Author/Authors :
Shafique, Sarmad Department of Computer Science - Bahria University - Islamabad, Pakistan , Tehsin, Samabia Department of Computer Science - Bahria University - Islamabad, Pakistan
Abstract :
Leukaemia is a form of blood cancer which afects 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. Terefore, diferent 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. Tese automated systems are fast,
reliable, and accurate as compared to manual diagnosis methods. Tis paper presents review of computer-aided diagnosis systems
regarding their methodologies that include enhancement, segmentation, feature extraction, classifcation, and accuracy.