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Computer-Aided Diagnosis of Acute Lymphoblastic Leukaemia

Leukaemia is a form of blood cancer which affects the white blood cells and damages the bone marrow. Usually complete blood count (CBC) and bone marrow aspiration are used to diagnose the acute lymphoblastic leukaemia. It can be a fatal disease if not diagnosed at the earlier stage. In practice, man...

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Detalles Bibliográficos
Autores principales: Shafique, Sarmad, Tehsin, Samabia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5851334/
https://www.ncbi.nlm.nih.gov/pubmed/29681996
http://dx.doi.org/10.1155/2018/6125289
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author Shafique, Sarmad
Tehsin, Samabia
author_facet Shafique, Sarmad
Tehsin, Samabia
author_sort Shafique, Sarmad
collection PubMed
description Leukaemia is a form of blood cancer which affects the white blood cells and damages the bone marrow. Usually complete blood count (CBC) and bone marrow aspiration are used to diagnose the acute lymphoblastic leukaemia. It can be a fatal disease if not diagnosed at the earlier stage. In practice, manual microscopic evaluation of stained sample slide is used for diagnosis of leukaemia. But manual diagnostic methods are time-consuming, less accurate, and prone to errors due to various human factors like stress, fatigue, and so forth. Therefore, different automated systems have been proposed to wrestle the glitches in the manual diagnostic methods. In recent past, some computer-aided leukaemia diagnosis methods are presented. These automated systems are fast, reliable, and accurate as compared to manual diagnosis methods. This paper presents review of computer-aided diagnosis systems regarding their methodologies that include enhancement, segmentation, feature extraction, classification, and accuracy.
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spelling pubmed-58513342018-04-22 Computer-Aided Diagnosis of Acute Lymphoblastic Leukaemia Shafique, Sarmad Tehsin, Samabia Comput Math Methods Med Review Article Leukaemia is a form of blood cancer which affects the white blood cells and damages the bone marrow. Usually complete blood count (CBC) and bone marrow aspiration are used to diagnose the acute lymphoblastic leukaemia. It can be a fatal disease if not diagnosed at the earlier stage. In practice, manual microscopic evaluation of stained sample slide is used for diagnosis of leukaemia. But manual diagnostic methods are time-consuming, less accurate, and prone to errors due to various human factors like stress, fatigue, and so forth. Therefore, different automated systems have been proposed to wrestle the glitches in the manual diagnostic methods. In recent past, some computer-aided leukaemia diagnosis methods are presented. These automated systems are fast, reliable, and accurate as compared to manual diagnosis methods. This paper presents review of computer-aided diagnosis systems regarding their methodologies that include enhancement, segmentation, feature extraction, classification, and accuracy. Hindawi 2018-02-28 /pmc/articles/PMC5851334/ /pubmed/29681996 http://dx.doi.org/10.1155/2018/6125289 Text en Copyright © 2018 Sarmad Shafique and Samabia Tehsin. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Review Article
Shafique, Sarmad
Tehsin, Samabia
Computer-Aided Diagnosis of Acute Lymphoblastic Leukaemia
title Computer-Aided Diagnosis of Acute Lymphoblastic Leukaemia
title_full Computer-Aided Diagnosis of Acute Lymphoblastic Leukaemia
title_fullStr Computer-Aided Diagnosis of Acute Lymphoblastic Leukaemia
title_full_unstemmed Computer-Aided Diagnosis of Acute Lymphoblastic Leukaemia
title_short Computer-Aided Diagnosis of Acute Lymphoblastic Leukaemia
title_sort computer-aided diagnosis of acute lymphoblastic leukaemia
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5851334/
https://www.ncbi.nlm.nih.gov/pubmed/29681996
http://dx.doi.org/10.1155/2018/6125289
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