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Acute Lymphoblastic Leukemia Identification Using Blood Smear Images and a Neural Classifier. (Khashman, Adnan,)
Bibliographical information (record 267613)
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Acute Lymphoblastic Leukemia Identification Using Blood Smear Images and a Neural Classifier.
Author:
 Khashman, Adnan, Search Author in Amazon Books

Publisher:
Springer,
Edition:
 2013.
Classification:
 QA76
Detailed notes
    - There is a need for fast and cost-effective leukemia identification methods, because early identification could increase the likelihood of recovery. Currently, diagnostic methods require sophisticated expensive laboratories such as immune-phenotype and cytogenetic abnormality. Therefore, we propose an identification method based on using blood smear images of normal and cancerous cells, in addition to a neural network classifier. We focus in this paper on identifying Acute Lumphoblastic Leukemia (ALL) cases, and implement our experiments following three learning schemes for a neural model. The neural classifiers distinguish between normal blood cells and ALL-infected cells. The experimental results show that the proposed novel leukemia identification system can be effectively used for such a task, and thus could be implemented for identifying other leukemia types in real life applications.
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Library
Section
EOL-1545
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NEU Grand LibraryOnline (QA76 .A28 2013)
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