Tumor Detection and Segmentation Using Watershed and Hierarchical Clustering Algorithms | Abstract

ISSN ONLINE(2320-9801) PRINT (2320-9798)

Special Issue Article Open Access

Tumor Detection and Segmentation Using Watershed and Hierarchical Clustering Algorithms

Abstract

Tumor is an abnormal mass of tissue which may be solid or fluid. Tumor is a collection of cells forming a lump or mass. The tumor is of different types and they have different characteristics and different treatment. This tumor, when turns in to cancer become life-threatening. So medical imaging, it is necessary to detect the exact location of tumor and its type. For locating tumor in magnetic resonance image (MRI) segmentation of MRI plays an important role.MRI is the preferred technology which enables the diagnosis and evaluation of brain tumor. The current work presents a Watershed method for tumor segmentation and hierarchical clustering algorithm that is employed to cluster brain tumor. Comparing to the other clustering techniques the performance of hierarchical clustering plays a major role. The patient's stage is determined by this process, whether it can be cured with medicine or not

R. Rajeswari , G. Gunasekaran

To read the full article Download Full Article | Visit Full Article