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___________幾種圖像去噪算法的仿真分析及其在fMRI數(shù)據(jù)處理中的應(yīng)用_________ Simulation analysis of several image denoising algorithms and its application in fMRI data processing |
| 作者： 胡穎 郁蕓 周蕾蕾 胡新華 楊坤 |
| 單位： 南京醫(yī)科大學(xué)基礎(chǔ)醫(yī)學(xué)院(南京210029) |
| 關(guān)鍵詞： 平滑算法；仿真；功能核共振；噪聲 |
| 分類號(hào)： R318.04 |
| 出版年·卷·期（頁(yè)碼）：2016·35·2（156-160） |
| 摘要： |
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目的 去除圖像噪聲是醫(yī)學(xué)圖像處理過(guò)程中的基本預(yù)處理步驟，對(duì)圖像的后繼分析處理的質(zhì)量有重大影響。本文基于圖像去噪和醫(yī)學(xué)圖像的診斷準(zhǔn)確率息息相關(guān)這一現(xiàn)實(shí)問(wèn)題，對(duì)幾種圖像去噪算法進(jìn)行仿真分析，并實(shí)現(xiàn)功能磁共振（functional magnetic resonance imaging, fMRI）數(shù)據(jù)應(yīng)用。方法 首先闡述了幾種常用圖像去噪算法的基本原理，其次使用不同算法對(duì)加入高斯噪聲的Lena圖像進(jìn)行去噪仿真，并對(duì)不同結(jié)果的峰值信噪比（peak signal-to-noise ratio, PSNR）和均方差（mean square error, MSE）進(jìn)行比較，最后總結(jié)并選擇最優(yōu)降噪算法應(yīng)用于fMRI數(shù)據(jù)分析中，以期獲得較好的后期處理基礎(chǔ)。結(jié)果 小波分層閾值算法在fMRI處理中的峰值信噪比和均方差更優(yōu)。結(jié)論 在fMRI圖像去噪過(guò)程中，利用小波分層閾值算法更能提高圖像的信息利用率，有助于提高醫(yī)師診斷的準(zhǔn)確率。 |
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Objective Image denoising is a basic pretreatment of medical image processing, which has a significant impact on the quality of subsequent analysis and processing of the image. Certain analysis and simulation of the image denoising algorithms are made in this paper. Methods Firstly, we describe the basic principles of several common image denoising algorithms. Secondly, we use different algorithms to do denoising simulation with the Lena image added with Gaussian noise, and then compare the different results of peak signal-to-noise ratio (PSNR) and mean square error (MSE). Finally, we summarize and choose the optimal image denoising algorithm in the application of functional magnetic resonance imaging (fMRI) data analysis to obtain better post-processing foundation. Results The results of PSNR and MSE by using wavelet hierarchical threshold algorithm in fMRI are better. Conclusions In fMRI denoising, wavelet hierarchical threshold algorithm can improve the utilization of image information and increase the physician’s diagnostic accuracy. |
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地址：北京安定門外安貞醫(yī)院內(nèi)北京生物醫(yī)學(xué)工程編輯部 電話：010-64456508 傳真：010-64456661 電子郵箱：[email protected] |