Blood cell identification using a simple neural network

International Journal of Neural Systems

Volumn 18, Issue 5, 2008, Pages 453-458

  Khashman, Adnan ^a  

^a NEAR EAST UNIVERSITY   (Turkey)

Author keywords

Back propagation; Blood cell identification; Global pattern averaging; Neural network

Indexed keywords

ARTIFICIAL INTELLIGENCE; BLOOD; CELLS; CYTOLOGY; FEATURE EXTRACTION; IMAGE CLASSIFICATION; VEGETATION; VISUAL COMMUNICATION;

BACK PROPAGATION; BLOOD CELL IDENTIFICATION; BLOOD CELLS; CELL FEATURES; CELL TYPES; GLOBAL PATTERN AVERAGING; GLOBAL PATTERNS; HUMAN VISUAL INSPECTIONS; MORPHOLOGICAL FEATURES; SYSTEM USES; TIME CONSUMING;

NEURAL NETWORKS;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; AUTOMATED PATTERN RECOGNITION; BLOOD CELL COUNT; COMPARATIVE STUDY; COMPUTER PROGRAM; CYTOLOGY; ERYTHROCYTE; HUMAN; IMAGE CYTOMETRY; LEUKOCYTE; METHODOLOGY; THROMBOCYTE;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BLOOD CELL COUNT; BLOOD PLATELETS; ERYTHROCYTES; HUMANS; IMAGE CYTOMETRY; LEUKOCYTES; NEURAL NETWORKS (COMPUTER); PATTERN RECOGNITION, AUTOMATED; SOFTWARE; SOFTWARE VALIDATION;

EID: 55849137653     PISSN: 01290657     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0129065708001713     Document Type: Article

References (13)

1. H. Sheikh, B. Zhu and E. Micheli-Tzanakou, Neural networks and blood cell identification, Journal of Medical Systems, Springer Netherlands 21 (4) (Aug. 1997) 201-210.
2. W. Lin, J. Xiao and E. Micheli-Tzanakou, A computational intelligence system for cell classification, IEEE International Conference on Information Technology applications to Biomedicine (May 1998) 105-109.
3. W. Shitong and W. Min, A New detection algorithm (NDA) based on fuzzy cellular neural networks for white blood cell detection, IEEE Transactions on Information Technology in Biomedicine 10 (1) (Jan. 2006) 5-10.
4. B. F. Buxton, H. Abdallahi, D. Fernandez-Reyes and W. Jarra, Development of an extension of the Otsu algorithm for multidimensional image segmentation of thin-film blood slides, IEEE International Conference on Computing: Theory and Applications (March 2007) 552-562.
5. F. Scotti, Robust segmentation and measurements techniques of white cells in blood microscope images, IEEE Instrumentation and Measurement Technology Conference (April 2006) 43-48.
6. W. Wang, H. Song and Q. Zhao, A modified watersheds image segmentation algorithm for blood cell, IEEE International Conference on Communications, Circuits and Systems 1 (June 2006) 450-454.
7. F. Yi, Z. Chongxun, P. Chen and L. Li, White blood cell image segmentation using on-line trained neural network, IEEE Conference on Engineering in Medicine and Biology (Sep. 2005) 6476-6479.
8. N. Theera-Umpon and S. Dhompongsa, Morphological granulometric features of nucleus in automalic bone marrow white blood cell classification, IEEE Transactions on Information Technology in Biomedicine 11 (3) (May 2007) 353-359.
9. S. Mircic and N. Jorgovanovic, Application of neural network for automatic classification of leukocytes, IEEE 8th Seminar on Neural Network Applications in Electrical Engineering (Sep. 2006) 141-144.
10. T. Markiewicz, S. Osowski, B. Marianska and L. Moszczynski, Automatic recognition of the blood cells of myelogenous leukemia using SVM, Proceedings of International Joint Conference on Neural Networks, Canada (Aug. 2005) 2496-2501.
11. Q. Zheng, B. K. Milthorpe and A. S. Jones, Direct neural network application for automated cell recognition, Cytometry Part A Journal, Wiley-Liss Inc. 57 (1) (Jan. 2004) 1-9.
12. A. Khashman, IBCIS: Intelligent blood cell identification system, Progress in Natural Science, Elsevier Science Inc. Vol. 18 (2008) 1309-1314.
13. A. Khashman, Face recognition using neural networks and pattern averaging, Lecture Notes on Computer Science, Springer-Verlag, Berlin Heidelberg New York 3972 (May 2006) 98-103.