Print ISSN: 1681-6900

Online ISSN: 2412-0758

Keywords : Artificial intelligence


Detection of COVID-19 Based on Chest Medical Imaging and Artificial Intelligence Techniques

Nawres A. Alwash; Hussain Kareem

Engineering and Technology Journal, 2021, Volume 39, Issue 10, Pages 1588-1600
DOI: 10.30684/etj.v39i10.2200

The emergence of COVID-19 disease in the world has moved the wheel of scientific research in order to detect it in the best method, and the fastest of these methods is the use of Artificial Intelligence (AI) techniques to help medical professionals detect COVID-19. The proposed topic is aim to develop algorithm based on combination between imageprocessing techniques with artificial intelligence to diagnose COVID-19. The proposed algorithm consists of five stages to detect and classify COVID-19 from Computer Tomography (CT) images. These stages include; The first of these stages is to collect data from hospitals as real data and from Kagglewebsite for patients and healthy people, then the stage before removing the noise and converting it from RGB to grayscale, then we improve the image, segmentation and formalities, the other stage is a stage used to extract the important characteristics, and the last stage is the classification of images CT scan using Feed Forward Back Propagation Network (FFBPN) and Support Vector Machine (SVM )and compare the result between them and see if the person is infected or healthy. This study was implemented in MATLAB software. The results showed that the noise cancellation technology using anisotropic filtering gave the best results. As for the optimization technology, only the brightness of the images has been increased. At the stage of segmentation of the area of ​​lung injection using the area transplant method, the best results are detection of COVID-19 from other healthy tissues. The FFBPN gave the best results for detecting and classifying COVID-19 as well as determining whether a person has been infected or not. The results of the proposed methodology in accurate and rapid detection of COVID-19 in the lung. The contribution of this paper is to help medical staff detect COVID-19 without human intervention.

Utilizing Artificial Intelligence to Collect Pavement Surface Condition Data

Hasan H. Joni; Imzahim A. Alwan; Ghazwan A. Naji

Engineering and Technology Journal, 2020, Volume 38, Issue 1, Pages 74-82
DOI: 10.30684/etj.v38i1A.251

Nowadays, data collection mechanisms are developed from ancient methods, including visual surveying to modern methods, which rely on digital imaging devices and laser scanning. This is expensive, delay of the pavement maintenance management and consuming of time. In this paper, a robust method proposed for automotive detection of linear distresses from real life movies of Iraqi highways. In the suggested method, common types of cracks, potholes and raveling are distinguished and collected automatically using high speed imaging techniques. The data extracted using the suggested method can be used for selecting priority of management maintenance of country roads and making decisions for treatment or rehabilitation.