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.

Indigenous Model of Higher Education Reforms in Pakistan: Higher Education Quality Assurance Initiatives

Quality of higher education is believed to be one of the most important aspects of human resource development, creation of knowledge and social uplift in a country. Higher education institutions in general and policy institutions including Higher Education Commission of Pakistan in particular are realizing their increasing role in national uplift through improving quality of higher education. Purposes of this study are manifold: to explore types of quality improvements, reforms and initiatives that took place in higher education in Pakistan since its inception; to review available quality assurance models for higher education institutions that contribute in continuous quality improvement in HEIs. Furthermore, primary data are collected in order to determine the attitude and perceptions of faculty members, senior academicians and administrators towards quality improvement practices in Higher Education Institutions (HEIs). Moreover, the intention is to explore the status of implementation of quality assurance practices and their implications on the institutional performance in the context of higher education. Also, the study develops constructs that can contribute to the continuous improvement in the quality of higher education. Finally, Indigenous Quality Assurance Model for HEIs is developed in this study which is believed appropriate and applicable to address quality of higher education in the country. The findings of this research will be useful in order to address the quality assurance issues at multiple levels: national policy, HEIs management and various stakeholders including faculty members. The components contributing in continuous quality system improvement in HEIs are addressed at length. Finally, the model developed in this work can be used at all the levels addressed above for quality assurance purposes