| DC 欄位 |
值 |
語言 |
| DC.contributor | 機械工程學系 | zh_TW |
| DC.creator | 黃福文 | zh_TW |
| DC.creator | Fu-wen Huang | en_US |
| dc.date.accessioned | 2010-7-1T07:39:07Z | |
| dc.date.available | 2010-7-1T07:39:07Z | |
| dc.date.issued | 2010 | |
| dc.identifier.uri | http://ir.lib.ncu.edu.tw:88/thesis/view_etd.asp?URN=963203084 | |
| dc.contributor.department | 機械工程學系 | zh_TW |
| DC.description | 國立中央大學 | zh_TW |
| DC.description | National Central University | en_US |
| dc.description.abstract | 肝臟診斷與治療最常用的方式是超音波影像掃描，二維的超音波影像雜訊多，且缺乏空間方位資訊，容易造成誤診。若能經由影像間對位技術，將超音波影像與電腦斷層影像融合，則可提供醫師三維且更清晰的影像資訊，對提升診斷與手術品質有相當的助益。本研究提出一套藉由肝臟的血管影像特徵，來自動進行電腦斷層影像與超音波影像的對位及融合。
先將徒手掃描的超音波影像重建成超音波立體影像，再將電腦斷層影像與超音波立體影像經由影像處理擷取出血管輪廓，血管輪廓經由三維數位拓樸關係，得到血管中心線，最後經由初始對位與疊代最近點(Iterative closest point, ICP)演算法，得到電腦斷層影像與超音波影像的座標轉換關係，並以影像相似性量測來評估其對位準確度。實驗使用自製的肝臟血管假體模型來測試，實驗結果顯示不同方位但相同血管模型的對位準確度大約可達到78%；而不同方位但血管模型變形的對位準確度大約可達到66%。此一研究方法若加入非剛性對位補償，應可用作肝臟電腦斷層影像與超音波影像之對位融合。
| zh_TW |
| dc.description.abstract | Ultrasound imaging is the most popular approach for liver diagnosis and surgery. Two-dimensional ultrasound images have terrible noises and are lack of spatial information. Sometimes, it is difficult to avoid misdiagnosis. If CT and US images can be registered and fused through mapping techniques, three-dimensional and clear information will enable doctors to improve diagnosis and surgery quality. This study proposed an image registration method based on the blood vessels of the liver to automatically fuse CT and US images.
The freehand-scanned ultrasound images are first reconstructed into 3D ultrasound image model. Then profiles of blood vessels of CT and 3D ultrasound image models are extracted by using image processing. The center lines of the vessels can be determined through 3D digital topology relation. Finally, the transformation matrix between CT and ultrasound images can be found by applying preliminary registration with interactive closest point algorithm. Image similarity measure is used to evaluate the registration accuracy. In the experiments, self-designed liver vessels phantoms are applied to verify the proposed methods. The results show that registration accuracy of the two modalities using identical phantoms but in different positions can reach about 78%, while that using normal and deformed phantoms is approximately 66%. Base on the result, the proposed method integrated with non-rigid deformation offset will enable the registration and fusion of CT and ultrasound liver images.
| en_US |
| DC.subject | 影像相似性 | zh_TW |
| DC.subject | 影像融合 | zh_TW |
| DC.subject | 影像對位 | zh_TW |
| DC.subject | 肝臟手術 | zh_TW |
| DC.subject | fusion | en_US |
| DC.subject | registration | en_US |
| DC.subject | liver resection surgery | en_US |
| DC.subject | image similarity measurement | en_US |
| DC.subject | ICP algorithm | en_US |
| DC.title | 肝臟血管電腦斷層影像與超音波影像之剛性融合 | zh_TW |
| dc.language.iso | zh-TW | zh-TW |
| DC.title | Rigid fusion of CT and ultrasound hepatic vascular images | en_US |
| DC.type | 博碩士論文 | zh_TW |
| DC.type | thesis | en_US |
| DC.publisher | National Central University | en_US |