Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/6057
標題: 腦部功能性磁振影像的影像後處理技術研發
Post-processing of Brain Functional MR Imaging
作者: 戴佳坦
Dai, Chia-Tan
關鍵字: perfusion;灌流;rCBV;relative cerebral blood volume;rCBF;relative cerebral blood flow;tMTT;tissue mean transit time;相對腦血流容積;相對腦血流量;平均血流穿透時間
出版社: 電機工程學系
摘要: 
數年來,腦部磁振造影科技的研發日新月異,由於超高速及高解析度動態造影的發展,開啟了偵測腦中血流的新機。有關腦部功能性磁振影像及其相關之腦部擴散/灌流影像(diffusion/perfusion imaging)之技術亦日漸成熟。
在1.5T磁場強度之全身測量系統,以超高速及高解析度動態影像波序(EPI),患者在經靜脈快速注射對比劑(Gd+-DTPA, 0.2mmol/kg, 3cc/sec)後,以其在局部組織中 T2* 效應,獲取微血管灌流影像。整個灌流影像檢查動態過程共取9個切面,包括四十五個相位(Phase),以取得不同相位時影像中訊號的變化相,全部共405張灌流影像。將所得之灌流影像經由電腦處理得到有趣部位 (ROI, region of interest)的訊號強度對時間曲線;根據公式,T2*訊號強度的改變和顯影劑及血流量均呈現線性的關係。由此訊號強度對時間曲線獲得相對腦血流容積(rCBV, relative cerebral blood volume),相對腦血流量(rCBF, relative cerebral blood flow),和腦組織平均血流穿透時間(tMTT, tissue mean transit time),再由以上分析的資料產生不同的灌流組像(perfusion mapping)。
在此研究中,我們由GE的磁振造影檢查儀得到的影像原始資料經由轉換過程傳送至個人電腦,建立影像資料庫,並經由自動偵測讀取,濾波和遮罩等影像處理技巧作處理,再依數學計算公式的應用取得灌流影像的rCBV Mapping。

In recent years, the research and development of Magnetic Resonance Imaging (MRI) has proceeded very rapidly. The development of ultra-fast and high-resolution imaging methods has opened up brand new opportunities for detecting the status of blood flow in the brain. The technology of functional MRI and its related brain diffusion/perfusion imaging has become more and more mature recently.
In a whole body system of 1.5T magnet, we use a high-speed and high-resolution dynamic imaging sequence, to acquire the perfusion images of capillaries after intravenous administration of contrast media (Gd+-DTPA, 0.2mmol/kg, 3cc/sec). The entire imaging process took nine slices, including 45 phases for each slice, in order to obtain the temporal change of the signals . Through image processing, the curve of signal level versus time for the Region of Interest (ROI) in perfusion images was then generated. The relationship between the T2* signal changes and the volume of contrast medium (i.e., blood volume)is linear. From the curve of signals versus time, the Relative Cerebral Blood Volume (rCBV), Relative Cerebral Blood Flow (rCBF), and Tissue Mean Transit Time (tMTT) were obtained. Then, different perfusion mappings were generated.
In this thesis, we sent the images obtained from the GE-MRI scanner to a personal computer. After creating the imaging database, the data are processed to obtain the rCBV mapping through auto detection and a number of image-processing techniques, such as filtering and masking.
URI: http://hdl.handle.net/11455/6057
Appears in Collections:電機工程學系所

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