Psychosocial Nurturing of Children in Islam

Psychosocial nurturing of children is linked with Parenting and personality development theories and child development theories too report evidences of influences of parenting on children nurturing. The purpose of this paper is to explore existing parenting styles in current literature and how these parenting styles influence upon and form the personality of the children in their early years. The paper aims to examine parenting with reference to authoritarian parenting, authoritative parenting, permissive parenting and uninvolved parenting. It discussed the expectations and responsiveness of the parents which determine their behavior and style. Through parenting, psychosocial nurturing of the children is determined and it was explained in existing literature and analyzed in Islamic teachings. The study followed a critical interpretivist method which examined the literature and conducted content analysis. The study examines the parenting concept and parenting style in Islamic teachings. Islam lays special emphasis on communication and attitude of the parents towards their children particularly in early childhood. Parenting style in Islamic teaching displays a loving and guiding mode. It is less demanding and more responsive in early years. Parenting in Islamic teaching encourages developing tolerance, harmony and peace. It shows flexibility to accept children’s dispositions and tries to discipline their inner faculties. Islamic teachings expect from parents to be responsive with love and passion. It gives children freedom to talk, walk, think and act in a carefree environment where they can become socially and emotionally strong. Parenting in Islam accepts children’s interests and attitudes with positive responses and respects their rights with warmth and love. It particularly develops moral awareness so that children can distinguish between right and wrong and also understand that they need to abide by rules and regulations. Lastly literature also reports that parenting in Islam does not allow any sort of harassment, coercion, frightening and unjust environment for the little angels.

Denoising and Segmentation of Blood Vessels in Retina Images Using Statistical Techniques

Visual pathology is one of the leading health complications in present day. The number of individuals with retinopathy signs has increased significantly in the recent years. Timely medications have produced favorable results in evading the visual deficiency. However, the exploration of retinal photographs is another option for periodical retinal treatment which is non-invasive. Various approaches have presented for inspection of the retinal photographs which are based on supervised techniques that utilize important distinctive features to be extracted from good quality retina images for training. In contrast, unsupervised methods perform exploration of the retinal image without the utilization of any trained information or human intervention. These type of models have been developed in this research. The proposed framework identifies an eye objects (e.g. optic disc, fovea and macula) in the first step. Later, these objects along with the background are eliminated from the retinal photographs in order to attain the retinal vascular map to locate the lesion manifestation. Inspired from the current research of retinal blood vessels segmentation, this dissertation introduces new approaches for localization of blood vessels in retina images. This research is focused on solving problems of the tiny vessels detection, manual threshold selection, computation complexity, degradation of accuracy with the change of the dataset, improper handling of pathological images, contrast enhancement, erroneous classification of blood vessels and denoising of retina images. The different preprocessing steps, contrast enhancement techniques, thresholding schemes, vasculature enhancement schemes and postprocessing techniques of vessels segmentation in retina images have been explored in this dissertation. Five new methods have been introduced for localization of the vascular map in retina images. The first two methods modify the basic thresholding techniques along with strong preprocessing and postprocessing steps. A third method also includes thresholding for blood vessels segmentation along with a novel scheme for contrast enhancement that makes the vessels more prominent from the background. These methods localized both wide and tiny vessels accurately and automatically of the different datasets. These methods are also robust against noise and various retinal disease abnormalities. Additionally, reduction in the computation complexity of all the methods is observed. Experimental results of the proposed methods have accomplished remarkable improvement in terms of accuracy, sensitivity, specificity and area under the curve (AUC). The last two proposed methods introduced parallel steps for noise elimination, vasculature enhancement and segmentation. Initially, vessels location map (VLM) is extracted by utilizing various preprocessing and thresholding techniques. Then vasculature based enhancement is achieved by applying B-COSFIRE filter and Frangi’s filter in each method individually. In the first step of both methods, background noise and geometrical objects (e.g. optic disk, macula, fovea, etc.) are removed. Thus, VLM is obtained by identifying wide vessels positions to couple with the output image of the second step. The proposed methods have shown better accuracy, sensitivity and specificity when compared to existing methods. The proposed methods of this dissertation can indeed contribute to the development of an automatic retinal vessel segmentation system capable of handling both healthy and unhealthy images of all datasets.