Yun-Ni Ting

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Noise removal in MR images has been challenging due to the unpleasant noise with a Rician distribution, which is signal dependent. Denoising of MR images is of importance for subsequent diagnoses and analyses, such as tissue classification, segmentation, and registration. We propose a post-acquisition denoising algorithm to adequately and adaptively remove(More)
In magnetic resonance imaging(MRI), there has been a tradeoff between the scan time and NEX in order to produce high quality images. Clinically, small NEX values corresponding to reduce scan times are usually used that increases inevitable noise, which obeys a Rician distribution. We propose on automatic filtering method based on noise estimation and(More)
Magnetic resonance imaging has been widely applied in many clinical diagnoses. In order to increase the accuracy of diagnosis, it is crucial to improve the image quality. This paper proposed a method that modifies the bilateral filter with automatic parameter selection in local contrast correction (LCC) capable to adjust image contrast while maintaining(More)
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