelet-based algorithm for image enhancement is proposed in the paper. On the basis of multiscale analysis, the proposed algorithm solves efficiently the problem of noise over-enhancement, which commonly occurs in the traditional methods for contrast enhancement. The decomposed coefficients at same scales are processed by a nonlinear method, and the coefficients at different scales are enhanced in different degree. During the procedure, the method takes full advantage of the properties of Human visual system so as to achieve better performance. The simulations demonstrate that these characters of the proposed approach enable it to fully enhance the content in images, to efficiently alleviate the enhancement of noise and to achieve much better enhancement effect than the traditional approaches. Key words wavelet transform - image contrast enhancement - multiscale analysis CLC number TP 391 Foundation item: Supported by the National Natural Science Foundation of China (69931010)Biography: Wu Ying-qian (1974-), male, Ph. D, research direction: image processing, image compression and wavelet.

Enhancement Technique of Image Contrast using New Histogram Transformation

This paper presents a preprocessing technique that can provide the improved quality of image robust to illumination changes. First, in order to enhance the image contrast, we proposed new adaptive histogram transformation combining histogram equalization and histogram specification. Here, by examining the characteristic of histogram distribution shape, we determine the appropriate target distribution. Next, applying the histogram equalization with an image histogram, we have obtained the uniform distribution of pixel values, and then we have again carried out the histogram transformation using an inverse of target distribution function. Finally we have conducted various experiments that can enhance the quality of image by applying our method with various standard images. The experimental results show that the proposed method can achieve moderately good image enhancement results.

Dynamic contrast enhanced ultrasound in differential diagnosis of hepatocellular carcinoma: A systematic review and meta-analysis

BACKGROUND Non-invasive differential diagnosis between hepatocellular carcinoma(HCC)and other liver cancer(i.e.cholangiocarcinoma or metastasis)is highly challenging and definitive diagnosis still relies on histological exam.The patterns of enhancement and wash-out of liver nodules can be used to stratify the risk of malignancy only in cirrhotic patients and HCC frequently shows atypical features.Dynamic contrast-enhanced ultrasound(DCEUS)with standardized software could help to overcome these obstacles,providing functional and quantitative parameters and potentially improving accuracy in the evaluation of tumor perfusion.AIM To explore clinical evidence regarding the application of DCEUS in the differential diagnosis of liver nodules.METHODS A comprehensive literature search of clinical studies was performed to identify the parameters of DCEUS that could relate to histological diagnosis.In accordance with the study protocol,a qualitative and quantitative analysis of the evidence was planned.RESULTS Rise time was significantly higher in HCC patients with a standardized mean difference(SMD)of 0.83(95%CI:0.48-1.18).Similarly,other statistically significant parameters were mean transit time local with a SMD of 0.73(95%CI:0.20-1.27),peak enhancement with a SMD of 0.37(95%CI:0.03-0.70),area wash-in area under the curve with a SMD of 0.47(95%CI:0.13-0.81),wash-out area under the curve with a SMD of 0.55(95%CI:0.21-0.89)and wash-in and wash-out area under the curve with SMD of 0.51(95%CI:0.17-0.85).SMD resulted not significant in fall time and wash-in rate,but the latter presented a trend towards greater values in HCC compared to intrahepatic cholangiocarcinoma.CONCLUSION DCEUS could improve non-invasive diagnosis of HCC,leading to less liver biopsy and early treatment.This quantitative analysis needs to be applied on larger cohorts to confirm these preliminary results.

High-Stability High-Energy Picosecond Optical Parametric Chirped Pulse Amplifier as a Preamplifier in Nd：Glass Petawatt System for Contrast Enhancement

We demonstrate a novel picosecond optical parametric preamplification to generate high-stability, high-energy and high-contrast seed pulses. The 5ps seed pulse is amplified from 60pJ to 300μJ with an 8.6ps/ 3mJ pump laser in a signal stage of short pulse non-collinear optical parametric chirped pulse amplification. The total gain is more than 106 and the rms energy stability is under 1.35%. The contrast ratio is higher than 10s within a scale of 20ps before the main pulse. Consequently, the improvement factor of the signal contrast is approximately equal to the gain 106 outside the pump window.

Correlation of Enhancement Degree on Contrast-enhanced Ultrasound with Histopathology of Carotid Plaques and Serum High Sensitive C-Reactive Protein Levels in Patients Undergoing Carotid Endarterectomy

This study was undertaken to investigate the correlation of the enhancement degree on contrast-enhanced ultrasound(CEUS) with the histopathology of carotid plaques and the serum high sensitive C-reactive protein(hs-CRP) levels in patients undergoing carotid endarterectomy(CEA). Carotid CEUS was performed preoperatively in 115 patients who would undergo CEA, and the enhancement degree of the carotid plaques was evaluated by both the visual semiquantitative analysis and the quantitative time-intensity curve analysis. Serum hs-CRP levels were detected using the particle-enhanced immunoturbidimetric assay also before the operation. Additionally, the carotid plaque samples were subjected to histopathological examination postoperatively. The density of neovessels and the number of macrophages in the plaques were assessed by immunohistochemistry. The results showed that among the 115 patients, grade 0 plaque contrast enhancement was noted in 35 patients, grade 1 in 48 patients and grade 2 in 32 patients. The degree of plaque enhancement, the density of neovessels, the number of macrophages, and the hs-CRP levels were highest in the grade 2 patients. Correlation analysis showed that the enhancement degree of the carotid plaques was closely related to the immunohistochemical parameters of the plaques and the serum hs-CRP levels. It was suggested that the carotid plaque enhancement on CEUS can be used to evaluate the vulnerability of carotid plaques.

A Novel Approach for Enhancement of Geometric and Contrast Resolution Properties of Low Contrast Images

The present work encompasses a new image enhancement algorithm using newly constructed Chebyshev fractional order differentiator. We have used Chebyshev polynomials to design Chebyshev fractional order differentiator. We have generated the high pass filter corresponding to it. The designed filters are applied for decomposing the input image into four bands and low-low(L-L) sub-band is updated using correction coefficients. Reconstructed image with updated L-L sub-band provides the enhanced image. The visual results obtained are encouraging for image enhancement. The applicability of the developed algorithm is illustrated on three different test images.The effects of order of differentiation on the edges of images have also been presented and discussed.

A New Method of CT Medical Images Contrast Enhancement

A new method of contrast enhancement is proposed in the paper using multiscale edge representation of images, and is applied to the field of CT medical image processing. Comparing to the traditional Window technique, our method is adaptive and meets the demand of radiology clinics more better. The clinical experiment results show the practicality and the potential applied value of our method in the field of CT medical images contrast enhancement.

Contrast Correction Using Hybrid Statistical Enhancement on Weld Defect Images

Luminosity and contrast variation problems are among the most challenging tasks in the image processing field,significantly improving image quality.Enhancement is implemented by adjusting the dark or bright intensity to improve the quality of the images and increase the segmentation performance.Recently,numerous methods had been proposed to normalise the luminosity and contrast variation.A new approach based on a direct technique using statistical data known as Hybrid Statistical Enhancement(HSE)is presented in this study.TheHSE method uses themean and standard deviation of a local and global neighbourhood and classified the pixel into three groups;the foreground,border,and problematic region(contrast&luminosity).The datasets,namely weld defect images,were utilised to demonstrate the effectiveness of the HSE method.The results from the visual and objective aspects showed that the HSE method could normalise the luminosity and enhance the contrast variation problem effectively.The proposed method was compared to the two(2)populor enhancement methods which is Homomorphic Filter(HF)and Difference of Gaussian(DoG).To prove the HSE effectiveness,a few image quality assessments were presented,and the results were discussed.The HSE method achieved a better result compared to the other methods,which are Signal Noise Ratio(8.920),Standard Deviation(18.588)and Absolute Mean Brightness Error(9.356).In conclusion,implementing the HSE method has produced an effective and efficient result for background correction and quality images improvement.

Contrast enhancement methods in sodium MR imaging: a new emerging technique

Background: In the last decade, sodium mag-netic resonance imaging was investigated for its potential as a functional cardiac imaging tool for ischemia. Later interest was developed in contrast enhancement for intracellular sodium. Little success was reported to suppress extracellular sodium resulting in the intracellular sodium MRI image acquisition using quantum filters or sodium transition states as contrast properties. Now its clinical application is ex-panding as a new challenge in brain and other cancer tumors. Contrast enhancement: We highlight the physical principles of sodium MRI in three different pulse sequences using filters (single quantum, multiple quantum, and triple quantum) meant for sodium contrast enhancement. The optimization of scan parameters, i.e. times of echo delay (TE), inversion recovery (TI) periods, and utility of Dysprosium (DyPPP) shift contrast agents, enhances contrast in sodium MRI images. Inversion recovery pulse sequence without any shift reagent measures the intracellular sodium concentration to evaluate ischemia, apoptosis and membrane integrity. Membrane integrity loss, apoptosis and malignancy are results of growth factor loss and poor epithelial capability related with MRI visible intracellular sodium concentration. Applications and limitations: The sodium MR imaging technical advances reduced scan time to distinguish intracellular and extracellular sodium signals in malignant tumors by use of quantum filter techniques to generate 3D sodium images without shift regents. We observed the association of malignancy with increased TSC, and reduced apoptosis and epithelial growth factor in breast cancer cells. The validity is still in question. Conclusion: Different modified sodium MRI pulse sequences are research tools of sodium contrast enhancement in brain, cardiac and tumor imaging. The optimized MRI scan pa-rameters in quantum filter techniques generate contrast in intracellular sodium MR images without using invasive contrast shift agents. Still, validity and clinical utility are in

CNN-Based Forensic Method on Contrast Enhancement with JPEG Post-Processing

As one of the most popular digital image manipulations,contrast enhancement(CE)is frequently applied to improve the visual quality of the forged images and conceal traces of forgery,therefore it can provide evidence of tampering when verifying the authenticity of digital images.Contrast enhancement forensics techniques have always drawn significant attention for image forensics community,although most approaches have obtained effective detection results,existing CE forensic methods exhibit poor performance when detecting enhanced images stored in the JPEG format.The detection of forgery on contrast adjustments in the presence of JPEG post processing is still a challenging task.In this paper,we propose a new CE forensic method based on convolutional neural network(CNN),which is robust to JPEG compression.The proposed network relies on a Xception-based CNN with two preprocessing strategies.Firstly,unlike the conventional CNNs which accepts the original image as its input,we feed the CNN with the gray-level co-occurrence matrix(GLCM)of image which contains CE fingerprints,then the constrained convolutional layer is used to extract high-frequency details in GLCMs under JPEG compression,finally the output of the constrained convolutional layer becomes the input of Xception to extract multiple features for further classification.Experimental results show that the proposed detector achieves the best performance for CE forensics under JPEG post-processing compared with the existing methods.

Contrast Enhancement Using Weighted Coupled Histogram Equalization with Laplace Transform

Histogram equalization is a traditional algorithm improving the image contrast,but it comes at the cost of mean brightness shift and details loss.In order to solve these problems,a novel approach to processing foreground pixels and background pixels independently is proposed and investigated.Since details are mainly contained in the foreground,the weighted coupling of histogram equalization and Laplace transform were adopted to balance contrast enhancement and details preservation.The weighting factors of image foreground and background were determined by the amount of their respective information.The proposed method was conducted to images acquired from CVG⁃UGR and US⁃SIPI image databases and then compared with other methods such as clipping histogram spikes,histogram addition,and non⁃linear transformation to verify its validity.Results show that the proposed algorithm can effectively enhance the contrast without introducing distortions,and preserve the mean brightness and details well at the same time.

A General Framework of Reversible Data Hiding with Controlled Contrast Enhancement

This paper proposes a two-step general framework for reversible data hiding(RDH)schemes with controllable contrast enhancement.The first step aims at preserving visual perception as much as possible on the basis of achieving high embedding capacity(EC),while the second step is used for increasing image contrast.In the second step,some peak-pairs are utilized so that the histogram of pixel values is modified to perform histogram equalization(HE),which would lead to the image contrast enhancement.However,for HE,the utilization of some peak-pairs easily leads to over-enhanced image contrast when a large number of bits are embedded.Therefore,in our proposed framework,contrast over-enhancement is avoided by controlling the degree of contrast enhancement.Since the second step can only provide a small amount of data due to controlled contrast enhancement,the first one helps to achieve a large amount of data without degrading visual quality.Any RDH method which can achieve high EC while preserve good visual quality,can be selected for the first step.In fact,Gao et al.’s method is a special case of our proposed framework.In addition,two simple and commonly-used RDH methods are also introduced to further demonstrate the generalization of our framework.

Derivation of Optimal Global Equalization Function with Variable Size Block Based Local Contrast Enhancement

A conventional global contrast enhancement is difficult to apply in various images because image quality and contrast enhancement are dependent on image characteristics largely. And a local contrast enhancement not only causes a washed-out effect, but also blocks. To solve these drawbacks, this paper derives an optimal global equalization function with variable size block based local contrast enhancement. The optimal equalization function makes it possible to get a good quality image through the global contrast enhancement. The variable size block segmentation is firstly exeoated using intensity differences as a measure of similarity. In the second step, the optimal global equalization function is obtained from the enhanced contrast image having variable size blocks. Conformed experiments have showed that the proposed algorithm produces a visually comfortable result image.

Association of Renal Volume with the Degree of Aortic Contrast Enhancement in Abdominal CT

To assess the correlation of renal volume measured on CT with aortic contrast enhancement on the hepatic arterial phase of dynamic CT, 64 consecutive patients (34 men, 30 women) were retrospectively examined. Renal volumes were measured on CT. The aortic contrast enhancement was inversely correlated with renal medullary volume (r = -0.52, p 0.0001), and renal cortical volume (r = -0.3, p = 0.02). Renal volume may have inverse correlation with aortic contrast enhancement on the hepatic arterial phase of dynamic CT. This might call for adjustment of contrast material dose based in part on renal volume in the future.

A Bi-Histogram Shifting Contrast Enhancement for Color Images

Recent contrast enhancement(CE)methods,with a few exceptions,predominantly focus on enhancing gray-scale images.This paper proposes a bi-histogram shifting contrast enhancement for color images based on the RGB(red,green,and blue)color model.The proposed method selects the two highest bins and two lowest bins from the image histogram,performs an equalized number of bidirectional histogram shifting repetitions on each RGB channel while embedding secret data into marked images.The proposed method simultaneously performs both right histogram shifting(RHS)and left histogram shifting(LHS)in each histogram shifting repetition to embed and split the highest bins while combining the lowest bins with their neighbors to achieve histogram equalization(HE).The least maximum number of histograms shifting repetitions among the three RGB channels is used as the default number of histograms shifting repetitions performed to enhance original images.Compared to an existing contrast enhancement method for color images and evaluated with PSNR,SSIM,RCE,and RMBE quality assessment metrics,the experimental results show that the proposed method's enhanced images are visually and qualitatively superior with a more evenly distributed histogram.The proposed method achieves higher embedding capacities and embedding rates in all images,with an average increase in embedding capacity of 52.1%.

Reversible Data Hiding with Contrast Enhancement Using Bi-histogram Shifting and Image Adjustment for Color Images

Prior versions of reversible data hiding with contrast enhancement(RDHCE)algorithms strongly focused on enhancing the contrast of grayscale images.However,RDHCE has recently witnessed a rise in contrast enhance-ment algorithms concentrating on color images.This paper implies a method for color images that uses the RGB(red,green,and blue)color model and is based on bi-histogram shifting and image adjustment.Bi-histogram shifting is used to embed data and image adjustment to achieve contrast enhancement by adjusting the images resulting from each channel of the color images before combining them to generate the final enhanced image.Images are first divided into three channels-R,G,and B-and the Max,Med,and Min channels are then determined from these.Before histogram shifting,some calculations are done to determine how many iterations there will be for each channel.The images are adjusted to improve visual quality in the enhanced images after data has been embedded in each channel.The experimental results show that the enhanced images produced by the proposed method are qualitatively and aesthetically superior to those produced by some earlier methods,and their quality was assessed using PSNR,SSIM,RCE,RMBE,and CIEDE2000.The embedding rate obtained by the suggested method is acceptable.

Improved Image Contrast Enhancement Based on Local Standard Deviation and Compared with Other Algorithms

An adaptive contrast enhancement (ACE) algorithm is presented in this paper, in which the contrast gain is determined by mapping the local standard deviation (LSD) histogram of an image to a Gaussian distribution function. The contrast gain is nonlinearly adjusted to avoid noise overenhancement and ringing artifacts while improving the detail contrast with less computational burden. The effectiveness of our method is demonstrated with radiological images and compared with other algorithms.

Preoperative detecting metastases of cervical cancer in pelvic and para-aortic lymph nodes:comparison of integrated ^(18)F-FDG PET/CT with or without contrast enhancement

Purpose: Compared the performance of contrast-enhanced PET/CT and non-enhanced PET/CT for preoperatively detecting pelvic and para-aortic lymph node metastases in patients with cervical cancer. Methods: This prospective study included 72 patients with clinically M0 cervical cancer. They underwent surgery within two weeks of PET/CT imaging. Imaging consisted of a whole-body PET/CT protocol without intravenous contrast, followed by abdominal and pelvic PET/CT protocol including contrast-enhanced CT. We compared the diagnostic efficiency between the methods on per-patient and per-lesion basis. Results: Patient-based analysis showed that the sensitivity, specificity, and accuracy of contrast-enhanced PET/CT were 63.6% (14/22), 94.0% (47/50), and 84.7%(61/72), respectively, whereas those of non-enhanced PET/CT were 54.5% (12/22), 88.0% (44/50), and 77.8% (56/72), respectively, and those of enhanced CT alone were 36.4% (8/22), 80.0% (40/50), and 66.7% (48/72), respectively. Lesion-based analysis showed that the sensitivity, specificity, and accuracy of contrast-enhanced PET/CT were 77.7% (87/112), 98.7%(938/950), and 96.5% (1025/1062), respectively, whereas those of non-enhanced PET/CT were 69.6% (78/112), 97.5% (926/950), and 94.5% (1004/1062), respectively, and those of enhanced CT were 54.4% (61/112), 96.1% (913/950), and 91.7% (974/1062), respectively. Contrast-enhanced PET/CT had the best sensitivity, specificity and accuracy. Although patient-based analysis showed no significant difference between contrast-enhanced PET/CT and non-enhanced PET/CT (p =0.540, 0.295 and 0.286), the specificity and accuracy of these two methods were significantly different on lesion-based analysis (p =0.043 and 0.027).