A Hybrid Classification Scheme Using 2D-SWT and SVM for the Detection of Acute Lymphoblastic Leukemia

[1]  Yudong Zhang,et al.  AN MR BRAIN IMAGES CLASSIFIER VIA PRINCIPAL COMPONENT ANALYSIS AND KERNEL SUPPORT , 2012 .

[2]  Paolo Rota,et al.  On automated Flow Cytometric analysis for MRD estimation of Acute Lymphoblastic Leukaemia: A comparison among different approaches , 2015, 2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

[3]  Banshidhar Majhi,et al.  Microscopic Image Classification Using DCT for the Detection of Acute Lymphoblastic Leukemia (ALL) , 2016, CVIP.

[4]  Dipti Patra,et al.  An ensemble classifier system for early diagnosis of acute lymphoblastic leukemia in blood microscopic images , 2013, Neural Computing and Applications.

[5]  M. F. Miswan,et al.  Red blood cell segmentation using masking and watershed algorithm: A preliminary study , 2012, 2012 International Conference on Biomedical Engineering (ICoBE).

[6]  Banshidhar Majhi,et al.  A survey on automated diagnosis on the detection of Leukemia: A hematological disorder , 2016, 2016 3rd International Conference on Recent Advances in Information Technology (RAIT).

[7]  Shitong Wang,et al.  A new detection algorithm (NDA) based on fuzzy cellular neural networks for white blood cell detection , 2006, IEEE Transactions on Information Technology in Biomedicine.

[8]  Banshidhar Majhi,et al.  GLRLM-Based Feature Extraction for Acute Lymphoblastic Leukemia (ALL) Detection , 2018 .

[9]  A. G. Ramakrishnan,et al.  Automation of differential blood count , 2003, TENCON 2003. Conference on Convergent Technologies for Asia-Pacific Region.

[10]  Banshidhar Majhi,et al.  Gray level co-occurrence matrix and random forest based acute lymphoblastic leukemia detection , 2017, Biomed. Signal Process. Control..

[11]  Vincenzo Piuri,et al.  All-IDB: The acute lymphoblastic leukemia image database for image processing , 2011, 2011 18th IEEE International Conference on Image Processing.