Abstract—In this work, an image analysis approach for automated detection, segmentation, and classification of particular cells, specially the cancer cells from normal cells is introduced. In this technique we can also count the number of defected cells and find their position with image processing. The results of this analysis are useable in designing a neural network for more accurate analysis. The particular cells segregation is the most important property of this work. Using the LABVIEW Software gave practical usages to this image processing system because it can communicate with other equipments used in this system and controls them in order to have an automatic system. This demonstrates the potential effectiveness of such a system on diagnostic tasks that require the classification of individual cells.
Index Terms—Convolution, fast fourier transforms, gaussian processes, LABVIEW.
Hossein Ghayoumi Zadeh and Javad Haddadnia are with Bio Medical Engineering Department, Hakim Sabzevari University, Sabzevar, Iran (e-mail: h.ghayoumizadeh@gmail.com, haddadnia@sttu.ac.ir).
Siamak Janianpour is with Electrical and Computer Engineering Department, Hakim Sabzevari University, Sabzevar, Iran (e-mail: s.janianpour@ieee.org).
Cite: Hossein Ghayoumi Zadeh, Siamak Janianpour, and Javad Haddadnia, "Recognition and Classification of the Cancer Cells byusing Image Processing and Lab VIEW," International Journal of Computer Theory and Engineering vol. 5, no. 1, pp. 104-107, 2013.
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