Development of optimized memory based VLSI architecture with histogram analysis for image contrast enhancement

Contrast enhancement efficacy of iodinated contrast media: Effect of molecular structure on contrast enhancement

Nowadays, High Intensity Focused Ultrasound (HIFU) is a common surgery option for the treatment of uterine fibroids in China, the immediate response of which is clinically evaluated using Contrast Enhanced (CE) imaging. However, the injection of gadolinium with its potential adverse effect is of concern in CE and therefore, it deserves efforts to find a better imaging method without the need for contrast agent injection for this task. To assess the role of diffusion-weighted imaging (DWI) in evaluating the immediate therapeutic response of HIFU treatment for uterine fibroids in comparison with CE. 68 patients with 74 uterine fibroids receiving HIFU treatment were enrolled, and immediate treatment response was assessed using post-surgical DWI images. Semi-quantitative ordinal ablation quality grading and quantitative nonperfusion volume (NPV) measurement based on DWI and CE imaging were determined by two experienced radiologists. Agreement of ablation quality grading between DWI and CE was assessed using the weighted kappa coefficient, while intraobserver, interobserver and interprotocol agreements of NPV measurements within and between DWI and CE were evaluated using the intraclass correlation (ICC) and Bland-Altman analysis. Grading of immediate HIFU treatment response showed a moderate agreement between DWI and CE (weighted kappa = 0.446, p < 0.001). NPV measured in 65 fibroids with DWI of Grade 3~5 showed very high ICCs for the intraobserver and interobserver agreement within DWI and CE (all ICC > 0.980, p < 0.001) and also for the interprotocol agreement between DWI and CE (ICC = 0.976, p < 0.001). DWI could provide satisfactory ablation quality grading, and reliable NPV quantification results to assess immediate therapeutic responses of HIFU treatment for uterine fibroids in most cases, which suggests that non-contrast enhanced DWI might be potentially used as a more costeffective and convenient method in a large proportion of patients for this task replacing CE imaging.

Contrast-enhanced (CE) breast imaging involves the injection contrast agents (i.e., iodine) to increase conspicuity of malignant lesions. CE imaging may be used in conjunction with digital mammography (DM) or digital breast tomosynthesis (DBT) and has shown promise in improving diagnostic specificity. Both CE-DM and CE-DBT techniques require optimization as clinical diagnostic tools. Physical factors including x-ray spectra, subtraction technique, and the signal from iodine contrast, must be considered to provide the greatest object detectability and image quality. We developed a cascaded linear system model (CLSM) for the optimization of CE-DM and CE-DBT employing dual energy (DE) subtraction or temporal (TE) subtraction. We have previously developed a CLSM for DBT implemented with an a-Se flat panel imager (FPI) and filtered backprojection (FBP) reconstruction algorithm. The model is used to track image quality metrics - modulation transfer function (MTF) and noise power spectrum (NPS) - at each stage of the imaging chain. In this study, the CLSM is extended for CE breast imaging. The effect of x-ray spectrum (varied by changing tube potential and the filter) and DE and TE subtraction techniques on breast structural noise was measured was studied and included as a deterministic source of noise in the CLSM. From the two-dimensional (2D) and three-dimensional (3D) MTF and NPS, the ideal observer signal-to-noise ratio (SNR), also known as the detectability index (d'), may be calculated. Using d' as a FOM, we discuss the optimization of CE imaging for the task of iodinated contrast object detection within structured backgrounds. Increasing x-ray energy was determined to decrease the magnitude of structural noise and not its correlation. By performing DE subtraction, the magnitude of the structural noise was further reduced at the expense of increased stochastic (quantum and electronic) noise. TE subtraction exhibited essentially no residual structural noise at the expense of increased quantum noise, even over that of the DE case. For DE subtraction, optimization of dose weighting to the HE view (fh ) results in the minimization of quantum noise. Both subtraction weighting factor (wSub ) and the iodine contrast signal were dependent on the LE and HE x-ray spectra. To best detect a 5 mm Gaussian lesion with 5 mg/ml of iodine within a 4 cm thick breast, it was found that the high energy (HE) view should be acquired with a tube potential of 47 kVp (W/Ti spectrum) and the low energy (LE) view with a potential of 23 kVp (W/Rh spectrum). Due to the complete removal of structural noise, TE subtraction produced much higher d' than DE subtraction both as a function of mean glandular dose and iodine concentration. We have shown the effect of increasing x-ray energy as well as projection domain subtraction on breast structural noise. Further, we have exhibited the utility of the CLSM for DE and TE subtraction CE imaging in the optimization of imaging parameters such as x-ray energy, fh , and wSub as well as guiding the understanding of their effects on image contrast and noise.

The aim of this study was to evaluate the degree of hepatic enhancement and image quality in patients with cirrhosis or chronic hepatitis who underwent multiphasic contrast-enhanced dynamic imaging on MDCT at least twice using standard (300 mg I/mL) and higher (370 mg I/mL) iodine concentrations in contrast medium during follow-up periods. This study included 20 patients with chronic liver diseases who underwent at least two multiphasic contrast-enhanced dynamic MDCT examinations using 100 mL of standard (300 mg I/mL = group A) and higher (370 mg I/mL = group B) iodine concentrations in contrast medium. After we obtained unenhanced CT scans, we performed multiphasic scanning at 30 sec (arterial phase), 60 sec (portal phase), and 180 sec (late phase) after the start of contrast medium injection. The CT values of hepatic parenchyma, abdominal aorta, and portal vein were measured. The mean enhancement value was defined as the difference in CT values between unenhanced and contrast-enhanced images. Visual image quality was also assessed on the basis of the degree of hepatic and vascular enhancement, rated on a 4-point scale. The mean hepatic parenchyma enhancement values in group B was significantly greater (p < 0.001) than those in group A during the portal phase (43.8 +/- 8.2 H vs 36.2 +/- 7.3 H) and the late phase (33.7 +/- 7.0 H vs 27.3 +/- 3.9 H), but the difference on the arterial phase images between the two groups (9.4 +/- 3.2 H vs 8.3 +/- 2.5 H) was not significant. The mean aorta-to-liver contrast during the arterial phase in group B was significantly higher (p < 0.001) than that in group A (236 +/- 40 H vs 193 +/- 32 H). For qualitative analysis, the mean visual scores for hepatic parenchyma and vasculature enhancement in group B were significantly higher than those in group A in arterial phase (p < 0.018), portal phase (p < 0.0001), and late phase (p < 0.0001). In the same patients with chronic liver diseases, a higher iodine concentration (370 mg I/mL) in the contrast medium improves contrast enhancement of liver parenchyma in the portal phase and late phase images, improves overall image quality, and helps improve diagnostic accuracy for liver diseases on multiphasic contrast-enhanced dynamic MDCT.

The aim of this study was to describe the changes in the MR appearance of painful lesions of the spine before and after treatment in 18 patients with multiple myeloma and to correlate these changes with the clinical response to treatment. Eighteen patients with multiple myeloma and tumor nodules in the spine had MR imaging of the same site in the spine before and after treatment. Unenhanced T1- and T2-weighted spin-echo images, dynamic ultrafast low-angle shot (turbo-FLASH) images before and after IV bolus injection of paramagnetic contrast material, and contrast-enhanced T1-weighted spin-echo images were obtained. Characteristic signal and contrast enhancement before and after treatment were compared and were correlated with clinical data and the results of immunochemical and pathologic tests. Changes in signal intensity and enhancement of the lesions occurred after treatment in 14 of 18 patients. The characteristics of the lesions after treatment had three patterns: (1) rim enhancement or no enhancement of the lesions, (2) early enhancing lesions associated with other nonenhancing lesions or lesions with rim enhancement, and (3) no change from the enhancement pattern seen before treatment. In 13 of 18 patients, these patterns correlated well with the response to treatment. A discrepancy was observed in five patients. The MR appearance of spinal myeloma is different before and after treatment. MR images, particularly contrast-enhanced images, may be helpful in monitoring the response to treatment of focal bone lesions of myeloma.

For successful abdominal radiotherapy it is crucial to have a clear tumor definition and an accurate characterization of the motion. While dynamic contrast-enhanced (DCE) MRI aids tumor visualization, it is often hampered by motion artifacts. 4D-MRI characterizes this motion, but often lacks the contrast to clearly visualize the tumor. This dual requirement is challenging due to time constraints. Here, we propose combining both into a single acquisition by reconstructing the data in various ways in order to achieve both high spatio-temporal resolution DCE-MRI and accurate 4D-MRI motion estimates.A 5 min T1-weigthed DCE acquisition was collected in five renal-cell carcinoma patients and simulated in a digital phantom. Data were acquired continuously using a 3D golden angle radial stack-of-stars acquisition. This enabled three types of reconstruction; (1) a high spatio-temporal resolution DCE time series, (2) a 5D reconstruction and (3) a contrast-enhanced 4D-MRI for motion characterization. Motion extracted from the 4D- and 5D-MRI was compared with a separately acquired 4D-MRI and additional 2D cine MR imaging.Simulations on XCAT showed that 5D reconstructions severely underestimated motion (), whereas contrast-enhanced 4D-MRI only underestimated motion by . This was confirmed in the in vivo data where motion of the contrast-enhanced 4D-MRI was approximately smaller than the motion in the 2D cine MRI (5.8 mm versus 6.5 mm), but equal to a separately acquired 4D-MRI (5.8 mm versus 5.9 mm). 5D reconstructions underestimated the motion by more than , but minimized respiratory-induced blurring in the contrast enhanced images. DCE time-series demonstrated clear tumor visualization and contrast enhancement throughout the entire field-of-view.DCE- and 4D-MRI can be integrated into a single acquisition that enables different reconstructions with complementary information for abdominal radiotherapy planning and, in an MRI-guided treatment, precise motion information, input for motion models, and rapid feedback on the contrast enhancement.

The purpose of this study was to assess the potential for improved lesion detection in the posterior disk attachment and its surrounding tissue in temporomandibular disorders when gadolinium-enhanced MR imaging performed with fat suppression is used. Forty-five patients underwent MR imaging with conventional T1- and T2-weighted, gadolinium-enhanced T1-weighted, and gadolinium-enhanced fat-suppressed spin-echo imaging sequences. Qualitative and quantitative assessments of the contrast enhancement of each type of imaging were also performed. The contrast-enhanced fat-suppressed T1-weighted imaging sequence had several advantages over the other imaging techniques in detecting abnormalities of the posterior disk attachment and in detecting bone marrow lesions in the mandibular condyle. The most significant advantage was better enhancement of lesion conspicuity. The diagnostic accuracy of contrast-enhanced fat-suppressed imaging was 77% versus 70% for conventional contrast-enhanced imaging. The kappa value for interobserver agreement was .95 for contrast-enhanced fat-suppressed imaging and .72 for conventional contrast-enhanced imaging. Contrast-enhanced fat-suppressed T1-weighted spin-echo MR imaging is a valuable technique for visualizing the extent and degree of lesions in the posterior disk attachment and bone marrow lesions in the mandibular condyle.

Objective To investigate the application value of contrast-enhanced transrectal ultrasound (CE-TRUS) in differential diagnosis of prostate benign and malignant lesions. Methods A retrospective analysis of patients with prostate lesions detected by CE-TRUS from January 2014 to December 2016 in Southwest Hospital of Third Military Medical University was performed. Seventy-two cases of prostate disease with 88 lesions were confirmed by transrectal prostate biopsy under ultrasound guidance. The age of patients with benign and malignant lesions, serum prostate specific antigen (PSA), and the size of prostate and prostate inner gland were compared by independent sample t test. Pathologic results of transrectal prostate biopsy under ultrasound guidance were used as diagnostic gold standard, and the sensitivity, specificity and accuracy of CE-TRUS in diagnosis of benign and malignant prostate lesions were calculated. Results Sixty-seven lesions in 52 patients were benign prostatic diseases, and 21 lesions in 20 patients were prostate cancer in this study. The size of prostate and prostate inner gland were not different between patients with prostate cancer and benign prostatic diseases [(58.33±34.99) cm3 vs (57.14±24.42) cm3, t=0.185, P=0.854; (34.98±19.96) cm3 vs (33.89±17.65) cm3, t=0.213, P=0.832]. Most of prostate cancer lesions were in prostate outer gland area (15/21), and contrast-enhanced ultrasound imaging showed contrast enhancement increased mostly in arterial phase and faded faster than the surrounding tissues (16/21). However, most of prostate benign lesions were in prostate inner gland (47/67), and contrast-enhanced ultrasound imaging showed contrast enhancement was mostly equal with the surrounding tissue in arterial phase and faded the same as the surrounding tissues in venous phase (47/67). Pathologic results of transrectal prostate biopsy under ultrasound guidance were used as diagnostic gold standard, the sensitivity of CE-TRUS in diagnosis of benign and malignant prostate lesions was 85.71%, the specificity was 91.04%, and the accuracy was 89.77%. Two lesions were in prostate inner and outer gland border areas in the three missed prostate cancer lesions, and Gleason scores were all medium and high differentiated group. Six prostate benign lesions were diagnosed as malignant lesions, five lesions were confirmed prostate hyperplasia with chronic prostatitis and one was confirmed granulomatous inflammation with coagulation necrosis by transrectal prostate biopsy under ultrasound guidance. Conclusion CE-TRUS can effectively identify prostate benign and malignant lesions, and provides reliable information for accurate diagnosis of prostate cancer. Key words: Prostatic neoplasms; Ultrasonography; Contrast media; Diagnosis, differential

In this paper, an intelligent method for image contrast enhancement in real time digital video applications is proposed. This new technique is based on the generation of adaptive transfer functions by using Neural Network. The method is designed in order to be implemented in digital television systems, based on Thin Film Transistor Liquid Cristal Displays (TFT-LCD), that has become the dominant technology in consumer electronics. The method provides the required amount of contrast enhancement for every image according to real time analysis of brightness and contrast in the video frame information, then a different contrast enhancement transfer curve for each image is generated. The statistical information is extracted by histogram analysis from current or previous image frames. Technological factors are considered where it is applied, as well as aspects of the visual perception within a non-controlled environment, which is the case of the consumer environment. The method is based on the design of a general transfer function model that compensates the decrement in gray scale dynamic range in images representation which is a consequence of the TFT-LCD technology limits; in particular the light leakage from the panel backlight sources of the Cold Cathode Fluorescent Light (CCFL) or the LED type, as well as an unsuitable dynamic control of backlight intensity. Using subjective methods for image quality, the contrast is enhanced in a set of representative images for different degrees of brightness and contrast, a unique transfer function is obtained for each representative image. This set of transfer functions, as well as the statistic of the pixel values distribution from each image frame are used as an input - output pattern during the training of a neural network. On the basis of the experimentation, an evaluation and comparative analysis takes place between the functions of transformation obtained by subjective method of image quality and the curves obtained through the trained neural network.

Early detection of breast cancer in the mammograms is very essential in the field of medicine. Contrast enhancement for the detection of micro calcification of mammograms based on the Histogram Modified Contrast Limited Adaptive Histogram Equalization (HM-CLAHE) is presented. Histogram equalization is an effective and simple technique for contrast enhancement. The standard histogram equalization (HE) usually results in excessive contrast enhancement because of lack of control on the level of enhancement. The Histogram Modified Contrast Limited Adaptive Histogram Equalization (HM CLAHE) is proposed in this paper to adjust the level of contrast enhancement, which in turn gives the resultant image a strong contrast and brings the local details for more relevant interpretation. It incorporates both histogram modifications as an optimization technique and Contrast Limited Adaptive Histogram Equalization. This method is tested for Mias mammogram images. The performance of this method is determined using the parameter like Enhancement Measure (EME). From the subjective and quantitative measures it is interesting that this proposed technique provides better contrast enhancement with preserving the local information of the mammogram images.

Blackberry (Rubus spp.): a pH-dependent oral contrast medium for gastrointestinal tract images by magnetic resonance imaging

Low light images suffer from a low dynamic range and severe noise due to low signal-to-noise ratio (SNR). In this paper, we propose joint contrast enhancement and noise reduction of low light images via just-noticeable-difference (JND) transform. We adopt the JND transform to achieve both contrast enhancement and noise reduction based on human visual perception. First, we generate a JND map based on an the human visual system (HVS) response model from foreground and background luminance, called JND transform. Second, for base image, we perform perceptual contrast enhancement based on luminance adaptation to effectively allocate a dynamic range to each gray level while preventing under enhancement (tone distortion) and over-enhancement. Third, we refine the JND map using Weber's law, luminance adaptation and visual masking. Weber's law enhances the JND map based on the luminance variation after contrast enhancement. Luminance adaptation suppresses noise for smooth regions, while visual masking enforces detail enhancement for textural regions. Fourth, we perform inverse JND transform to generate the enhanced luma channel from the JND map and base image. Finally, we conduct chroma denoising by transferring texture information of the enhanced luma channel to the chroma channels with guided filtering. Experimental results show that the proposed method achieves both contrast enhancement and noise reduction for low light images as well as outperforms state-of-the-art methods in terms of quantitative measurements.

Contrast-Enhanced Ultrasound Imaging Detects Intraplaque Neovascularization in an Experimental Model of Atherosclerosis

Iodinated contrast agent is frequently used in computed tomography (CT) imaging to enhance organ contrast enhancement and improve diagnostic sensitivity. Despite this importance, there currently is a lack of standardization in contrast administration protocol across institutions, leading to many safety and clinical diagnostic risks. To solve this, we built three liver contrast enhancement/perfusion models: two using simple linear regression and another by combining a pre-existing pharmacokinetics mathematical model with clinical data with the eventual goal of individualizing contrast administration protocol to optimize contrast-enhanced CT imaging for each patient. These models primarily use patient attributes, such as height, weight, sex, age and contrast administration information, and bolus tracking information to make such predictions. 418 Chest/Abdomen/Pelvis CT scans were used in this study. 75% of cases were used to train these models and the rest were used to test the prediction accuracy. Pearson’s correlation coefficient test was used to find the correlations between the patient attributes and contrast enhancement in liver parenchyma. Weight, height, BMI, and lean body mass were found to be statistically significant predictors for contrast enhancement (P<0.05), with weight as the strongest predictor. Of the predictive models, we found that including bolus tracking information increases predictive accuracy (r2=0.75 v. 0.42) and that in the absence of bolus tracking information, combining clinical data with pre-existing pharmacokinetics model may provide the needed enhancement curve.

Small hepatocellular carcinomas in cirrhosis: differences in contrast enhancement effects between helical CT and MR imaging during multiphasic dynamic imaging