Automatic segmentation of malaria parasites on thick blood film using blob analysis

Sulistyawati, Dwi; Rahmanti, Farah Zakiyah; Purnama, I Ketut Eddy; Purnomo, Mauridhi Hery

doi:10.1109/isitia.2015.7219968

Cited by 4 publications

(3 citation statements)

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“…The analysed works performed classification phase for different purposes. The majority of them aimed to distinguish among two classes only, malaria infected and noninfected RBCs, or to detect and count parasites in a malaria blood image [ 4 , 10 , 12 , 14 , 15 , 17 , 18 , 20 , 21 , 25 , 28 , 32 , 34 , 35 , 36 , 38 , 44 , 49 , 51 ].…”

Section: Discussionmentioning

confidence: 99%

“…However, they are not focused on MM techniques as they analyze generic computer vision systems for malaria diagnosis, as in [ 11 , 12 , 13 ]. Furthermore, newer and promising approaches, addressing for example the problem of malaria diagnosis in remote areas [ 11 , 14 ], or improving significantly both the detection and the classification performances [ 15 , 16 , 17 , 18 ], have not been considered in the previous reviews.…”

Section: Scope Of This Reviewmentioning

confidence: 99%

“…In [ 18 ], Sulistyawati et al combined morphological operations (erosion, dilation, opening and closing) and blob analysis to segment and identify malaria parasites with a high degree of accuracy.…”

Section: Computer Aided Diagnosis Of Malaria By Using Mathematicalmentioning

confidence: 99%

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Recent Advances of Malaria Parasites Detection Systems Based on Mathematical Morphology

Loddo

Ruberto

Kocher

2018

Sensors

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Abstract: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. Nevertheless, this kind of visual inspection is subjective, error-prone and time-consuming. In order to overcome the issues, numerous methods of automatic malaria diagnosis have been proposed so far. In particular, many researchers have used mathematical morphology as a powerful tool for computer aided malaria detection and classification. Mathematical morphology is not only a theory for the analysis of spatial structures, but also a very powerful technique widely used for image processing purposes and employed successfully in biomedical image analysis, especially in preprocessing and segmentation tasks. Microscopic image analysis and particularly malaria detection and classification can greatly benefit from the use of morphological operators. The aim of this paper is to present a review of recent mathematical morphology based methods for malaria parasite detection and identification in stained blood smears images.

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