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A Novel ECFT Algorithm to Improve the Excellence of Computer Tomography Images for Effective Segmentation
In the advancement of cancer treatment, radio therapy still remains one of the important therapies. Diagnosing tumor is also a significant task in the medical field. Resulting is image based diagnosis plays a vital role in the treatment of tumors. CT images have traditionally provided the essential information used to identify treatment volumes. Computed Tomography (CT) is the most important modality for image based treatment planning, treatment simulation and dose calculation for tumor diagnosis. Image diagnosis is a challenging problem for researchers in computer scientist as well as the medical field because noise removal introduces artifacts and causes blurring of the images. In this paper, different Computer Tomography image noises, artifacts and filters were analysed. A novel filtering ECFT (Enhanced Curvelet Filtering Technique) is proposed to improve the quality of the CT images. Real time Dataset are used to evaluate the performance of filtering algorithms and the experimental results demonstrate the noise removal based on ECFT shows acceptable efficiency in image quality compared with other filtering techniques.
Image filters, Computed tomography, image noise, artifacts, image quality.
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