A Novel Approach for Objective Assessment of White Blood Cells Using Computational Vision Algorithms.
In the field of medicine, the analysis of blood is one of the most important exams to determine the physiological state of a patient. In the analysis of the blood sample, an important process is the counting and classification of white blood cells, which is done manually, being an exhaustive, subjec...
| Published in: | Advances in Hematology pp. 1 - 10 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Published: |
Wiley-Blackwell
11/13/2018
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=132988117&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 132988117 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 16879104 8NC1 jtl: Advances in Hematology issn: 16879104 maglogo: N pubinfo: dt: 11/13/2018 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 132988117 10.1155/2018/4716370 132988117 ppf: 1 ppct: 9 formats: tig: atl: A Novel Approach for Objective Assessment of White Blood Cells Using Computational Vision Algorithms. aug: au: Rodríguez Barrero, Cesar Mauricio Romero Gabalan, Lyle Alberto Roa Guerrero, Edgar Eduardo affil: KINESTASIS Seedlings of Research, University of Cundinamarca, Fusagasugá, Colombia sug: ab: In the field of medicine, the analysis of blood is one of the most important exams to determine the physiological state of a patient. In the analysis of the blood sample, an important process is the counting and classification of white blood cells, which is done manually, being an exhaustive, subjective, and error-prone activity due to the physical fatigue that generates the professional because it is a method that consumes long laxes of time. The purpose of the research was to develop a system to identify and classify blood cells, by the implementation of the networks of Gaussian radial base functions (RBFN) for the extraction of its nucleus and subsequently their classification through the morphological characteristics, its color, and the distance between objects. Finally, the results obtained with the validation through the coefficient of determination showed an overall accuracy of 97.9% in the classification of the white blood cells per individual, while the precision in the classification by type of cell evidenced results in 93.4% for lymphocytes, 97.37% for monocytes, 79.5% for neutrophils, 73.07% for eosinophils, and a 100% in basophils with respect to the professional. In this way, the proposed system becomes a reliable technological support that contributes to the improvement of the analysis for identification of blood cells and therefore would benefit the low-level hematology establishments as well as to the processes of research in the area of medicine. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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