Medical Image Segmentation using Marker Controlled Watershed Transformation
Mandeep Kaur, Gagandeep Jindal · 2011
Segmentation refers to the process of partitioning a digital image into multiple segments (sets of pixels, also known as superpixels). The goal of segmentation is to simplify and/or change the representation of an image into something that is more meaningful and easier to analyze. Image segmentation is used to cluster pixels into salient image regions, i.e., regions corresponding to individual surfaces, objects, or natural parts of objects. The watershed transform has interesting properties that make it useful for many different image segmentation applications: it is simple and intuitive, can be parallelized, and always produces a complete division of the image. However, when applied to medical image analysis, it has important drawbacks (oversegmentation, sensitivity to noise).In this paper medical image segmentation using marker controlled watershed segmentation is presented. Objective of this paper is segmenting the medical image using marker controlled watershed segmentation, and comparing the results of directly applying watershed transformation and marker controlled watershed transformation.