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  2. 電機資訊學院
  3. 資訊網路與多媒體研究所
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/101452
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dc.contributor.advisor洪一平zh_TW
dc.contributor.advisorYi-Ping Hungen
dc.contributor.author謝獻沅zh_TW
dc.contributor.authorHsien-Yuan Hsiehen
dc.date.accessioned2026-02-03T16:23:51Z-
dc.date.available2026-02-04-
dc.date.copyright2026-02-03-
dc.date.issued2026-
dc.date.submitted2026-01-26-
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dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/101452-
dc.description.abstract肺結節定位是胸腔鏡次肺葉切除手術前的關鍵步驟,傳統上多依賴電腦斷層影像(CT)導引定位。本研究提出一套基於延展實境(XR)的肺結節定位系統。術前在病人身上貼附可在CT中顯影的基準標記並標示位置,據術前CT重建包含基準標記與器官之數位孿生模型。術中依照病人身上標示之特殊圖樣,將平面標記復位後,偵測並估計平面標記在空間中的位置,基準標記與平面標記兩者經配準後達成器官模型與體表的對齊。術者可於系統中規劃染劑定位針的穿刺路徑,並在系統導引下完成肺結節染劑定位。本研究於複合式手術室中進行驗證,共納入15名病患,定位完成後以術中CT評估定位誤差,平均定位誤差為7.9 mm(標準差 5.1 mm)。zh_TW
dc.description.abstractLung nodule localization is a critical step prior to sublobar resection in video-assisted thoracoscopic surgery. Traditionally, localization relies on CT-guided techniques. This study proposes an extended reality (XR)-based localization system. Prior to surgery, radiopaque fiducial markers are attached to the patient's body, and their positions are marked. Digital twin models, including the fiducial markers and relevant organs, are reconstructed from preoperative CT images. Intraoperatively, planar markers are repositioned according to the marked skin patterns. The spatial pose of the planar markers is then detected and estimated. Registration between the fiducial and planar markers aligns the organ models with the body. The system allows the surgeon to plan the puncture path for dye localization, which is then executed under XR guidance. The system was validated in a hybrid operating room in 15 patients. Localization error was evaluated using intraoperative CT. The mean localization error was 7.9 mm (SD: 5.1 mm).en
dc.description.provenanceSubmitted by admin ntu (admin@lib.ntu.edu.tw) on 2026-02-03T16:23:51Z
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dc.description.provenanceMade available in DSpace on 2026-02-03T16:23:51Z (GMT). No. of bitstreams: 0en
dc.description.tableofcontentsVerification Letter from the Oral Examination Committee i
Acknowledgements ii
摘要 iii
Abstract iv
Contents v
List of Figures viii
List of Tables ix
Chapter 1 Introduction 1
1.1 Clinical Background 1
1.2 XR and Digital Twins 2
Chapter 2 Related Work 5
2.1 CT-Guided Lung Nodule Localization 5
2.2 XR-Guided Lung Nodule Localization 6
Chapter 3 Design Considerations 8
3.1 Patient Setup and Positioning Design 8
3.2 Fiducial Marker Chosen Strategy 9
3.2.1 Exploratory Design Attempts 9
3.2.2 Two-Stage Fiducial Design 11
3.3 Fiducial Marker Placement and Tattoo Sticker Design 13
Chapter 4 Method 15
4.1 Overview 15
4.2 Generation of Digital Twin Organ Models 17
4.2.1 Patient Positioning 17
4.2.2 CT Imaging with Fiducial Markers 17
4.2.3 3D Reconstruction 19
4.3 Marker-Based Registration 21
4.3.1 Planar Markers Reposition 21
4.3.2 Marker Detection and Pose Estimation 21
4.3.3 Registration of Fiducial and Planar Markers 24
4.4 XR-Guided Localization 26
4.4.1 Puncture Path Determination 26
4.4.2 Execution of Localization 28
4.5 User Interface 30
Chapter 5 Results and Discussions 32
5.1 Experimental Setup 32
5.2 Results 33
5.2.1 Localization Results 33
5.2.2 Monte Carlo Simulation Results 35
5.3 Discussion and Limitations 38
5.3.1 Discussion on Localization Results 38
5.3.2 Discussion on Monte Carlo Simulation 42
Chapter 6 Conclusion and Future Work 44
References 46
-
dc.language.isoen-
dc.subject延展實境-
dc.subject肺結節定位-
dc.subject數位孿生-
dc.subject虛實配準-
dc.subject電腦斷層-
dc.subjectExtended Reality-
dc.subjectLung Nodule Localization-
dc.subjectDigital Twin-
dc.subjectVirtual-to-Real Registration-
dc.subjectComputed Tomography-
dc.title基於XR導引之肺結節定位zh_TW
dc.titleXR-Guided Lung Nodule Localizationen
dc.typeThesis-
dc.date.schoolyear114-1-
dc.description.degree碩士-
dc.contributor.oralexamcommittee陳晉興;林風;柯宗瑋;韓秉軒zh_TW
dc.contributor.oralexamcommitteeJin-Shing Chen;Phone Lin;Tsung-Wei Ke;Ping-Hsuan Hanen
dc.subject.keyword延展實境,肺結節定位數位孿生虛實配準電腦斷層zh_TW
dc.subject.keywordExtended Reality,Lung Nodule LocalizationDigital TwinVirtual-to-Real RegistrationComputed Tomographyen
dc.relation.page52-
dc.identifier.doi10.6342/NTU202600278-
dc.rights.note同意授權(限校園內公開)-
dc.date.accepted2026-01-27-
dc.contributor.author-college電機資訊學院-
dc.contributor.author-dept資訊網路與多媒體研究所-
dc.date.embargo-lift2026-02-04-
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