研究限制及未來研究方向

根據以上結果，線性模型的演算提升，對於超音波影像來說，在影像品質的 對比度與訊雜比提升是有相當的幫助，但也有些限制及缺點，在未來需要多做測 試及研究：

(1) 機器的探頭老舊，壓電晶體的衰減下，在音波發射後收集反射回來的聲波就 不夠靈敏了，故在訊號轉換成影像上，也會有些許的影響。因此，機器本身 的構造及影像解析度，及探頭的新舊程度，都會影響影像的品質，間接影響 演算的提升率。本次只使用兩種機器，那未來是否能運用在其他品牌的超音 波掃描儀，是我們未來可以去實驗並探討的。

(2) 演算法的套用對於對比度的提升，有非常明顯的效果，而在主動脈訊雜比 (SNR1)與脂肪訊雜比(SNR2)就沒有達到所預期的效果了，推估原因可能是因 為主動脈和脂肪在超音波的表現上皆是有固定回音的表現，即便是解析度不 佳的儀器，都能分辨出這兩者器官的不同，所以在這兩部分訊雜比的提升上，

就無太大的收穫，這是需要再多做實驗與探討的，未來可再多測試其他的影 像優化的演算法，以克服此難題。

(3) 目前演算法專用於 B-Mode 的灰階影像，對於其他的模式的超音波是否能夠 使用？這是需要再多做測試與實驗。由於目前演算法是套用在單一影像來做 提升，在運動模式下能否也能有如此效果，或者是杜普勒影像也能達到影像

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優化，必頇要不斷的測試修正甚至撰寫，才能符合臨床所預期的診斷需求，

未來會朝這方面去努力。

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