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.

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 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.

Aggregation-induced T_(1)/T_(2)contrast enhancement for magnetic resonance imaging-guided intraoperative surgery

Magnetic resonance imaging(MRI)plays an important role in precision medicine that is hampered by the lack of contrast agents with high efficiency and the ability to translate diagnostic accuracy into therapeutic intervention.Herein,we demonstrate a DNA-based MRI probe that overcomes previous single-mode enhancement and provides a mechanism of action for aggregationinduced dual-modal MRI signal enhancement.A facile method is developed to produce aggregated T_(1)/T_(2)dual-modal NaGdF_(4):Dy@PDA-DNA(PDA=polydopamine)MRI probes.When aggregated,this probe can further amplify MRI signal intensity and exhibit improved geometrical and positional stability in vivo.The performance of the NaGdF_(4):Dy@PDA-DNA MRI probe toward MRI-guided preoperative planning and visualization-guided surgery is verified using an orthotopic tumor-bearing mouse model.The result shows that the rapid metabolism of the degraded probe leads to the mitigation of long-term toxic effects.Therefore,the developed high-performance MRI probe is of great significance for enhancing MRI diagnostic accuracy into precision medical therapeutic interventions.

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.

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.

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 5 ps seed pulse is amplified from 60 pJ to 300μJ with an 8.6 ps/3 mJ pump laser in a signal stage of short pulse non-collinear optical parametric chirped pulse amplification. The total gain is more than 10~6 and the rms energy stability is under 1.35%. The contrast ratio is higher than 10~8 within a scale of 20 ps before the main pulse. Consequently, the improvement factor of the signal contrast is approximately equal to the gain 10~6 outside the pump window.

An Artificial Intelligence-Based Framework for Fruits Disease Recognition Using Deep Learning

Fruit infections have an impact on both the yield and the quality of the crop.As a result,an automated recognition system for fruit leaf diseases is important.In artificial intelligence(AI)applications,especially in agriculture,deep learning shows promising disease detection and classification results.The recent AI-based techniques have a few challenges for fruit disease recognition,such as low-resolution images,small datasets for learning models,and irrelevant feature extraction.This work proposed a new fruit leaf leaf leaf disease recognition framework using deep learning features and improved pathfinder optimization.Three fruit types have been employed in this work for the validation process,such as apple,grape,and Citrus.In the first step,a noisy dataset is prepared by employing the original images to learn the designed framework better.The EfficientNet-B0 deep model is fine-tuned on the next step and trained separately on the original and noisy data.After that,features are fused using a serial concatenation approach that is later optimized in the next step using an improved Path Finder Algorithm(PFA).This algorithm aims to select the best features based on the fitness score and ignore redundant information.The selected features are finally classified using machine learning classifiers such as Medium Neural Network,Wide Neural Network,and Support Vector Machine.The experimental process was conducted on each fruit dataset separately and obtained an accuracy of 100%,99.7%,99.7%,and 93.4%for apple,grape,Citrus fruit,and citrus plant leaves,respectively.A detailed analysis is conducted and also compared with the recent techniques,and the proposed framework shows improved accuracy.

Quantitative Assessment of the Effect of Nitric Oxide Synthase Inhibition on Tumor Vascular Activity Using Dynamic Contrast-Enhanced Computed Tomography

Purpose: The purpose of this study was to develop a method to quantitatively assess the effect of nitric oxide synthase (NOS) inhibition on tumor vascular activity using dynamic contrast-enhanced computed tomography (DCE-CT) and to investigate its usefulness using animal experiments. Mate-rials and Methods: The DCE-CT studies were performed in anesthetized Fisher rats bearing tumors using a 4-row multi-slice CT. The scanning started 4 s before a bolus injection of iodinated contrast agent (CA) (150 mgI/kg) from the tail vein using an automatic injector and lasted 60 s at 1-s in-tervals. The contrast enhancement (CE) images were generated by subtracting the CT images before and after the administration of CA. First, the DCE-CT studies were performed before and 15, 30, and 45 min after administration of N-nitro-L-arginine (L-NNA) (1, 3, and 10 mg/kg) or vehicle, and the relative CE values were calculated by normalizing the CE image at each time point by that obtained from the first DCE-CT study. Second, we investigated the case when L-arginine (L-ARG) (200 mg/kg) and L-NNA (1, 3, and 10 mg/kg) were administered after the first and second DCE-CT studies, respectively. Third, we investigated the case when L-NNA (1, 3, and 10 mg/kg) and L-ARG (200 mg/kg) were administered after the first and second DCE-CT studies, respectively. Finally, we investigated the case when L-NNA (1, 3, and 10 mg/kg) and L-ARG (200 mg/kg) were administered simultaneously after the first DCE-CT study. Results: The relative CE value significantly decreased after L-NNA administration in a dose-dependent manner (p-values = 0.0074 and <0.0001 for 0 vs. 3 mg/kg and 0 vs. 10 mg/kg, respectively, at 15 min, 0.0003 and <0.0001 for 0 vs. 3 mg/kg and 0 vs. 10 mg/kg, respectively, at 30 min, and 0.0367 and 0.0004 for 0 vs. 3 mg/kg and 0 vs. 10 mg/kg, respectively, at 45 min). When L-ARG was administered prior to the administration of 1 mg/kg L-NNA, the relative CE value at 45 min was significantly higher than that at 15 min. When L-ARG was administered after L-NNA administration, there was no significant difference between the relative CE values at 15 min and 45 min. These results suggest that when using L-NNA in combination with L-ARG, their effect on tumor vascular activity differs depending on the order of their administration. When L-NNA and L-ARG were administered simultaneously, there was a tendency for the relative CE value to be higher than that when only L-NNA was administered, at all injected doses of L-NNA. Conclusion: Our method using DCE-CT is useful for monitoring the effect of NOS inhibition on tumor vascular activity and for determining the optimal injected dose and timing of NOS inhibitors for anticancer therapy.

Statistical Histogram Decision Based Contrast Categorization of Skin Lesion Datasets Dermoscopic Images

Most of the melanoma cases of skin cancer are the life-threatening form of cancer.It is prevalent among the Caucasian group of people due to their light skin tone.Melanoma is the second most common cancer that hits the age group of 15–29 years.The high number of cases has increased the importance of automated systems for diagnosing.The diagnosis should be fast and accurate for the early treatment of melanoma.It should remove the need for biopsies and provide stable diagnostic results.Automation requires large quantities of images.Skin lesion datasets contain various kinds of dermoscopic images for the detection of melanoma.Three publicly available benchmark skin lesion datasets,ISIC 2017,ISBI 2016,and PH2,are used for the experiments.Currently,the ISIC archive and PH2 are the most challenging and demanding dermoscopic datasets.These datasets’pre-analysis is necessary to overcome contrast variations,under or over segmented images boundary extraction,and accurate skin lesion classification.In this paper,we proposed the statistical histogram-based method for the pre-categorization of skin lesion datasets.The image histogram properties are utilized to check the image contrast variations and categorized these images into high and low contrast images.The two performance measures,processing time and efficiency,are computed for evaluation of the proposed method.Our results showed that the proposed methodology improves the pre-processing efficiency of 77%of ISIC 2017,67%of ISBI 2016,and 92.5%of PH2 datasets.

A Post-Processing Algorithm for Boosting Contrast of MRI Images

Low contrast of Magnetic Resonance(MR)images limits the visibility of subtle structures and adversely affects the outcome of both subjective and automated diagnosis.State-of-the-art contrast boosting techniques intolerably alter inherent features of MR images.Drastic changes in brightness features,induced by post-processing are not appreciated in medical imaging as the grey level values have certain diagnostic meanings.To overcome these issues this paper proposes an algorithm that enhance the contrast of MR images while preserving the underlying features as well.This method termed as Power-law and Logarithmic Modification-based Histogram Equalization(PLMHE)partitions the histogram of the image into two sub histograms after a power-law transformation and a log compression.After a modification intended for improving the dispersion of the sub-histograms and subsequent normalization,cumulative histograms are computed.Enhanced grey level values are computed from the resultant cumulative histograms.The performance of the PLMHE algorithm is comparedwith traditional histogram equalization based algorithms and it has been observed from the results that PLMHE can boost the image contrast without causing dynamic range compression,a significant change in mean brightness,and contrast-overshoot.

Application of contrast-enhanced intraoperative ultrasonography in the decision-making about hepatocellular carcinoma operation

AIM:To evaluate the detection and differentiation ability of contrast-enhanced intraoperative ultrasonography(CE-IOUS) in hepatocellular carcinoma(HCC) operations.METHODS:Clinical data of 50 HCC patients were retrospective analyzed.The sensitivity,specificity,false negative and false positive rates of contrast enhanced magnetic resonance imaging(CE-MRI),IOUS and CEIOUS were calculated and compared.Surgical strategy changes due to CE-IOUS were analyzed.RESULTS:Lesions detected by CE-MRI,IOUS and CEIOUS were 60,97 and 85 respectively.The sensitivity,specificity,false negative rate,false positive rate of CEMRI were 98.2%,98.6%,98.6%,60.0%,respectively;for IOUS were 50.0%,90.9%,1.8%,1.4%,respectively;and for CE-IOUS were 1.4%,40.0%,50.0%,9.1%,respectively.The operation strategy of 9(9/50,18.0%) cases was changed according to the results of CE-IOUS.CONCLUSION:Compared with CE-MRI,CE-IOUS performs better in detection and differentiation of small metastasis and regenerative nodules.It plays an important role in the decision-making of HCC operation.

Effect of contrast-enhanced ultrasound on differential diagnosis of intrahepatic cholangiocarcinoma and arterial phase enhanced hepatic inflammatory lesions

Objective: To investigate differential diagnosis between intrahepatic cholangiocarcinoma(ICC) and arterial phase enhanced hepatic inflammatory lesions in patients without liver cirrhosis using contrast-enhanced ultrasound(CEUS).Methods: ICC and hepatic inflammatory lesions cases with CEUS and pathological diagnosis between Sep 2013 and Oct 2016 were investigated retrospectively. Imaging features of conventional ultrasound and CEUS were analyzed. The parameters of time intensity curve(TIC), including the arrival time, peak intensity(PI) in the lesions, the starting time for washout, and the intensity difference at 3 min(ΔI_3) after contrast agent infection between the lesion and the liver parenchyma, were compared between ICC and hepatic inflammatory lesions.Results: Twenty-five ICC and fifteen inflammatory patients were included in this study. Seventeen ICC(68.0%)and two inflammatory cases(13.3%) showed bile duct dilatation on conventional ultrasound. Using CEUS, three ICC cases(12.0%) were misdiagnosed as inflammatory lesions and three inflammatory lesions(20.0%) as ICC; two ICC(8.0%) and one inflammatory case(6.7%) could not be made definite diagnosis. Washout started at 34.5±3.5 s and 61.5±12.9 s for ICC and inflammatory lesions respectively(P<0.001). The intensity difference between lesion and liver parenchyma at 3 min after contrast agent injection was 10.8±3.1 dB in ICC and 4.2±2.3 dB in inflammatory group(P<0.001). The sensitivity and specificity differentiating ICC and inflammatory lesions were76% and 87% if the cut-off value of the intensity difference was 7.7 d B.Conclusions: Combined with TIC analysis, and particularly with the characteristic of the early-starting and obvious washout in ICC, CEUS can be useful in differential diagnosis between hepatic inflammatory lesions and ICC.

Can contrast enhanced ultrasound differentiate intrahepatic cholangiocarcinoma from hepatocellular carcinoma?

BACKGROUND Hepatocellular carcinoma(HCC)and intrahepatic cholangiocarcinoma(ICC)differ in treatment and prognosis,warranting an effective differential diagnosis between them.The LR-M category in the contrast-enhanced ultrasound(CEUS)liver imaging reporting and data system(LI-RADS)was set up for lesions that are malignant but not specific to HCC.However,a substantial number of HCC cases in this category elevated the diagnostic challenge.AIM To investigate the possibility and efficacy of differentiating ICC from HCC classified in the LR-M category according to the CEUS LI-RADS.METHODS Patients with complete CEUS records together with pathologically confirmed ICC and LR-M HCC(HCC classified in the CEUS LI-RADS LR-M category)between January 2015 and October 2018 were included in this retrospective study.Each ICC was assigned a category as per the CEUS LI-RADS.The enhancement pattern,washout timing,and washout degree between the ICC and LR-M HCC were compared using theχ2 test.Logistic regression analysis was used for prediction of ICC.Receiver operating characteristic(ROC)curve analysis was used to investigate the possibility of LR-M criteria and serum tumor markers in differentiating ICC from LR-M HCC.RESULTS A total of 228 nodules(99 ICCs and 129 LR-M HCCs)in 228 patients were included.The mean sizes of ICC and LR-M HCC were 6.3±2.8 cm and 5.5±3.5 cm,respectively(P=0.03).Peripheral rim-like arterial phase hyperenhancement(APHE)was detected in 50.5%(50/99)of ICCs vs 16.3%(21/129)of LR-M HCCs(P<0.001).Early washout was found in 93.4%(93/99)of ICCs vs 96.1%(124/129)of LR-M HCCs(P>0.05).Marked washout was observed in 23.2%(23/99)of ICCs and 7.8%(10/129)of LR-M HCCs(P=0.002),while this feature did not show up alone either in ICC or LR-M HCC.Homogeneous hyperenhancement was detected in 15.2%(15/99)of ICCs and 37.2%(48/129)of LR-M HCCs(P<0.001).The logistic regression showed that rim APHE,carbohydrate antigen 19-9(CA 19-9),and alpha fetoprotein(AFP)had significant correlations with ICC(r=1.251,3.074,and-2.767,respectively;P<0.01).Rim APHE presented the best enhancement pattern for diagnosing ICC,with an area under the ROC curve(AUC)of 0.70,sensitivity of 70.4%,and specificity of 68.8%.When rim hyperenhancement was coupled with elevated CA 19-9 and normal AFP,the AUC and sensitivity improved to 0.82 and 100%,respectively,with specificity decreasing to 63.9%.CONCLUSION Rim APHE is a key predictor for differentiating ICC from LR-M HCC.Rim APHE plus elevated CA 19-9 and normal AFP is a strong predictor of ICC rather than LR-M HCC.Early washout and marked washout have limited value for the differentiation between the two entities.

Differentiation of atypical hepatic hemangioma from liver metastases: Diagnostic performance of a novel type of color contrast enhanced ultrasound

BACKGROUND In clinical practice,the diagnosis is sometimes difficult with contrast-enhanced ultrasound(CEUS)when the case has an atypical perfusion pattern.Color parametric imaging(CPI)is an analysis software for CEUS with better detection of temporal differences in CEUS imaging using arbitrary colors.It measures the differences in arrival time of the contrast agent in lesions so that the perfusion features of atypical hemangioma and colorectal cancer(CRC)liver metastasis can be distinguished.AIM To evaluate the role of a novel type of CPI of CEUS in the differential diagnosis of atypical hemangioma from liver metastases in patients with a history of CRC.METHODS From January 2016 to July 2018,42 patients including 20 cases of atypical hemangioma and 22 cases of liver metastases from CRC were enrolled.These patients had a mean age of 60.5±9.3 years(range:39-75 years).All patients received ultrasound,CEUS and CPI examinations.Resident and staff radiologists independently and retrospectively reviewed CEUS and CPI images.Two sets of criteria were assigned:(1)Routine CEUS alone;and(2)CEUS and CPI.The diagnostic sensitivity,specificity,accuracy and receiver operating characteristic(ROC)curve of resident and staff radiologists were analyzed.RESULTS The following CPI features were significantly different between liver hemangioma and liver metastases analyzed by staff and resident radiologists:Peripheral nodular enhancement(65%-70.0%vs 4.5%-13.6%,P<0.001,P=0.001),mosaic/chaotic enhancement(5%-10%vs 68.2%-63.6%,P<0.001,P<0.001)and feeding artery(20%vs 59.1%-54.5%,P=0.010,P=0.021).CPI imaging offered significant improvements in detection rates compared with routine CEUS in both resident and staff groups.By resident radiologists,the specificity and accuracy of CEUS+CPI were significantly increased compared with that of CEUS(77.3%vs 45.5%,P=0.030;78.6%vs 50.0%,P=0.006).In addition,the area under the curve(AUC)of CEUS+CPI was significantly higher than that of CEUS(0.803 vs 0.757,P=0.036).By staff radiologists,accuracy was improved in CEUS+CPI(81.0%vs 54.8%,P=0.010),whereas no significant differences in specificity and sensitivity were found(P=0.144,P=0.112).The AUC of CEUS+CPI was significantly higher than that of CEUS(0.890 vs 0.825,P=0.013)by staff radiologists.CONCLUSION Compared with routine CEUS,CPI could provide specific information on the hemodynamic features of liver lesions and help to differentiate atypical hemangioma from liver metastases in patients with CRC,even for senior radiologists.

Contrast-enhanced ultrasound imaging for intestinal lymphoma

BACKGROUND Intestinal lymphoma is a rare tumor.Contrast-enhanced ultrasound(CEUS)findings of intestinal lymphoma have not been reported previously,and the relationship between CEUS and clinicopathological features and prognostic factors is still unknown.AIM To describe the B-mode US and CEUS features of intestinal lymphoma and investigate the correlation of CEUS and histopathological features.METHODS This was a single-center retrospective study.Eighteen patients with histologically confirmed intestinal lymphoma underwent B-mode US and CEUS examinations between October 2016 and November 2019.We summarized the features of Bmode US and CUES imaging of intestinal lymphoma and compared the frequency of tumor necrosis in intestinal lymphomas with reference to different pathological subtypes(aggressive or indolent)and clinical stage(early or advanced).The time–intensity curve parameters of CEUS were also compared between patients with normal and elevated serum lactate dehydrogenase.RESULTS In B-mode imaging,four patterns were observed in intestinal lymphoma:Mass type(12/18,66.7%),infiltration type(1/18,5.6%),mesentery type(4/18,22.2%)and mixed type(1/18,5.6%).All cases were hypoechoic and no cystic areas were detected.On CEUS,most cases(17/18,94.4%)showed arterial hyperechoic enhancement.All cases showed arterial enhancement followed by venous wash out.A relatively high rate of tumor necrosis(11/18,61.1%)was observed in this study.Tumor necrosis on CEUS was more frequent in aggressive subtypes(10/13,76.9%)than in indolent subtypes(1/5,20.0%)(P=0.047).There were no correlations between tumor necrosis and lesion size and Ann Arbor stage.There was no significant difference in time–intensity curve parameters between normal and elevated lactate dehydrogenase groups.CONCLUSION B-mode US and CEUS findings of intestinal lymphoma are characteristic.We observed a high rate of tumor necrosis,which appeared more frequently in aggressive pathological subtypes of intestinal lymphoma.

Contrast enhanced ultrasound in diagnosing liver lesion that spontaneously disappeared:A case report

BACKGROUND Focal liver lesions(FLLs)are abnormal masses that are distinguishable from the surrounding liver parenchyma,solid or cystic and may be benign or malignant.They are usually detected incidentally on abdominal examinations.The classification of FLLs is very important as it directly determines the diagnosis and treatment of patients.CASE SUMMARY A 46-year-old male patient was admitted into the hospital with tarry stool,during the investigation of this issue an incidental FLL was detected.Upon further investigation of this“incidentaloma”computerized tomography and magnetic resonance imaging reached contradictory conclusions.The lesion was then further investigated using contrast-enhanced ultrasound(CEUS)with an initial diagnosis of idiopathic FLL was acquired and observation of the FLL over time need for final diagnosis,however in the follow up the FLL disappeared spontaneously.CONCLUSION CEUSs value for characterization of FLLs is undeniable,especially when other methods produce inconsistent results,is undeniable but with its limitations.Why and how the FLL disappeared is not known,and can be only hypothesized it was a pseudolesion.

Application Value of Contrast-Enhanced Ultrasound in the Diagnosis of Breast Lesions

Objective:To explore the value and effect of contrast-enhanced ultrasound in the diagnosis of breast lesions.Methods:Seventy-two patients with breast lesions in Shaanxi Provincial People’s Hospital from June 2020 to December 2021 were selected as the research subjects.All 72 patients met the diagnostic criteria of breast lesions.Two patients with incomplete clinical data were excluded;hence,there were 70 patients remaining.The diagnostic results of the two examination methods and the diagnostic value of the joint examination for breast lesions were analyzed and compared.Results:The results of benign,malignant,missed,and misdiagnosed breast lesions by contrast-enhanced ultrasound were 31,32,6,and 1 cases,respectively,accounting for 44.29%,45.71%,8.57%,and 1.43%,respectively.The results of benign,malignant,missed,and misdiagnosed breast lesions by ultrasound automatic volume imaging were 21,24,17,and 8 cases,respectively,accounting for 30.00%,34.28%,24.29%,and 11.43%,respectively.There were statistical differences between the two groups for missed diagnosis and misdiagnosis,but there was no significant difference between the two groups for benign and malignant lesions.The accuracy,sensitivity,and specificity of contrast-enhanced ultrasound were 87.69%,83.62%,and 83.45%,respectively;the accuracy,sensitivity,and specificity of ultrasound automatic volume imaging were 71.39%,68.99%,and 74.69%,respectively;the accuracy,sensitivity,and specificity of contrast-enhanced ultrasound combined with ultrasound automatic volume imaging were 96.29%,92.68%,and 91.78%,respectively.Conclusion:Contrast-enhanced ultrasonography has a high clinical application value and a low inspection error rate in the diagnosis of breast lesions.It merits clinical advancement since it helps doctors diagnose and treat breast lesions more effectively.