A proposed model to eliminate the confusion of hematological diseases in thin blood smear by using deep learning : pretrained model
Joint Authors
Sharif, Mahir M.
Muhammad, Hasan Abd al-Rahman
Husayn, al-Tahir Muhammad
Source
Journal of Omdurman Islamic University
Issue
Vol. 18, Issue 1 (30 Apr. 2022), pp.81-92, 12 p.
Publisher
Omdurman Islamic University Institute of Researches and Strategic Studies
Publication Date
2022-04-30
Country of Publication
Sudan
No. of Pages
12
Main Subjects
Electronic engineering
Information Technology and Computer Science
Abstract EN
This research aimed to developing and designing a model for resolving the confusion between hematology in a thin blood smear by means of a pre-defined deep learning model for detection and identification of hematological diseases in thin blood smear images for accurate diagnosis of the different diseases that leukemia and malaria were performed as a sample.
There are catastrophic consequences that may lead to death as a result of a mistake in diagnosis and confusion in the knowledge of the disease in particular, especially in hematology, where another disease that was not originally found in the sample is identified for the similarity, which results in surgery and sometimes the administration of drugs in error.
In this work, an image processing system was developed to identify patients with malaria and leukemia.
The techniques in deep learning have been implemented where the CNN (Alexnet and Resnet50) image recognition model was applied to detect patterns and extract features of the different types of malaria and leukemia from the images.
And that is through developing algorithms to distinguish between the two diseases, discovering the presence of similarities in the patterns of stages and the different types of malaria and leukemia in blood images, and reaching to solve the problem of confusion by training, verification, and testing using the mutual verification system that uses three folds.
The system achieved an accuracy of 94.3% for Resnet50 and 92.3 for Alexnet in detecting and classifying the types and stages of the two diseases (malaria and leukemia).
And 100% to distinguish between them.
American Psychological Association (APA)
Sharif, Mahir M.& Muhammad, Hasan Abd al-Rahman& Husayn, al-Tahir Muhammad. 2022. A proposed model to eliminate the confusion of hematological diseases in thin blood smear by using deep learning : pretrained model. Journal of Omdurman Islamic University،Vol. 18, no. 1, pp.81-92.
https://search.emarefa.net/detail/BIM-1424265
Modern Language Association (MLA)
Sharif, Mahir M.…[et al.]. A proposed model to eliminate the confusion of hematological diseases in thin blood smear by using deep learning : pretrained model. Journal of Omdurman Islamic University Vol. 18, no. 1 (Apr. 2022), pp.81-92.
https://search.emarefa.net/detail/BIM-1424265
American Medical Association (AMA)
Sharif, Mahir M.& Muhammad, Hasan Abd al-Rahman& Husayn, al-Tahir Muhammad. A proposed model to eliminate the confusion of hematological diseases in thin blood smear by using deep learning : pretrained model. Journal of Omdurman Islamic University. 2022. Vol. 18, no. 1, pp.81-92.
https://search.emarefa.net/detail/BIM-1424265
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 92
Record ID
BIM-1424265