Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/6209
標題: 立體磁振造影血管顯像術
Stereoscopic Magnetic Resonance Angiography
作者: 周正杰
關鍵字: 
出版社: 電機工程學系
摘要: 
摘要
由於醫學影像造影時間所形成的限制,一般所獲得的醫學影像都是二維平面的影像,導致必須犧牲影像深度的資訊,而如何將二維影像重建成三維影像便成為醫學影像研究上的一個重要課題。
磁振造影血管顯影術是一種將人體內血管顯示出來但不顯示其它任何組織的造影技術。其產生的影像有兩種,一種為將三度空間的血管投影到二維平面的投影影像(二維血管顯影術),另一種則是取得完整的三度空間資訊的三度空間醫學影像(三維血管顯影術)。第二種影像的優點,在於可以隨心所欲去觀察任一角度的資訊,缺點則是造影的時間非常長。當時間受到限制時,只能犧牲掉深度資訊,以二維的投影影像來診斷病變。為了能滿足時間的限制,也能還原影像深度的資訊,在本篇論文中我們研究以二維影像重建立體血管的方法。
立體磁振造影血管顯像術,是利用兩個角度的血管投影影像,來重建立體血管影像。和一般X光血管顯像術所產生的投影影像比較,X光投影影像中像素亮度值,可視為光線行進路徑上所有物質衰減值的積分,因此可由此積分進而反推物體的形狀。但是磁振造影血管顯像術成像的參數很多(例如:T1、T2、質子密度、與共振偏移等),影響像素亮度的參數也非常多,所以很難由像素亮度值直接推得與物體形狀的關係。
因此,我們放棄以像素值來作為推得物體形狀的參數,而改以空間幾何的方式來還原物體形狀,可以假設血管切面的形狀近似橢圓形,再將從投影影像中取得的邊界值,配合所導出的演算法,求得橢圓形的參數,即可還原血管切面形狀,而得到立體血管影像。
本篇論文也以實際的例子,來重建實際的三度空間血管影像。由從台中榮總醫院所獲得的80張磁振造影血管影像,我們取其中50張影像,分別作左右各150的投影,當作實際血管投影影像。然後取得邊界值,以推導而得的演算法算出切面形狀的參數,重建血管三度空間模型。把還原的影像再作同樣角度的投影,將獲得的邊界值與原始的邊界值做比較,其平均誤差為0.471。

Abstract
Magnetic resonance angiography (MRA) is an imaging technique to show the blood vessels but suppress signals from all the other tissues. There are two approaches to acquire an image of MRA. One is done in two dimension by projecting the 3-D vessels onto 2-D plane. The other is to directly obtain the complete 3-D information. The advantage of 3-D MRA is that one can view the data from arbitrary direction. However, the scan time is usually very long for 3-D MRA. When the scan time is limited, we must use 2-D MRA and the depth of information is sacrificed. In this thesis, we research on the subject of recovering the depth information by reconstructing 3-D vessels from two projective MRA images.
Stereoscopic angiography utilizes two images by projecting blood vessels onto 2-D plane in two angles. Two major modalities are digital subtraction angiography (DSA) and magnetic resonance angiography (MRA). For DSA, the pixel value is the integration of the attenuation value in the path of the X ray. We can use this property to derive the shape of the vessels by solving the integrals. On the other hands, there are many imaging parameters in MRA (such as T1 , T2 and proton density). Therefore, it is difficult to obtain the relation between the shape of the vessels and the pixel intensity. Therefore, we attempt to reconstruct the shape of the vessels by geometry. We assume that the shape of the vessel on every cross-section is an ellipse. Then, we develop an algorithm to estimate the parameters of the ellipse from the boundaries of the projective images. The reconstructed ellipses are then taken as the 3-D shape of the vessels.
Eighty images of MRA were used to demonstrate the capability of our algorithm. From these images, we use fifty images to make two projective images. The two projections are 300 apart. We employ our algorithm to estimate all the ellipses and reconstruct the 3-D model of the vessels. Comparing the boundaries of the original projective images with the boundaries of the reconstructed 3-D model, the average error is 0.471 pixels.
URI: http://hdl.handle.net/11455/6209
Appears in Collections:電機工程學系所

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