Framework for COVID-19 Segmentation and Classification Based on Deep Learning of Computed Tomography Lung Images

Corona Virus Disease 2019(COVID-19) has affected millions of people worldwide and caused more than6.3 million deaths(World Health Organization, June 2022). Increased attempts have been made to develop deep learning methods to diagnose COVID-19 based on computed tomography(CT) lung images. It is a challenge to reproduce and obtain the CT lung data, because it is not publicly available. This paper introduces a new generalized framework to segment and classify CT images and determine whether a patient is tested positive or negative for COVID-19 based on lung CT images. In this work, many different strategies are explored for the classification task.ResNet50 and VGG16 models are applied to classify CT lung images into COVID-19 positive or negative. Also,VGG16 and ReNet50 combined with U-Net, which is one of the most used architectures in deep learning for image segmentation, are employed to segment CT lung images before the classifying process to increase system performance. Moreover, the image size dependent normalization technique(ISDNT) and Wiener filter are utilized as the preprocessing techniques to enhance images and noise suppression. Additionally, transfer learning and data augmentation techniques are performed to solve the problem of COVID-19 CT lung images deficiency, therefore the over-fitting of deep models can be avoided. The proposed frameworks, which comprised of end-to-end, VGG16,ResNet50, and U-Net with VGG16 or ResNet50, are applied on the dataset that is sourced from COVID-19 lung CT images in Kaggle. The classification results show that using the preprocessed CT lung images as the input for U-Net hybrid with ResNet50 achieves the best performance. The proposed classification model achieves the 98.98%accuracy(ACC), 98.87% area under the ROC curve(AUC), 98.89% sensitivity(Se), 97.99 % precision(Pr), 97.88%F-score, and 1.8974-seconds computational time.

Basis of Halal Lifestyle in Islamic Law

The halal lifestyle in Islamic law is evaluated within the principles of makasidus-sharia,which aim to protect five principal vales of humanity,namely,life,reason,religion,generation and property.The legitimacy of halal life is therefore based on the provisions of the Qur’an and Sunnah that aim to protect these values of all humanity.The similarities between halal and other ethical practices in the context of universal values concerning both Muslims and non-Muslims will provide an opportunity for global recognition of halal life.In this article we investigate how halal lifestyle is to be based according to Islamic law.We first frame the halal life and later lay down its legal basis and finally conclude by illuminating on the halal lifestyle from a universal perspective.