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圖像域自適應(yīng)線性自回歸MRI圖像客觀質(zhì)量提升算法研究 An in-planeobjective quality enhancement algorithm of 3D MRI via linear AR model |
| 作者： 武博 李文志 張旭 段娟 孫智 梁志遠(yuǎn) 張楠 |
| 單位：首都醫(yī)科大學(xué)生物醫(yī)學(xué)工程學(xué)院(北京100069) |
| 關(guān)鍵詞： 圖像插值；客觀質(zhì)量提升重建；線性自回歸模型；加權(quán)最小二乘法；距離權(quán)重 |
| 分類號(hào)：R318.04 |
| 出版年·卷·期（頁碼）：0·0·0（0-0） |
| 摘要： |
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目的 磁共振成像(magnetic resonance imaging, MRI)是臨床醫(yī)學(xué)影像檢查的重要手段，然而受限于檢查時(shí)間，高客觀質(zhì)量的MRI圖像難以獲得，有效提高M(jìn)RI圖像分辨率成為研究熱點(diǎn)。本文為高效地提高M(jìn)RI圖像分辨率，減少患者檢查時(shí)間，提出圖像域的基于線性自回歸模型自適應(yīng)客觀質(zhì)量提升算法。方法 首先，創(chuàng)建基于距離權(quán)重的自回歸模型獲得插值系數(shù)；其次，利用自適應(yīng)算法解決自回歸算法中插值矩陣病態(tài)的問題；最后，通過對(duì)標(biāo)準(zhǔn)數(shù)據(jù)庫中具有不同噪聲水平的圖像進(jìn)行測試。結(jié)果 本算法重建圖像的峰值信噪比（peak signal to noise ratio, PSNR）平均值比經(jīng)典算法提高1.8~4dB，結(jié)構(gòu)相似度（structural similarity index measurement, SSIM）指標(biāo)平均提高0.02~0.06。結(jié)論 圖像域自適應(yīng)線性自回歸MRI圖像客觀質(zhì)量提升算法在有效提高M(jìn)RI圖像分辨率的同時(shí)，保持了較高的客觀質(zhì)量。 |
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Objective Magnetic resonance imaging (MRI) is an important examination in clinical medical imaging. Objective quality enhancement (OBE) is a hot research topic and the aim is to effectively improve the resolution of the MRI. Methods First, an autoregressive interpolation algorithm based on the distance weighting factor is proposed. Second, considering the case of the ill-conditioned matrix, an adaptive interpolation method is adopted. Finally, the simulation is carried out on the brain MRI images with different noise levels from a standard matrix. Results Compared with other classic interpolation methods, the average peak signal to noise ratio (PSNR) of super resolution MRI obtained by this method improves 1.8dB to 4dB and the average structural similarity index measurement (SSIM) improves 0.02 to 0.06. Conclusions The proposed algorithm can effectively improve resolution of MRI and achieve a promising objective quality. |
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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] |