The International Arab Journal of Information Technology (IAJIT)


Malaria Parasite Detection on Microscopic Blood Smear Images with Integrated Deep Learning

Malaria is a deadly syndrome formed by the Plasmodium parasite that spreads through the bite of infected Anopheles mosquitoes. There are several drugs to cure malaria but it is difficult to detect due to inadequate equipment and technology. Microscopic check-ups of blood smear images by experts help to detect malaria-infected parasites accurately. However, manual analysis is tedious and time-consuming as the experts have to deal with many cases. This paper presents computer assisted malaria parasite detection model by classifying the blood smear image with hybrid deep learning methods that have high accuracy for classification. In the proposed approach the blood smear images are pre-processed using bilateral filtering technique in which features are extracted with the convolutional neural network. These features are selected by the improved grey-wolf optimization, and image classification is performed with the support vector machine. To evaluate the efficiency of the proposed technique, the NIH malaria dataset is utilized and the results are compared with existing approaches in terms of accuracy, F-Measure, recall, precision, and specificity. The outcome reveals that the proposed scheme is accurate and can be more helpful to pathologists for reliable parasite detection.

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[31] Yuan Y. and Meng M., “Deep Learning for Polyp Recognition in Wireless Capsule Endoscopy Images,” Medical Physics, vol. 44, no. 4, pp. 1379-1389, 2017. Christonson Berin Jones is a Professor at Department of Computer Science and Engineering in Madurai Institute of Engineering and Technology, Sivagangai District, Tamil Nadu, India. He obtained his BE ME and PhD degree at Manonmaniam Sundaranar University, Tirunelveli, TamilNadu, India. His Ph.D research focuses on Image Processing for various applications.” Chakravarthi Murugamani received his B. Tech degree in Information Technology, from Anna University, Chennai, India in 2005; and his M.Tech degree in Information Technology from Sathyabama University, Chennai, India in 2011. He completed his Ph.D degree in Information Technology from St. Peter’s University, Chennai, India in 2017. He is currently working as Professor and Head in the Department of Information Technology with the Bhoj Reddy Engineering College for Women, Hyderabad, India. He has published more than 10 International Journals along with 4 International and National conferences. He has even published 1 patent in IPR. He is also an active member in CSI and ISTE. He has received 2 times Certificate of Appreciation from IIT Madras, India for Instrumental role as SPOC for the SWAYAM- NPTEL Local Chapter for Bhoj Reddy Engineering College for Women, Hyderabad Active SPOC based on Performance and Participation of Candidates. His research and teaching interests include Computer Networks, Artificial Intelligence, Image Processing and Computer Graphics. He is an active researcher, reviewer and editor for many international journals.