Machine Vision based Computer-Aided Detection of Pulmonary Tuberculosis using Chest X-Ray Images

Tuberculosis (TB) is a lethal disease and developing countries are struggling to overcome this health hazard especially in rural areas and faced globally. Therefore, serious measures are required to reduce this global health hazard. Millary and pulmonary are the most common types of tuberculosis occurring globally. X-ray is the preliminary method to detect tuberculosis; however, the diagnosis is quite often subject to human error. In contrast, the chances of curing Tuberculosis depend on its timely and accurate diagnosis. Therefore, an intelligent machine learning algorithm is developed in this study to assist the clinician in an accurate TB identification in x-ray images. The proposed method pre-processes the X-ray image, enhances its quality and extracts the features of each class which are further passed on to a Deep Convolutional Neural Network-based design for the X-ray image classification, followed by the identification of the tuberculosis type i.e. Millary, Cavitary, Healthy. The classification accuracy for the developed method resulted in 88% and 89% for millary and cavitary TB diseases in x ray images.

Drug Induced Developmental Defects of Teeth

The present study was designed to evaluate the effect of commonly used drugs on the dental tissues. The dental tissues are sensitive to certain drugs if they are used by the conceiving mothers for a prolonged period of time during pregnancy. Some commonly used drugs were selected for this study e.g. aspirin, estrogen and lithium, which have been reported to affect the human tissues in intrauterine life, if used by the mothers. The study was conducted on the female rabbits. The experimental animals were divided into four groups, each of which having (n=7) subjects. Three of them for the study of drug treatments and the fourth one was taken as a control. Drugs were given with the predetermined doses according to their body weights, until the birth of their offsprings. The offsprings of these rabbits were used for the research purposes. Different parameters e.g. the variation in the size of the teeth, the contents and composition of mineral in the outer dental tissue i.e. enamel, and the ultrastructural changes of the enamel surfaces of teeth, investigated by SEM were included in the study. Analysis of teeth was done at the age of three months to examine the congenital defects developed during intrauterine life. Volumetric analysis was done on 672 samples before the extraction of teeth. The teeth were then extracted to analyze 336 samples for the mineral contents and to study the surface structure of enamel with the help of scanning electron microscope and energy dispersive X-ray spectroscopy (SEM-EDX). A very large variation was observed in the results, within the samples, between the control and the experimental groups, from either the chemical analysis or the volumetric measurements. It was observed that the incisors and molars were esthetically and functionally the compromised teeth. It was apparent that the statistically significant results could not be achieved which have overshadowed the aggregate differences between the groups. However this study could help to establish the association of chronic use of certain drugs with the developmental anomalies of dental tissues. It may also guide the future investigators to work on the interaction of drug related factors in pathogenesis of different pathologies. It could possibly be helpful to achieve the aesthetic and functional goals in the field of dentistry. The study was expected to provide suggestions for the use of certain drugs during pregnancy and new leads for further research.