Preprint Review Version 1 This version is not peer-reviewed

Recent Advances of Malaria Parasites Detection Systems Based on Mathematical Morphology

Version 1 : Received: 14 December 2017 / Approved: 14 December 2017 / Online: 14 December 2017 (17:10:19 CET)

A peer-reviewed article of this Preprint also exists.

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. Sensors 2018, 18, 513.

Journal reference: Sensors 2018, 18, 513
DOI: 10.3390/s18020513

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.

Subject Areas

malaria; red blood cells segmentation; mathematical morphology; medical image analysis

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