研究生: |
陳栩茹 Syu-Ru Chen |
---|---|
論文名稱: |
虛擬腹腔鏡手術訓練與評估系統之設計與開發 Design and Development of a Virtual Laparoscopic Surgery Training and Assessment System |
指導教授: |
林淵翔
Yuan-Hsiang Lin |
口試委員: |
吳晉賢
Chin-Hsien Wu 張宏 none 周迺寬 none |
學位類別: |
碩士 Master |
系所名稱: |
電資學院 - 電子工程系 Department of Electronic and Computer Engineering |
論文出版年: | 2014 |
畢業學年度: | 102 |
語文別: | 中文 |
論文頁數: | 84 |
中文關鍵詞: | 客觀評估 、腹腔鏡手術訓練 、虛擬實境 、微創手術 、器械軌跡偵測 |
外文關鍵詞: | objectively assessment, laparoscopic surgery, virtual reality, minimal invasive surgery, instrument tracking |
相關次數: | 點閱:479 下載:4 |
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相對於傳統開腹手術,微創手術具有傷口小、出血少、恢復期短等優點,但因為外科醫生需透過螢幕觀看內視鏡傳出來的畫面進行手術,所以醫生的手術技巧、穩定度、手眼協調能力就變的很重要。比起傳統手術,微創手術的困難度相對較高,所以外科醫師除了需有大量的知識訓練,還需透過有效的訓練工具進行技巧練習。如此,才能有效地降低實際手術的風險。
本論文所開發的虛擬腹腔鏡手術訓練與評估系統,主要包含三個部分,分別為定位裝置、訓練箱以及虛擬場景。我們自行開發的器械定位裝置可以偵測器械的空間座標、旋轉角度和開闔等資訊,可以提供可靠的器械定位資料。此外,在訓練箱內建置與虛擬畫面相對應的場景,以解決虛擬實境缺乏自然觸覺回饋的問題。
利用本系統的中的兩個訓練模組,穩定度訓練模組以及雙手夾球訓練模組,透過實驗收集專家與新手操作時的器械軌跡資料,找出專家與新手的辨識特徵,並以此差異訂出專家與新手的分類閥值,最後再將此閥值對新的一批受測者進行分類,區分的準確度可達91%以上。
Compared with the traditional open surgery, minimally invasive surgery (MIS) has the advantages of small incision, less blood and faster recovery. However, surgeons need to conduct operations by watching the monitor through the laparoscope, so their skills, stabilization and hand-eye coordination are vital, making MIS relatively difficult. Therefore, in addition to a large amount of knowledge, we need effective training tools to improve the dexterity of operations skills, thereby lowering the risk of the surgery.
The developed system of virtual laparoscopic training surgery in this paper includes three parts: an instrument positioning device, a training box and virtual reality (VR) scenes. We design a positioning device to capture the space coordinate, rotation angle and clip information from the surgery instruments, aim to provide reliable instrument positioning data. In order to solve the problem of lacking haptic feedback in VR, we construct some physical objects inside the training box to map the virtual scene.
There are two training modules in the training system, stable training module, and ball-clipping-by-two-hands training module. By collecting the instrument tracking data of experimental practice from experts and novices, this paper identifies the characteristics of experts and novices respectively, and finds different classification thresholds to experts and novices. The results show that its accuracy for classification can reach up 91%.
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