食道腫瘤放射治療在製作治療計劃的過程中，針對腫瘤因呼吸及胸腔內如心跳、吞嚥蠕動等作用產生的移動，需加入2-3公分的安全邊距。其中機器的變異性及每日設定的誤差所需的邊距，可藉由品質保證量測及治療前驗證片拍攝評估。而食道移動所需的內部安全邊距，目前僅採用普遍的經驗值加設。
本研究的目的是藉由分析x光透視攝影，觀察食道因受腫瘤壓迫所形成鋇劑聚積，在影像序列間位置隨時間的變化，提供治療計劃中所需內部安全邊距的相關資訊。本研究所提出之自動化邊緣分割演算法，主要分為影像前置處理、影像邊緣偵測、邊緣訊號後處理及移動定量分析四個部分。
食道x光透視攝影，經自動化邊緣分割演算法處理後，可得和腫瘤相關的食道在頭腳向的移動為0.6-1.74公分、在前後向的移動為0.2-0.6公分。且演算法分析30秒之透視影像序列僅需5分鐘的處理時間。因此本研究所提出之自動化邊緣偵測演算法，可快速的提供治療計畫中個別病患所需的內部安全邊距，有效的縮減正常組織接受高劑量照射，提升放射治療之成效。

As the prescribed dose difference between tumor cell and normal tissue increases due to the advances of treatment technology, the treatment planning becomes more sensitive to treatment uncertainties. Among various treatment uncertainties, accurate evaluation of organ motion is a key factor to quality improvement in treatment planning.
In this study, we propose an automatic boundary extraction algorithm to extract medium-contrast enhanced esophagus in fluoroscopy. The algorithm is based on image thresholding, image edge detection, morphological closing to identify the esophageal boundary, and motion quantification of mass center.
The results of boundary extraction can provide an accurate motion estimate of the internal margins in superior-inferior direction around 0.6~ 1.74cm, and in anterior-posterior around 0.2~ 0.6cm. The algorithm can also extract edge position in the image sequence automatically and identify esophageal boundary efficiently.
Our experimental results have indicated the amount of esophageal motion extracted by the proposed algorithm serves as a good reference for the internal margin needed in radiotherapy. It is clinically feasible to increase the prescribed tumor dose while to reduce the normal tissue absorption.

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