Feature Extraction of White Blood Cells Using CMYK-Moment Localization and Deep Learning in Acute Myeloid Leukemia Blood Smear Microscopic Images

Artificial intelligence has revolutionized medical diagnosis, particularly for cancers. Acute myeloid leukemia (AML) diagnosis is a tedious protocol that is prone to human and machine errors. In several instances, it is difficult to make an accurate final decision even after careful examination by a...

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Veröffentlicht in:	IEEE access 2022, Vol.10, p.16577-16591
Hauptverfasser:	Elhassan, Tusneem Ahmed M., Rahim, Mohd Shafry Mohd, Swee, Tan Tian, Hashim, Siti Zaiton Mohd, Aljurf, Mahmoud
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Acute myeloid leukemia (AML) Algorithms Artificial intelligence Blood Classification CNN Datasets Deep learning Diagnosis Errors Feature extraction feature fusion Gabor filters Image color analysis Image processing Image segmentation Leukemia Leukocytes Localization Localization method Location awareness Machine learning Medical imaging ROI white blood cell (WBC) feature extraction
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