CLASSIFICATION AND QUANTIFICATION OF MALARIA PARASITES USING CONVOLUTIONAL NEURAL NETWORKS.

CDR Coalition Maxwell Mbabilla Aladago 71 PAGES (17737 WORDS) Thesis
Subscribe to access this work and thousands more

Abstract Malaria is currently one of the most deadly diseases in the world. While there are different treatment methods for the disease, the search for new drugs against malaria is still a very important area of research. One of the main challenges in manufacturing drugs against malaria is efficiently evaluating the performance of the drugs on the parasites since it requires, amongst others, precise measurements of the parasite growth-stages as well as their counts in blood smear images. The current gold-standard for making such detail diagnosis is manual microscopy which is tedious. This research showed that convolutional neural networks can be used to identify the different growth-cycle stages of Plasmodium parasites, even in situations where there is little data. Employing a variety of data augmentation techniques and transfer learning, a semantic segmentation model was built to discriminate between trophozoites, gametocytes and normal red blood cells with an accuracy of 85.86% in 353 Giemsa-stained thin blood smears. The results showed that it is possible to perform dense predictions on Giemsa-stained thin blood smears using convolutional neural networks

Subscribe to access this work and thousands more
Overall Rating

0

5 Star
(0)
4 Star
(0)
3 Star
(0)
2 Star
(0)
1 Star
(0)
APA

CDR, C (2021). CLASSIFICATION AND QUANTIFICATION OF MALARIA PARASITES USING CONVOLUTIONAL NEURAL NETWORKS.. Afribary.com: Retrieved April 14, 2021, from https://afribary.com/works/classification-and-quantification-of-malaria-parasites-using-convolutional-neural-networks-1

MLA 8th

Coalition, CDR. "CLASSIFICATION AND QUANTIFICATION OF MALARIA PARASITES USING CONVOLUTIONAL NEURAL NETWORKS." Afribary.com. Afribary.com, 01 Apr. 2021, https://afribary.com/works/classification-and-quantification-of-malaria-parasites-using-convolutional-neural-networks-1 . Accessed 14 Apr. 2021.

MLA7

Coalition, CDR. "CLASSIFICATION AND QUANTIFICATION OF MALARIA PARASITES USING CONVOLUTIONAL NEURAL NETWORKS.". Afribary.com, Afribary.com, 01 Apr. 2021. Web. 14 Apr. 2021. < https://afribary.com/works/classification-and-quantification-of-malaria-parasites-using-convolutional-neural-networks-1 >.

Chicago

Coalition, CDR. "CLASSIFICATION AND QUANTIFICATION OF MALARIA PARASITES USING CONVOLUTIONAL NEURAL NETWORKS." Afribary.com (2021). Accessed April 14, 2021. https://afribary.com/works/classification-and-quantification-of-malaria-parasites-using-convolutional-neural-networks-1