A Survey on Noisy Medical Image Segmentation using Clustering

Manisha Sutar1 and N. J. Janwe2

1M.Tech. (C.S.E.), R.C.E.R.T. Chandrapur (MS).

2Dept. of Comp. Tech. R.C.E.R.T. Chandrapur (MS).


Image segmentation plays a crucial role in many medical imaging applications by automating or facilitating the delineation of anatomical structures and other regions of interest. In medical field, segmentation of images like brain MR images, CT scan images, Ultrasound images etc., is a very important image processing step in many applications including automatic and semiautomatic delineation of areas to be treated prior to radiosurgery, delineation of tumors before and after surgical intervention for response assessment. We present herein a critical appraisal of the current status of semi-automated and automated methods for the segmentation of anatomical medical images. Current segmentation approaches are reviewed with an emphasis placed on revealing the advantages and disadvantages of these methods for medical imaging applications. The use of image segmentation in different imaging modalities is also described along with the difficulties encountered in each modality. We conclude with a discussion on the future of image segmentation methods in biomedical research.

Keywords: Image segmentation, Medical imaging, Brain MR images, CT scan images, Ultrasound images, Imaging modalities.

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