Plasmodium species aware based quantification of malaria parasitemia in light microscopy thin blood smear

Author:

Abbas Naveed1,Saba Tanzila2ORCID,Rehman Amjad3ORCID,Mehmood Zahid4,Javaid Nadeem5,Tahir Muhammad6,Khan Naseer Ullah1,Ahmed Khawaja Tehseen7,Shah Roaider1

Affiliation:

1. Department of Computer ScienceIslamia College Peshawar KPK Pakistan

2. College of Computer and Information SciencesPrince Sultan University Riyadh Saudi Arabia

3. College of Business AdministrationAl Yamamah University Riyadh Saudi Arabia

4. Department of Computer EngineeringUniversity of Engineering and Technology Taxila Pakistan

5. Department of Computer ScienceCOMSATS University Islamabad Pakistan

6. Department of Computer ScienceCOMSATS University Islamabad, Attock Campus Pakistan

7. Department of Computer ScienceBahauddin Zakariya University Multan Pakistan

Publisher

Wiley

Subject

Medical Laboratory Technology,Instrumentation,Histology,Anatomy

Reference72 articles.

1. Nuclei segmentation of leukocytes in blood smear digital images;Abbas N.;Pakistan Journal of Pharmaceutical Sciences,2015

2. Machine aided malaria parasitemia detection in Giemsa-stained thin blood smears

3. Plasmodium life cycle stage classification based quantification of malaria parasitaemia in thin blood smears

4. An innovative technique for contrast enhancement of computed tomography images using normalized gamma‐corrected contrast‐limited adaptive histogram equalization;Al‐Ameen Z.;EURASIP Journal on Advances in Signal Processing,2015

5. Bashir A. Mustafa Z. A. Abdelhameid I. &Ibrahem R.(2017).Detection of malaria parasites using digital image processing. 2017 International Conference on Communication Control Computing and Electronics Engineering (ICCEE). IEEE. pp.1–5.

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