Classification of Atypical White Blood Cells in Acute Myeloid Leukemia Using a Two-Stage Hybrid Model Based on Deep Convolutional Autoencoder and Deep Convolutional Neural Network

Recent advancements in artificial intelligence (AI) have led to numerous medical discoveries. The field of computer vision (CV) for medical diagnosis has received particular attention. Using images of peripheral blood (PB) smears, CV has been utilized in hematology to detect acute leukemia (AL). Sig...

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Veröffentlicht in:	Diagnostics (Basel) Jg. 13; H. 2; S. 196
Hauptverfasser:	Elhassan, Tusneem A., Mohd Rahim, Mohd Shafry, Siti Zaiton, Mohd Hashim, Swee, Tan Tian, Alhaj, Taqwa Ahmed, Ali, Abdulalem, Aljurf, Mahmoud
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland MDPI AG 05.01.2023 MDPI
Schlagworte:	Accuracy acute myeloid leukemia atypical white blood cells augmentation autoencoder Automation Back propagation Blood Bone marrow Classification CNN Datasets Deep learning Fractals Leukemia Lymphocytes Methods Morphology Neural networks Neutrophils atypical white blood cells CNN autoencoder acute myeloid leukemia augmentation
ISSN:	2075-4418, 2075-4418
Online-Zugang:	Volltext
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