Wavelet-based multiscale level-set curve evolution in noise reduction for MR imaging

Junmei Zhong; Bernard Dardzinski; Janaka Wansapura

doi:10.1117/12.651920

20 March 2006 Wavelet-based multiscale level-set curve evolution in noise reduction for MR imaging

Junmei Zhong, Bernard Dardzinski, Janaka Wansapura

Proceedings Volume 6144, Medical Imaging 2006: Image Processing; 614468 (2006) https://doi.org/10.1117/12.651920
Event: Medical Imaging, 2006, San Diego, California, United States

Abstract

In magnetic resonance (MR) imaging, there is a tradeoff between the spatial resolution, temporal resolution and signal to noise ratio (SNR). MR images usually suffer from low SNR and low resolutions. In order to make it practical for MR imaging with higher resolutions as well as sufficient SNR, it is necessary to reduce noise efficiently while preserving important image features. In this paper, we propose to use the wavelet-based multiscale level-set curve evolution algorithm to reduce noise for MR imaging. Experimental results demonstrate that this denoising algorithm can significantly improve the SNR and contrast to noise ratio (CNR) for MR images while preserving edges with good visual quality. The denoising results indicate that in MR imaging applications, we can almost doubly improve the temporal resolution or improve the spatial resolution while achieving sufficient SNR, CNR, and satisfactory image quality.

Citation Download Citation

Junmei Zhong, Bernard Dardzinski, and Janaka Wansapura "Wavelet-based multiscale level-set curve evolution in noise reduction for MR imaging", Proc. SPIE 6144, Medical Imaging 2006: Image Processing, 614468 (20 March 2006); https://doi.org/10.1117/12.651920

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