Breast Abnormality Detection Using LBP Variants and Discrete Wavelet Transform

In this paper, local directional position pattern (LDPP) and local ternary pattern (LTP) are selected for facial recognition method which are having many advantages over previous techniques like local binary pattern (LBP) and local directional pattern (LDP). The selected techniques of LDPP and LTP are estrangement in their algorithms which help solely to extract features out of an image. LDPP is a revised form of LDP. In a typical LDP, only the top edge direction was taken into consideration, but strength sign of the pixel was not considered which may result in same code for opposite kind of edge pixel. This snag is overcome by LDPP which is further concatenated with LTP for better feature extraction. Once features are extracted they are trained using deep belief network. In the experimental work 10 images of each expression i.e. angry, surprise, disgust, neutral, sad, smile are selected. LDPP and LTP are concatenated followed by principal component analysis (PCA) and general discriminant analysis (GDA). Further for training, Deep Belief Network (DBN) is used which eventually increases the recognition rate and achieve accuracy of 95.3% which was 89.3% without concatenating.

Objective: Visual descriptor methods like Local Binary Pattern (LBP) capture anatomical structures in captured images along with their disparities, which can be exploited by suitable methods for the diagnosis of medical anomalies. In our study, we have proposed a Local Mean Gradient Pattern (LMGP), based partly on LBP, a feature extraction algorithm for the classification of Computed Tomography (CT) images of the brain into normal, ischemic, or hemorrhage categories. Methods: The AISD and Kaggle datasets containing patients' brain CT scan images (acute ischemic stroke, hemorrhage, and normal cases) were taken. Initially, adaptive histogram equalization (AHE) techniques were applied as preprocessing operations to enhance the quality of the CT images. Furthermore, features were extracted from the preprocessed data using several feature extraction techniques, including our proposed LMGP feature descriptor. The features were then scaled using the standard scaling technique. Subsequently, preprocessed images were fed into different classifiers to build models for classifying brain CT scan images. Results: The effectiveness of our methodology LMGP was determined using different metrics, such as recall, precision, F1 score, logarithmic loss, accuracy (ACC), and area under the curve (ROC). Conclusively, LMGP performed best when the RBF-SVM classifier was used for the classification and gave an accuracy of 94% and 96% in the case of five-fold and ten-fold cross-validation, respectively. Conclusion: LMGP offers a distinctive and robust method of feature extraction from CT scan images by combining local information along with gradient change in pixels of the image. The efficacy of our proposed methodology (LMGP) was evaluated by using distinct classifiers, and the results were compared with eight different feature extraction methods. Overall, LMGP effectively outperformed all other feature descriptor methods in this study.

ABSTRACTObjectiveThe visual descriptor methods like Local Binary Pattern (LBP) capture anatomical structures in captured images along with their disparities, which can be exploited by suitable methods for the diagnosis of medical anomalies. We developed a Local Mean Gradient Pattern (LMGP), based partly on LBP, a feature extraction algorithm for the classification of Computed Tomography (CT) images of the brain into normal, ischemic, or hemorrhage categories.MethodsThe ASID dataset comprises of 397 acute ischemic stroke CT scan images and the Kaggle dataset consists of 200 CT scan images, out of which, 100 images were of the abnormal brain type (hemorrhage), and the remaining 100 images which don’t show any abnormalities were categorized as normal cases. The results of LMGP were compared with eight other feature extraction methods using linear, sigmoid, polynomial, and RBF kernels of the SVM classifier.ResultsThe effectiveness of our methodology was evaluated using recall, logarithmic loss, accuracy (ACC), confusion matrix and area under curve (ROC) metrics. The LMGP performed best when RBF-SVM was used for the classification and gave an accuracy of 93% and 95% in the case of five-fold and ten-fold cross-validation respectively. The ten-fold cross-validation gave a precision score of 0.9410, a recall score of 0.9521, an F1 score of 0.9458, and a negative log loss of -0.1645.ConclusionLMGP combines a unique and robust approach of CT scan image feature extraction by combining local information along with gradient change in pixels of the image. The present results of the study suggest the improved performance of the LMGP method over other methods compared in this study effectively.

As of 1992, breast cancer has been the second cause of death in Columbian women, with a rising trend in mortality due to this type of neoplasm (average annual rate 4.5*/100.000 inhabitants). Information about potential risk factors for breast cancer in Latin American countries is scarce. The objectives of the project were to test the breastfeeding protection against breast cancer and to establish the reproductive factors associated with breast cancer in Columbia. A hospital case-control study was carried out from July 1995 to March 1996 in Bogotá, Columbia, using paring by age groups. The study population consisted of 171 histopathologically confirmed cases and 171 controls. Reproductive history and sociodemographic data were collected through a questionnaire, and logistic regression models were used for statistical analysis of the data. The following associated factors were found as principal results: nuli-parousness as compared with women with over 3 children (OR=3.35 CI 1.40-8.0), age at first birth (OR=1.83 CI 0.70- 4.80), breast cancer history, breastfeeding the first child (OR=0.09 CI 0.01-0.64 for 1-11 months) and with a highly significant trend for accumulated breastfeeding above 24 months (p=0.001). This study indicates the importance of focusing on the promotion of prolonged breastfeeding by women identified as being at higher risk, and confirms that socio-economic level can determine life styles and reproductive events among women (such as breastfeeding time); this could explain the increase in breast cancer mortality in Latin American countries, similar to that in developed countries in terms of fertility and risk factors for breast cancer. The epidemiological information produced by this study will be useful for planning and carrying out early diagnosis and treatment of breast cancer in women identified as being at high risk of this disease.

Cohn et al. (2008) suggested that birth cohort trends in breast cancer rates for women under 50 years of age are consistent with declining use of DDT (dichloro-diphenyltrichloroethane) after 1959. They cited Weiss (2007) in claiming that increased detection and treatment of in situ breast cancer must be considered when interpreting recent trends in breast cancer mortality rates in young women. The remarks of Weiss (2007) relate to women 40–49 years of age, and earlier detection and improved treatment of breast cancer has had a marked impact on breast cancer mortality rates in these women since 1990 (Berry et al. 2005; Chu et al. 1996). The birth cohort trends relevant to examining the possible impact of childhood DDT exposure on U.S. breast cancer rates, however, were firmly established well before 1990 in women < 40 years of age (Tarone 2007). Cohn et al. (2007) reported a large increase in breast cancer risk estimates for p,p′-DDT [1,1,1-trichloro-2,2-bis(p-chlorophenyl)ethane] exposure with successive birth cohorts after 1930. Their reported odds ratio estimates by period of birth for the highest tertile of p,p′-DDT exposure were 0.6 for women born in 1931 or earlier (i.e., ≥ 14 years of age in 1945), 3.9 for women born in 1932–1937 (i.e., 8–13 years of age in 1945), 9.6 for women born in 1938–1941 (i.e., 4–7 years of age in 1945), and 11.5 for women born in 1942 or later (i.e., 0.25), and there was a marginally significant decrease in rates for women 35–39 years of age (p = 0.04). Thus the trends in breast cancer mortality rates among women born in 1930–1945 are not consistent with the sharply increasing trend in odds ratios for childhood DDT exposure by birth period reported by Cohn et al. (2007). The most recent mortality rate contributing to the reported regression analyses (corresponding to women in the 35- to 39-year age group born in 1945) was for 1983, well before improvements in detection and treatment would have had any impact on breast cancer mortality rates. Women born after 1945 were exposed to DDT for each of the first 13 years of life (and all years thereafter). In addition, DDT exposure increased from 1945 through 1959, when DDT use peaked (with dietary exposure peaking in 1965) (Wolff et al. 2005). If DDT exposure early in life markedly increases breast cancer risk, then some evidence of the increasing DDT use after 1945 might be expected in breast cancer mortality rate trends for young women born from 1946 through 1959 (Tarone 2007). Breast cancer mortality rates decreased significantly among women 20–24 years of age (p = 0.009) and 25–29 years of age (p = 0.0002) born between 1946 and 1959 (SEER 2006; Tarone 2007). The most recent rate contributing to these regression analyses was for 1987 (corresponding to women in the 25-to 29-year age group born in 1959). Breast cancer mortality rates decreased even more markedly (p < 0.0001) for women in the 30- to 34-year and 35- to 39-year age groups born from 1946 through 1959; some of the recent rates in these latter age groups were almost certainly affected by improved breast cancer detection and treatment, although decreasing trends were apparent in both age groups for rates well before 1990 (Tarone 2007). Thus, U.S. breast cancer mortality rates in women between the ages of 20 and 39 who were born between 1930 and 1959 show no evidence of an increase in breast cancer risk associated with their marked increase in DDT exposure during childhood. The observed birth cohort trends in breast cancer rates do not refute a possible association between childhood DDT exposure and breast cancer risk, and contrary to the implication of Cohn et al. (2008), no such claim was made in my earlier letter (Tarone 2008). The regression analyses reported above suffer the weaknesses of all ecologic analyses, and in fact, the decreasing birth cohort risk of breast cancer in baby boomers has been observed in spite of trends in established risk factors (e.g., parity, age at first birth, and oral contraceptive use) that would predict increasing breast cancer rates among U.S. women born after 1945. If, as suggested by Cohn et al. (2007), the public health significance of DDT exposure early in life is large, then this would provide additional evidence that the factor or factors responsible for the paradoxical decrease in birth cohort risk of breast cancer observed among U.S. baby boomers must have a very powerful impact on breast cancer etiology, large enough to turn an expected increasing trend in breast cancer rates among baby boomers into a decreasing trend.

A time for creative collaboration

Optimization and normalization strategies for long term untargeted HILIC-LC-qTOF-MS based metabolomics analysis: Early diagnosis of breast cancer

We propose a writer-specific off-line writer verification procedure to improve the reliability of the verification system. It has to be a challenging task, particularly in the off-line scenario, which uses images of the scanned document, where the dynamic information is not available. In this paper, we propose a local textural based feature Histogram of Oriented Gradients (HOG) along with gradient-based feature like local binary pattern (LBP). KNN, SMO and MLP classifiers are experimented within this work. These different classifiers are then trained then individually for each writer and they learn to verify a writer from another randomly selected writer. Our method achieves 89.62% accuracy using KNN on 100 writers database, whose metric is better than both SMO and MLP classifiers. The experimental results show that the two chosen sets of features for the writer verification problem provides improved accuracy and reduces the error rate.

It is still uncertain whether mammography is beneficial to women under 50 years of age. We report a follow-up of 4 1-year birth cohorts in 13 Finnish municipalities subjected to service screening. The women in these cohorts were born in even calendar years and they were 40-47 years old at the time of first screening, which was repeated every other year. At the beginning, 4,163 women were invited and 86% attended. Women were screened with mammography, physical breast examination and information on detection and early diagnosis of breast cancer by breast self-examination (BSE) was given. Incident cases of breast cancer and breast-cancer deaths were recorded. The expected numbers of incident breast-cancer cases and deaths from breast cancer were derived from control women who were residents of the same municipalities but who were born in adjacent calendar years (odd years) to those screened. In the screened cohorts 13 cancers were screen-detected, 32 cancers were interval cases and 8 cases were diagnosed among the non-attenders, while in the controls 85 cancers were detected during a 9-year follow-up from 1982 to 1990. One death from breast cancer occurred in the screened cohorts among cases diagnosed between 1982 and 1990, against 10 expected breast-cancer deaths during a 10-year follow-up from 1982 to 1991 of women initially free of breast cancer. Breast-cancer mortality in the screened cohorts was significantly lower than in the controls (Rate Ratio 0.11), but it is not clear how much of the reduction in mortality could be accounted for by the mammography itself and how much to other activities included in the screening programme (especially training in BSE) or to chance variation. It is unlikely that a programme sensitivity of 25% (13/53) would have resulted in 89% (100-11) effectiveness or reduction in the risk of death from breast cancer.

Effects of radiotherapy and of differences in the extent of surgery for early breast cancer on local recurrence and 15-year survival: an overview of the randomised trials

Does a young woman living with a smoker or taking a job working in a smoky bar have a greater chance of developing breast cancer? Some scientists believe that such situations can indeed raise a woman’s risk of developing breast cancer before the age of 50. Because epidemiological and toxicological studies show that women’s breast tissue may be especially sensitive to exposure to carcinogens prior to first pregnancy, these researchers contend that public education should be directed at alerting adolescents and young women to the potential risk. However, not everyone in the international public health community agrees that the evidence to date supports a link between passive smoking and breast cancer, and some say that women are being alarmed unnecessarily. This disagreement has sparked debate that is sometimes heated. The stakes are high because breast cancer is the most common cancer in women in industrialized countries, according to the WHO. It is the leading cancer killer of nonsmoking women, and second only to lung cancer deaths among women who smoke. Among the researchers interviewed for this article who disagree that there is enough evidence to link secondhand smoke (SHS) with breast cancer, the majority call the evidence to date “suggestive but not sufficient,” as the Surgeon General’s 2006 report, The Health Consequences of Involuntary Exposure to Tobacco Smoke, put it. That characterization is based largely on the fact that the research considered when the Surgeon General’s report was being amassed did not clearly link even active smoking to breast cancer. Researchers in this camp do, however, stress that ongoing campaigns to prohibit smoking in public will protect the whole of society against the wide variety of ills proven to be caused by SHS. These include lung cancer, cardiovascular disease, and sudden infant death syndrome, among others. A smaller group contends that the question of whether or not SHS causes breast cancer is a political issue with the potential to compromise the scientific process. “A premature decision about causality could jeopardize the credibility of the entire review process and all of the other, established effects of secondhand smoke,” says Michael Thun, national vice president of epidemiology and surveillance research for the American Cancer Society. Adds Valerie Beral, director of the University of Oxford Cancer Research UK Epidemiology Unit, “To prematurely come to conclusions about the causation when there is a big division in the scientific community . . . is bad science.” Thun debated the subject in a series of public forums held in conjunction with scientific meetings. Taking the opposing view was Kenneth C. Johnson, a research scientist with the Public Health Agency of Canada, who was one of the first scientists to discern a potential link. During the debates, Johnson pointed out there are about the same number of studies linking breast cancer to passive smoking as there were linking lung cancer to SHS in 1986, when the Surgeon General concluded that passive smoking caused lung cancer. Johnson also says that more of the breast cancer studies are statistically significant, and that the estimated risk for breast cancer is higher.

Objective: To analyze the trends of mortality and years of life lost (YLL) of breast cancer in women in Tianjin and provide references for the development of intervention strategies. Methods: The crude mortality rate, standard mortality rate, cumulative rate (0-74 years old) and truncated rate (35-64 years old) of breast cancer in women in Tianjin from 1999 to 2017 were calculated. The annual percentage change of the mortality rate and YLL rate were analyzed by Joinpoint regression. Results: From 1999 to 2017, a total of 8 356 deaths of breast cancer were reported in Tianjin, resulting in a YLL of 262 835.53 person-years. The average crude mortality rate was 9.15/100 000. The average age standardized rate(ASR) (World) was 6.14/100 000. The ratio of ASR (World) between urban and rural areas was 1.73∶1. The peak mortality ratio of age groups between urban area and rural area was 3.13∶1. From 1999 to 2017, both the crude mortality rate and ASR of breast cancer in Tianjin had rising trends. In 2017, the crude mortality rate and the ASR of breast cancer increased by 113.7% and 44.4% respectively compared with 1999. The increase of urban mortality mainly came from elderly group aged ≥75 years, and the mortality of young age groups in rural area showed an fast increases, which was most obvious in age group 45-59 years (average annual percentage change=3.6%, P<0.01). Conclusions: The mortality rate of breast cancer and disease burden in women in Tianjin are still in rapid increase. We should continue to implement the prevention and control strategies such as lifestyle intervention and screening of key groups. More attention need to be paid to the increase of breast cancer incidence in rural area.

Breast cancer surveillance programs for the general population are not adequate for the small number of women with hereditary breast and ovarian cancer syndrome. Breast cancer screening for women in Germany starts at the age of 50 years, but nearly half of all women with familial risk are already diagnosed with breast cancer at that time. Moreover, mammography alone is not suitable for an early diagnosis of breast cancer in young women from high-risk families. Their typical dense breast tissue causes a high rate of false-negative cases. Therefore, national and international prospective clinical trials were initiated to offer a multimodal breast cancer surveillance program including magnetic resonance tomography for the breast and semi-annual screening intervals to women with BRCA1/2 mutations and those from high-risk families who tested negative for BRCA1/2 mutations. This program will currently be evaluated by the 15 centers of the German Consortium for Hereditary Breast and Ovarian Cancer.

We present an extension of our previous work in [1] by investigating the use of Local Septenary Patterns (LSP) for breast density classification in mammograms. The LSP operator is a variant of Local Binary Patterns (LBP) inspired by Local Ternary Patterns (LTP) and Local Quinary patterns (LQP). The main extensions in our work are i) we investigate the use of a multi-resolution technique when extracting micro texture information, ii) we investigate different neighbourhood topologies as different ways of extracting texture features, and iii) we use an additional dataset called InBreast as well as the most popular dataset in the literature, which is the Mammographic Image Analysis Society (MIAS) to further evaluate the performance of the LSP operator.

ObjectiveMore than a third of women diagnosed with breast cancer in England, and over half of those who die from it, are over 70. The Be Clear on Cancer Breast Cancer in Women over 70 Campaign, running three times, 2014–2018, aimed to promote early diagnosis of breast cancer in England by raising symptom awareness and encouraging women to see their general practitioner (GP) without delay. We sought to establish whether the third campaign had successfully met its aims.MethodsMetrics covering the patient pathway, including symptom awareness, attending a GP practice with symptoms, urgent GP referral, diagnosis and stage of cancer, were assessed using national cancer databases and two household surveys.ResultsThe third campaign was associated with an increase in urgent cancer referrals, and therefore mammograms and ultrasounds performed. This was associated with an increase in breast cancers diagnosed. There was a delayed effect on GP attendances. Awareness of breast cancer prevalence for the 70‐and‐over age group improved. Impact on these metrics diminished across successive campaigns.ConclusionsFuture campaigns should focus on harder‐to‐reach women and include GPs as targets as this campaign showed a potential to affect referral behaviour.