PIXEL RUN LENGTH BASED ADAPTIVE REGION GROWING (PRL-ARG)TECHNIQUE FOR SEGMENTATION OF TUMOR FROM MRI IMAGES

摘要

Segmentation of anatomical regions of a brain is the fundamental problem in pattern recognition in medical images. Lots of work has been reported, showing various level of accuracy in segmenting the boundary of an anatomy or tumor. The motivation for our work came from the fact of accurate delineation of the contour of a tumor from magnetic resonance images with high level of precision. We have developed an algorithm by modifying the existing Region Growing (RG) algorithm, by considering the local statistics of the pixels along with Pixel Run Length (PRL) parameter. PRL based Adaptive Region Growing (ARG) algorithm (PRL-ARG) gave satisfactory result with good level of accuracy. The segmented tumor is quantified by area, perimeter and form factor, which in tum helps to classify the different shape and contour of tumor. This algorithm is a semi - automated method and it will help the radiologist and neurologist to perform the diagnosis more effectively and accurately.