文章基本信息

标题：Modified Watershed Segmentation with Denoising of Medical Images
本地全文：下载
作者：USHA MITTAL ; SANYAM ANAND
期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2013
卷号：2
期号：4
页码：982
出版社：S&S Publications
摘要：De-noising and segmentation are fundamental steps in processing of images. They can be used as preprocessingand post-processing step. They are used to enhance the image quality. Various medical imaging that areused in these days are Magnetic Resonance Images (MRI), Ultrasound, X-Ray, CT Scan etc. Various types of noisesaffect the quality of images which may lead to unpredictable results. Various noises like speckle noise, Gaussian noiseand Rician noise is present in ultrasound, MRI respectively. With the segmentation region required for analysis anddiagnosis purpose is extracted. Various algorithm for segmentation like watershed, K-mean clustering, FCM,thresholding, region growing etc. exist. In this paper, we propose an improved watershed segmentation using denoisingfilter. First of all, image will be de-noised with morphological opening-closing technique then watershedtransform using linear correlation and convolution operations is applied to improve efficiency, accuracy and complexityof the algorithm. In this paper, watershed segmentation and various techniques which are used to improve theperformance of watershed segmentation are discussed and comparative analysis is done.
关键词：De-noising; Segmentation; Watershed; Region merging; RAG; Morphological Operations.