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Sickle Cell Anemia Detection

Authors: Albayrak, Batuhan; Darıcı, Muazzez Buket; Kiracı, Furkan; Öğrenci, Arif Selçuk; Özmen, Atilla; Ertez, Kerem;

Sickle Cell Anemia Detection

Abstract

Anemia is a common name given to falls in oxygen transport capacity due to some of the functional disadvantages of red blood cells. Pathology Laboratorians put the tissue on the microscope glass and try to diagnose Anemia disease. Processes have been taken for a long time and it has been caused to distract. Therefore it has been caused to misdiagnose the Laboratorian. This work shortens the diagnostic period of the disease and to minimizes error probability of this diagnosis by extracting healthy cells and just having sickle cells on the blood tissue using Image Processing Algorithms with an accuracy of 91.11 %, precision of 92.9 %, recall of 79.05 % for Sickle Cell Anemia.

Anemi, kırmızı kan hücrelerinin bazı fonksiyonel dezavantajları nedeniyle oksijen taşıma kapasitesindeki düşüşlere verilen yaygın bir isimdir. Patoloji Laborantları mikroskop camı üzerine dokuyu yerleştirir ve Anemi hastalığını teşhis etmeye çalışırlar.Bu süreçler uzun sürmektedir ve dikkat dağılmasına neden olmaktadır. Bu nedenle, Laborantların yanlış teşhis etmesine sebep olmaktadır. Bu çalışma %91.11 kesinlik, %92.9 hassasiyet ve %79.05 hatırlanma oranıyla görüntü işleme algortmaları kullanarak kan dokusunda sağlıklı hücreli çıkararak ve sadece orak hücrelere sahip olarak teşhis süresini kısaltır ve teşhisin hata oranını en aza indirir.

Biyomedikal Klinik Mühendisliği Derneği

İzmir Katip Çelebi Üniversitesi

Biyomedikal Mühendisliği Bölümü

Country
Turkey
Keywords

Sickle Cell Anemia, Görüntü İşleme, Image Processing, Circular Hough Transform(CHT), Orak Hücreli Anemi, Dairesel Hough Dönüşümü(DHD)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green