Similarity Measurement of Breast Cancer Mammographic Images Using Combination of Mesh Distance Fourier Transform and Global Features

Similarity measurement in breast cancer is an important aspect of determining the vulnerability of detected masses based on the previous cases. It is used to retrieve the most similar image for a given mammographic query image from a collection of previously archived images. By analyzing these results, doctors and radiologists can more accurately diagnose early-stage breast cancer and determine the best treatment. The direct result is better prognoses for breast cancer patients. Similarity measurement in images has always been a challenging task in the field of pattern recognition. A widely-adopted strategy in Content-Based Image Retrieval (CBIR) is comparison of local shape-based features of images. Contours summarize the orientations and sizes images, allowing for heuristic approach in measuring similarity between images. Similarly, global features of an image have the ability to generalize the entire object with a single vector which is also an important aspect of CBIR. The main objective of this paper is to enhance the similarity measurement between query images and database images so that the best match is chosen from the database for a particular query image, thus decreasing the chance of false positives. In this paper, a method has been proposed which compares both local and global features of images to determine their similarity. Three image filters are applied to make this comparison. First, we filter using the mesh distance Fourier descriptor (MDFD), which is based on the calculation of local features of the mammographic image. After this filter is applied, we retrieve the five most similar images from the database. Two additional filters are applied to the resulting image set to determine the best match. Experiments show that this proposed method overcomes shortcomings of existing methods, increasing accuracy of matches from 68% to 88%

Incidence and determinants of hysterectomy among North Indian women: An 8-year follow-up study

BackgroundDespite indications of a rapid increase in the number of hysterectomies performed in India, very few studies have methodically investigated the rate and determinants of the incidence of hysterectomy. The present study aims to estimate the rate of incidence of hysterectomy and identify predictors/determinants of incident hysterectomy in a cohort of North Indian women.MethodsIn the present study, a cohort of 1,009 ever-married North Indian women (aged 30–75 years) was followed up after a median of 8.11 years. Those hysterectomized at the baseline (63) were excluded; and of the rest 946 participants, 702 (74.2%) could be successfully followed-up. During the baseline assessment, data about sociodemographic variables, reproductive history, menopausal status, physiological health, and selected blood biochemicals were collected. During the end-line assessment, data about sociodemographic variables, current menopausal status, and incident hysterectomy were recorded.ResultsThe overall rate of incidence of hysterectomy was found to be 11.59 per 1,000 women-years, in the study population. Interestingly, the incidence rates were found to be similar among pre- and post-menopausal women. Further, while late age at menarche was found to be negatively associated with incident hysterectomy, folate repletion and high triglyceride (TG) at the baseline were found to be positively associated.ConclusionsHigh rate of incident hysterectomy in the studied population points toward the huge burden of gynecological morbidity and the unavailability of non-invasive protocols. Such a situation warrants immediate policy intervention. Further, maintaining TG and folate within normal physiological ranges may be beneficial in gynecological ailments necessitating hysterectomy

Recent Strategies for the Remediation of Textile Dyes from Wastewater: A Systematic Review

The presence of dye in wastewater causes substantial threats to the environment, and has negative impacts not only on human health but also on the health of other organisms that are part of the ecosystem. Because of the increase in textile manufacturing, the inhabitants of the area, along with other species, are subjected to the potentially hazardous consequences of wastewater discharge from textile and industrial manufacturing. Different types of dyes emanating from textile wastewater have adverse effects on the aquatic environment. Various methods including physical, chemical, and biological strategies are applied in order to reduce the amount of dye pollution in the environment. The development of economical, ecologically acceptable, and efficient strategies for treating dye-containing wastewater is necessary. It has been shown that microbial communities have significant potential for the remediation of hazardous dyes in an environmentally friendly manner. In order to improve the efficacy of dye remediation, numerous cutting-edge strategies, including those based on nanotechnology, microbial biosorbents, bioreactor technology, microbial fuel cells, and genetic engineering, have been utilized. This article addresses the latest developments in physical, chemical, eco-friendly biological and advanced strategies for the efficient mitigation of dye pollution in the environment, along with the related challenges

Synergistic combination of electronic and electrical properties of SnO2 and TiO2 in a single SnO2-TiO2 composite nanofiber for dye-sensitized solar cells

Tin dioxide (SnO2) and titanium dioxide (TiO2) are popular metal oxide semiconductors; they are explored for many applications because of their unique properties. This paper details that electronic and electrical properties of SnO2 and TiO2 can be synergistically combined in an one-dimensional nanostructure, such as electrospun nanofibers. The resulting composite nanofibers (CNFs) showed beneficial properties when used as a photoanode in dye-sensitized solar cells (DSSCs). In particular, the CNFs showed higher conduction band energy than SnO2 and higher electrical conductivity than TiO2. The SnO2-TiO2 CNFs are synthesized by electrospinning a polymeric solution containing equimolar concentration of tin chloride and titanium alkoxide precursors and subsequent annealing. The composite formation is demonstrated by X-ray diffraction and energy dispersive X-ray measurements and morphology by scanning electron microscopy. Synergy in electronic and electrical properties are demonstrated by cyclic voltammetry, absorption spectroscopy, and electrochemical impedance spectroscopy. Dye-sensitized solar cells fabricated using the CNFs as photoanode showed higher open circuit voltage and short circuit current density than those achieved using pure SnO2 and pure TiO2, respectively