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Three Dimensional Reconstruction of Blood Vessels from Stereoscopic Magnetic Resonance Angiography

以立體血管顯像術重建三維血管模型之演算法

摘要


磁振造影血管顯像術是一種將人體內血管顯示出來但不顯示其它任何組職的造影技術,其產生影像有兩種方法:一種為將三度空間的血管投影到二維平面的投影像,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。三維血管顯像術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。為了縮短造影時間,通常是使用二維血管顯像術來診斷病變,但是這樣會犧牲掉深度資訊。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。因此我們改以血管空間幾何的關係來還原血管的形狀,假設血管為傾斜直圓柱而血管切面形狀則會近似於橢圓形,再從投影影像中取得血管的邊界值,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。我們以實際的三度空間磁振造影像,來重建三度空間血管影像,以驗證所導出的演算法。將每一張三度空間磁振造影像做兩張30度差的投影,而得到兩張投影影像,以推導而得的演算法算出切面形狀的參數,重建血管二度空間模型,然後將重建之立體血管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0.1011像素。

並列摘要


Magnetic resonance angiography (MRA) was an imaging technique to show the blood vessels but suppress signals from all the other tissues. There were two approaches to acquire an image of MRA. One was done in two-dimension (2-D) by projecting the three-dimensional (3-D) vessels onto 2-D plane. The other was to directly obtain the complete 3-D information. The advantage of 3-D MRA was that one can view the data from arbitrary direction. However, the scan time was usually very long for 3-D MRA. When the scan time was limited, we must use 2-D MRA and the depth information was lost. The depth information could be partially recovered using stereoscopic angiography, i.e., acquiring two 2-D images from different viewing angles. In addition to the stereoscopic views, stereoscopic angiography could also be used to reconstruct the 3-D shapes of the vessels. However, 3-D reconstruction was used more frequently in digital subtraction X-ray angiography (DSA). The main reason was that pixel intensity was directly related to the integration of the attenuation value along the path of the X-ray in DSA. Therefore, we could derive the vessel shape by solving the integrals from the two views. On the other hands, there were many imaging parameters in MRA (T1, T2, and proton density). Therefore, it was difficult to obtain the relation between the vessel shape and the pixel intensity. For this reason, we attempted to reconstruct the shape of the vessels simply from the edge information of the two views. We assumed that the shape of the vessel on every cross-section was an ellipse. Then, we developed an algorithm to estimate the parameters of the ellipse from the boundaries of the projective images. A 3-D MRA data set was used to test the capability of our algorithm. From these data, we made two projective images. The two projections were 30° apart. We employed 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 was 0.1011 pixels.

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