Evaluation of Contrast Enhancement by Digital Equalization in Digital Mammography

Purpose: This study evaluated an algorithm based on a method of contrast enhancement by digital equalization (CEDE). Method: The algorithm was designed to enhance image contrast by employing digital equalization of digital mammograms. The CEDE algorithm was tested using ten mammograms with cancer (13 lesions) taken the University of South Florida data base, together with eight mammograms which only contained benign lesions. Three readers compared the processed images with the original mammograms for lesion conspicuity. A five point ranking scale was employed where a score of 3 corresponded to equal lesion visibility, ranks > 3 corresponded to superior lesion visibility, whereas ranks < 3 corresponded to markedly inferior lesion visibility. Results: The mean observer score for all lesions was always at least equal to that of the original digital mammogram (i.e., 3 or greater), and there was no evidence of any image distortion or other image processing artefacts. The mean rank (± standard deviation) for the 13 malignant lesions was 3.52 ± 0.38. The corresponding rank for the eight benign lesions was 3.33 ± 0.26. These differences were statistically significant in terms of standard error. Conclusion: The CEDE algorithm is capable of significantly enhancing lesion contrast in digital mammograms and our preliminary results indicate that this algorithm merits additional refinement and further (objective) evaluation

Simulated phantom images for optimizing wavelet-based image processing algorithms in mammography

Image processing techniques using wavelet signal analysis have shown some promise in mammography. It is desirable, however, to optimize these algorithms before subjecting them to clinical evaluation. In this study, computer simulated images were used to study the significance of all the parameters available in a multiscale wavelet image processing algorithm designed to enhance mammograms. Computer simulated images had a gaussian-shaped signal in half of the regions of interest and included added random noise. Signal intensity and noise levels were varied to determine the detection threshold contrast-to-noise ratio (CNR). An index of the ratio of output to input contrast to noise ratios was used to optimize a wavelet based image processing algorithm. Computed CNRs were generally found to correlate well with signal detection by human observers in both the original and processed images. Use of simulated phantom images enabled the parameters associated with multiscale wavelet based processing techniques to be optimized

Hexagonal wavelet processing of digital mammography

This paper introduces a novel approach for accomplishing mammographic feature analysis through overcomplete multiresolution representations. We show that efficient representations may be identified from digital mammograms and used to enhance features of importance to mammography within a continuum of scale-space. We present a method of contrast enhancement based on an overcomplete, non-separable multiscale representation: the hexagonal wavelet transform. Mammograms are reconstructed from transform coefficients modified at one or more levels by local and global non-linear operators. Multiscale edges identified within distinct levels of transform space provide local support for enhancement. We demonstrate that features extracted from multiresolution representations can provide an adaptive mechanism for accomplishing local contrast enhancement. We suggest that multiscale detection and local enhancement of singularities may be effectively employed for the visualization of breast pathology without excessive noise amplification

Quantitative evaluation of wavelet-based image processing algorithms

Wavelet analysis is currently being investigated as an image enhancement tool for use in mammography. Although this approach to image processing appears to have great promise, there remain major uncertainties regarding an optimal form of wavelet based algorithms. It is, therefore, desirable to have a quantitative method for evaluating a wavelet based image processing algorithm. Optimization of algorithms prior to evaluation using standard Receiver Operating Characteristic method is made possible. A mathematical method has been developed where the input signal is a gaussian with added random noise. An enhancement factor (EF) is obtained from input and output signal-to-noise ratios, SNRi and SNRo, (EF equals SNRo/SNRi). The development and testing of this method is described, and a practical application in given showing the major features of a wavelet based image processing algorithm based on the Frazier-Jawerth transform

Adaptive multiscale processing for contrast enhancement

This paper introduces a novel approach for accomplishing mammographic feature analysis through overcomplete multiresolution representations. We show that efficient representations may be identified from digital mammograms within a continuum of scale space and used to enhance features of importance to mammography. Choosing analyzing functions that are well localized in both space and frequency, results in a powerful methodology for image analysis. We describe methods of contrast enhancement based on two overcomplete (redundant) multiscale representations: (1) Dyadic wavelet transform (2) (phi) -transform. Mammograms are reconstructed from transform coefficients modified at one or more levels by non-linear, logarithmic and constant scale-space weight functions. Multiscale edges identified within distinct levels of transform space provide a local support for enhancement throughout each decomposition. We demonstrate that features extracted from wavelet spaces can provide an adaptive mechanism for accomplishing local contrast enhancement. We suggest that multiscale detection and local enhancement of singularities may be effectively employed for the visualization of breast pathology without excessive noise amplification

Comparison of a dyadic wavelet image enhancement algorithm with unsharp masking and median filtering for mammography

Image processing techniques using wavelet signal analysis techniques have shown promise in mammography. Wavelet algorithms are compared with traditional image enhancement techniques of unsharp masking and median filtering. Computer simulated phantom images were generated containing lesions mimicking masses and microcalcifications. The degree of image enhancement was evaluated by comparing processed and original signal-to-noise (SNR) ratios in such phantom images. Results obtained in this study suggest that image processing algorithms based on the wavelet transform are likely to enhance the visibility of low-contrast features in mammograms

Tritiated ethylketocyclazocine binding in rat brain: Differential distribution of binding sites across brain regions

In rat brain, 3H-EKC shows a relative regional distribution of binding which parallels that of 3H-morphine. Dynorphin(1-13) has a pattern similar to morphine and dissimilar to EKC in displacing the three labels. Dynorphin(1-13) is more potent against 3H-morphine than against 3H-EKC across brain regions while [beta]-endorphin competes better against 3H-EKC.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/23889/1/0000128.pd

Special considerations in the management of adult patients with acute leukaemias and myeloid neoplasms in the COVID-19 era: recommendations from a panel of international experts

This article is made available for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.The ongoing COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 is a global public health crisis. Multiple observations indicate poorer post-infection outcomes for patients with cancer than for the general population. Herein, we highlight the challenges in caring for patients with acute leukaemias and myeloid neoplasms amid the COVID-19 pandemic. We summarise key changes related to service allocation, clinical and supportive care, clinical trial participation, and ethical considerations regarding the use of lifesaving measures for these patients. We recognise that these recommendations might be more applicable to high-income countries and might not be generalisable because of regional differences in health-care infrastructure, individual circumstances, and a complex and highly fluid health-care environment. Despite these limitations, we aim to provide a general framework for the care of patients with acute leukaemias and myeloid neoplasms during the COVID-19 pandemic on the basis of recommendations from international experts

Burden of cancer in the Eastern Mediterranean Region, 2005-2015: findings from the Global Burden of Disease 2015 Study

Fitzmaurice C, Alsharif U, El Bcheraoui C, et al. Burden of cancer in the Eastern Mediterranean Region, 2005-2015: findings from the Global Burden of Disease 2015 Study. INTERNATIONAL JOURNAL OF PUBLIC HEALTH. 2018;63(Suppl. 1):151-164.To estimate incidence, mortality, and disability-adjusted life years (DALYs) caused by cancer in the Eastern Mediterranean Region (EMR) between 2005 and 2015. Vital registration system and cancer registry data from the EMR region were analyzed for 29 cancer groups in 22 EMR countries using the Global Burden of Disease Study 2015 methodology. In 2015, cancer was responsible for 9.4% of all deaths and 5.1% of all DALYs. It accounted for 722,646 new cases, 379,093 deaths, and 11.7 million DALYs. Between 2005 and 2015, incident cases increased by 46%, deaths by 33%, and DALYs by 31%. The increase in cancer incidence was largely driven by population growth and population aging. Breast cancer, lung cancer, and leukemia were the most common cancers, while lung, breast, and stomach cancers caused most cancer deaths. Cancer is responsible for a substantial disease burden in the EMR, which is increasing. There is an urgent need to expand cancer prevention, screening, and awareness programs in EMR countries as well as to improve diagnosis, treatment, and palliative care services

Alcohol use and burden for 195 countries and territories, 1990-2016 : a systematic analysis for the Global Burden of Disease Study 2016

Background Alcohol use is a leading risk factor for death and disability, but its overall association with health remains complex given the possible protective effects of moderate alcohol consumption on some conditions. With our comprehensive approach to health accounting within the Global Burden of Diseases, Injuries, and Risk Factors Study 2016, we generated improved estimates of alcohol use and alcohol-attributable deaths and disability-adjusted life-years (DALYs) for 195 locations from 1990 to 2016, for both sexes and for 5-year age groups between the ages of 15 years and 95 years and older. Methods Using 694 data sources of individual and population-level alcohol consumption, along with 592 prospective and retrospective studies on the risk of alcohol use, we produced estimates of the prevalence of current drinking, abstention, the distribution of alcohol consumption among current drinkers in standard drinks daily (defined as 10 g of pure ethyl alcohol), and alcohol-attributable deaths and DALYs. We made several methodological improvements compared with previous estimates: first, we adjusted alcohol sales estimates to take into account tourist and unrecorded consumption; second, we did a new meta-analysis of relative risks for 23 health outcomes associated with alcohol use; and third, we developed a new method to quantify the level of alcohol consumption that minimises the overall risk to individual health. Findings Globally, alcohol use was the seventh leading risk factor for both deaths and DALYs in 2016, accounting for 2.2% (95% uncertainty interval [UI] 1.5-3.0) of age-standardised female deaths and 6.8% (5.8-8.0) of age-standardised male deaths. Among the population aged 15-49 years, alcohol use was the leading risk factor globally in 2016, with 3.8% (95% UI 3.2-4-3) of female deaths and 12.2% (10.8-13-6) of male deaths attributable to alcohol use. For the population aged 15-49 years, female attributable DALYs were 2.3% (95% UI 2.0-2.6) and male attributable DALYs were 8.9% (7.8-9.9). The three leading causes of attributable deaths in this age group were tuberculosis (1.4% [95% UI 1. 0-1. 7] of total deaths), road injuries (1.2% [0.7-1.9]), and self-harm (1.1% [0.6-1.5]). For populations aged 50 years and older, cancers accounted for a large proportion of total alcohol-attributable deaths in 2016, constituting 27.1% (95% UI 21.2-33.3) of total alcohol-attributable female deaths and 18.9% (15.3-22.6) of male deaths. The level of alcohol consumption that minimised harm across health outcomes was zero (95% UI 0.0-0.8) standard drinks per week. Interpretation Alcohol use is a leading risk factor for global disease burden and causes substantial health loss. We found that the risk of all-cause mortality, and of cancers specifically, rises with increasing levels of consumption, and the level of consumption that minimises health loss is zero. These results suggest that alcohol control policies might need to be revised worldwide, refocusing on efforts to lower overall population-level consumption.Peer reviewe