Loddo, A.; Di Ruberto, C.; Kocher, M. Recent Advances of Malaria Parasites Detection Systems Based on Mathematical Morphology. Sensors2018, 18, 513.
Loddo, A.; Di Ruberto, C.; Kocher, M. Recent Advances of Malaria Parasites Detection Systems Based on Mathematical Morphology. Sensors 2018, 18, 513.
Loddo, A.; Di Ruberto, C.; Kocher, M. Recent Advances of Malaria Parasites Detection Systems Based on Mathematical Morphology. Sensors2018, 18, 513.
Loddo, A.; Di Ruberto, C.; Kocher, M. Recent Advances of Malaria Parasites Detection Systems Based on Mathematical Morphology. Sensors 2018, 18, 513.
Abstract
This paper investigates existing mathematical morphology based techniques applied for performing malaria parasites detection and identification in both Giemsa and Leishman stained blood smears images. Malaria is an epidemic health disease and a rapid, accurate diagnosis is necessary for proper intervention. Generally, pathologists visually examine blood stained slides for malaria diagnosis; this kind of visual inspection is subjective, errorprone and time consuming. In order to cope with such issues, computer-aided methods have been increasingly evolved for abnormal erythrocyte and/or parasites detection, segmentation and semi/fully automated classification. The aim of this paper is to present a review of recent mathematical morphology based methods for malaria parasite detection.
Keywords
malaria; red blood cells segmentation; mathematical morphology; medical image analysis
Subject
Computer Science and Mathematics, Mathematics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
