Robust segmentation of cancer affected white blood cells using modified level set algorithm

Kalaiselvi Kalaiselvi (Kongu Engineering College); Asokan Ramasamy (Kongu Engineering College, India)

Cancer cells are multiplicative in nature. Doctors face difficulties in counting the white blood cells (WBCs) at a particular stage due to crowding of cells. This paper proposes the robust segmentation algorithm that can reliably separate touching cells. Segmentation is the main important step in medical image processing. Precisely locating the area of interest in an image, in the presence of inherent uncertainty and ambiguity, is a challenging problem in medical imaging. Hence, one is often faced with a situation that demands proper segmentation. The algorithm is composed of two steps. It begins with a detecting and finding the cells in the region that utilizes level set algorithm. Next, the contour of big cell is obtained using modified level set active contour based on a piecewise smooth function. Finally, the proposed algorithm is compared with several images which aids in applications such as locating the tumors and other pathologies etc.,

Journal: International Journal of Simulation- Systems, Science and Technology- IJSSST V14

Published: Feb 28, 2013

DOI: 10.5013/IJSSST.a.14.01.02