利用影像分叢與空間資訊之金屬假影矯正法

電腦斷層(computed tomography, CT)已成為創傷的第一線診斷工具，對於現今的臨床醫療帶來相當大的幫助及便利性，然而，當病人體內有金屬植入物時，該部位之影像便會產生大量的金屬假影，嚴重的影響影像品質。本研究提出一個以影像分叢為基礎的金屬假影矯正法，首先藉由加入空間資訊之k-means分叢技術建立模型影像，接著將原始影像與模型影像相減求出差異影像，並將此差異影像取絕對值常態化到1後，利用指數形式之加權函數求得加權因子，對原始及模型的投影資料加權，最後利用濾波反投影即可獲得矯正後影像。在圓柱形水假體的影像矯正之中，原本存在的亮暗紋可有效的移除，同時水的CT值由－28.95±97.97改善至－4.76±4.28。在骨盆腔CT影像的矯正之中可以發現金屬假影與亮暗帶已被移除，同時膀胱及軟組織的灰階值亦恢復為應有的均勻度與連續性，我們取四個有興趣區域(ROI)可以發現，矯正後軟組織的CT值皆較為接近理論值，且標準差也都降低至50%以下。我們認為此金屬假影矯正法能夠有效消除金屬假影對影像的損害，以提升影像之診斷價值。

關鍵字

電腦斷層；金屬假影； k-means分叢

並列摘要

Computed tomography (CT) has become one of most favorable choices for diagnosis of trauma. However, high-density metal implants in the CT scans induce metal artifact and compromise image quality. In this study, we proposed a model-based metal artifact correction method. First, we built a model image using k-means clustering technique with spatial information and calculated the difference between the original image and model image. The projection data of the original image and model image were then combined together by a weighting factor estimated from an exponential weighting function. At last, the corrected image was reconstructed using the filter back-projection method. In the cylindrical water phantom image, the metal artifact was removed. The CT number of water was improved from -28.95±97.97 to -4.76±4.28. In the clinical pelvic image, the dark band and metal line were removed and the continuity and uniformity of the CT number of the soft tissue were recovered as well. The CT numbers in the four ROI regions of the corrected image were approached to the theoretical value and standard deviations were below 50% as well. We conclude that the proposed method is useful for reducing the metal artifact and could improve the diagnostic value.

並列關鍵字

Computed tomography ； Metal artifact ； k-means clustering

國際替代計量

利用影像分叢與空間資訊之金屬假影矯正法

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