Computer Assisted Surgery最新文献

{"title":"Prediction of additional hospital days in patients undergoing cervical spine surgery with machine learning methods.","authors":"Bin Zhang, Shengsheng Huang, Chenxing Zhou, Jichong Zhu, Tianyou Chen, Sitan Feng, Chengqian Huang, Zequn Wang, Shaofeng Wu, Chong Liu, Xinli Zhan","doi":"10.1080/24699322.2024.2345066","DOIUrl":"https://doi.org/10.1080/24699322.2024.2345066","url":null,"abstract":"<p><strong>Background: </strong>Machine learning (ML), a subset of artificial intelligence (AI), uses algorithms to analyze data and predict outcomes without extensive human intervention. In healthcare, ML is gaining attention for enhancing patient outcomes. This study focuses on predicting additional hospital days (AHD) for patients with cervical spondylosis (CS), a condition affecting the cervical spine. The research aims to develop an ML-based nomogram model analyzing clinical and demographic factors to estimate hospital length of stay (LOS). Accurate AHD predictions enable efficient resource allocation, improved patient care, and potential cost reduction in healthcare.</p><p><strong>Methods: </strong>The study selected CS patients undergoing cervical spine surgery and investigated their medical data. A total of 945 patients were recruited, with 570 males and 375 females. The mean number of LOS calculated for the total sample was 8.64 ± 3.7 days. A LOS equal to or <8.64 days was categorized as the AHD-negative group (<i>n</i> = 539), and a LOS > 8.64 days comprised the AHD-positive group (<i>n</i> = 406). The collected data was randomly divided into training and validation cohorts using a 7:3 ratio. The parameters included their general conditions, chronic diseases, preoperative clinical scores, and preoperative radiographic data including ossification of the anterior longitudinal ligament (OALL), ossification of the posterior longitudinal ligament (OPLL), cervical instability and magnetic resonance imaging T2-weighted imaging high signal (MRI T2WIHS), operative indicators and complications. ML-based models like Lasso regression, random forest (RF), and support vector machine (SVM) recursive feature elimination (SVM-RFE) were developed for predicting AHD-related risk factors. The intersections of the variables screened by the aforementioned algorithms were utilized to construct a nomogram model for predicting AHD in patients. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve and C-index were used to evaluate the performance of the nomogram. Calibration curve and decision curve analysis (DCA) were performed to test the calibration performance and clinical utility.</p><p><strong>Results: </strong>For these participants, 25 statistically significant parameters were identified as risk factors for AHD. Among these, nine factors were obtained as the intersection factors of these three ML algorithms and were used to develop a nomogram model. These factors were gender, age, body mass index (BMI), American Spinal Injury Association (ASIA) scores, magnetic resonance imaging T2-weighted imaging high signal (MRI T2WIHS), operated segment, intraoperative bleeding volume, the volume of drainage, and diabetes. After model validation, the AUC was 0.753 in the training cohort and 0.777 in the validation cohort. The calibration curve exhibited a satisfactory agreement between the nomogram predictions and actual probabilities. T","PeriodicalId":56051,"journal":{"name":"Computer Assisted Surgery","volume":"29 1","pages":"2345066"},"PeriodicalIF":2.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141302103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ultrasound-based 3D bone modelling in computer assisted orthopedic surgery - a review and future challenges.","authors":"Benjamin Hohlmann, Peter Broessner, Klaus Radermacher","doi":"10.1080/24699322.2023.2276055","DOIUrl":"10.1080/24699322.2023.2276055","url":null,"abstract":"<p><p>Computer-assisted orthopedic surgery requires precise representations of bone surfaces. To date, computed tomography constitutes the gold standard, but comes with a number of limitations, including costs, radiation and availability. Ultrasound has potential to become an alternative to computed tomography, yet suffers from low image quality and limited field-of-view. These shortcomings may be addressed by a fully automatic segmentation and model-based completion of 3D bone surfaces from ultrasound images. This survey summarizes the state-of-the-art in this field by introducing employed algorithms, and determining challenges and trends. For segmentation, a clear trend toward machine learning-based algorithms can be observed. For 3D bone model completion however, none of the published methods involve machine learning. Furthermore, data sets and metrics are identified as weak spots in current research, preventing development and evaluation of models that generalize well.</p>","PeriodicalId":56051,"journal":{"name":"Computer Assisted Surgery","volume":"29 1","pages":"2276055"},"PeriodicalIF":2.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139543506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Augmented reality technology shortens aneurysm surgery learning curve for residents.","authors":"Xinman Liu, Weiping Xiao, Yibing Yang, Yan Yan, Feng Liang","doi":"10.1080/24699322.2024.2311940","DOIUrl":"10.1080/24699322.2024.2311940","url":null,"abstract":"<p><strong>Objectives: </strong>We aimed to prospectively investigate the benefit of using augmented reality (AR) for surgery residents learning aneurysm surgery.</p><p><strong>Materials and methods: </strong>Eight residents were included, and divided into an AR group and a control group (4 in each group). Both groups were asked to locate an aneurysm with a blue circle on the same screenshot after their viewing of surgery videos from both AR and non-AR tests. Only the AR group was allowed to inspect and manipulate an AR holographic representation of the aneurysm in AR tests. The actual location of the aneurysm was defined by a yellow circle by an attending physician after each test. Localization deviation was determined by the distance between the blue and yellow circle.</p><p><strong>Results: </strong>Localization deviation was lower in the AR group than in the control group in the last 2 tests (AR Test 2: 2.7 ± 1.0 mm vs. 5.8 ± 4.1 mm, <i>p</i> = 0.01, non-AR Test 2: 2.1 ± 0.8 mm vs. 5.9 ± 5.8 mm, <i>p</i> < 0.001). The mean deviation was lower in non-AR Test 2 as compared to non-AR Test 1 in both groups (AR: <i>p</i> < 0.001, control: <i>p</i> = 0.391). The localization deviation of the AR group decreased from 8.1 ± 3.8 mm in Test 2 to 2.7 ± 1.0 mm in AR Test 2 (<i>p</i> < 0.001).</p><p><strong>Conclusion: </strong>AR technology provides an effective and interactive way for neurosurgery training, and shortens the learning curve for residents in aneurysm surgery.</p>","PeriodicalId":56051,"journal":{"name":"Computer Assisted Surgery","volume":"29 1","pages":"2311940"},"PeriodicalIF":2.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139693639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A review on organ deformation modeling approaches for reliable surgical navigation using augmented reality.","authors":"Zheng Han, Qi Dou","doi":"10.1080/24699322.2024.2357164","DOIUrl":"https://doi.org/10.1080/24699322.2024.2357164","url":null,"abstract":"<p><p>Augmented Reality (AR) holds the potential to revolutionize surgical procedures by allowing surgeons to visualize critical structures within the patient's body. This is achieved through superimposing preoperative organ models onto the actual anatomy. Challenges arise from dynamic deformations of organs during surgery, making preoperative models inadequate for faithfully representing intraoperative anatomy. To enable reliable navigation in augmented surgery, modeling of intraoperative deformation to obtain an accurate alignment of the preoperative organ model with the intraoperative anatomy is indispensable. Despite the existence of various methods proposed to model intraoperative organ deformation, there are still few literature reviews that systematically categorize and summarize these approaches. This review aims to fill this gap by providing a comprehensive and technical-oriented overview of modeling methods for intraoperative organ deformation in augmented reality in surgery. Through a systematic search and screening process, 112 closely relevant papers were included in this review. By presenting the current status of organ deformation modeling methods and their clinical applications, this review seeks to enhance the understanding of organ deformation modeling in AR-guided surgery, and discuss the potential topics for future advancements.</p>","PeriodicalId":56051,"journal":{"name":"Computer Assisted Surgery","volume":"29 1","pages":"2357164"},"PeriodicalIF":1.5,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142301863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Flexible endoscope manipulating robot using quad-roller friction mechanism.","authors":"Subin Lee, Hyeonwook Kim, Jaehyeon Byeon, Seongbo Shim, Hyun-Joo Lee, Jaesung Hong","doi":"10.1080/24699322.2024.2404695","DOIUrl":"https://doi.org/10.1080/24699322.2024.2404695","url":null,"abstract":"<p><p>A robotic system for manipulating a flexible endoscope in surgery can provide enhanced accuracy and usability compared to manual operation. However, previous studies require large-scale, complex hardware systems to implement the rotational and translational motions of the soft endoscope cable. The conventional control of the endoscope by actuating the endoscope handle also leads to undesired slack between the endoscope tip and the handle, which becomes more problematic with long endoscopes such as a colonoscope. This study proposes a compact quad-roller friction mechanism that enables rotational and translational motions triggered not from the endoscope handle but at the endoscope tip. Controlling two pairs of tilted rollers achieves both types of motion within a small space. The proposed system also introduces an unsynchronized motion strategy between the handle and tip parts to minimize the robot's motion near the patient by employing the slack positively as a control index. Experiments indicate that the proposed system achieves accurate rotational and translational motions, and the unsynchronized control method reduces the total translational motion by up to 88% compared to the previous method.</p>","PeriodicalId":56051,"journal":{"name":"Computer Assisted Surgery","volume":"29 1","pages":"2404695"},"PeriodicalIF":1.5,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142301864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Monte Carlo-based rendering of 3D echocardiography for mixed reality-guided atrial septal puncture positioning.","authors":"Dharani Dhar Maddali, Håvard Solvin, Matthias Lippert, Yücel Karabiyik, Gry Dahle, Jon Mikkelsen Hjelmervik, Gabriel Kiss, Ole Jakob Elle, Henrik Brun","doi":"10.1080/24699322.2024.2403444","DOIUrl":"https://doi.org/10.1080/24699322.2024.2403444","url":null,"abstract":"<p><p>Catheter-based intervention procedures contain complex maneuvers, and they are often performed using fluoroscopic guidance assisted by 2D and 3D echocardiography viewed on a flat screen that inherently limits depth perception. Emerging mixed reality (MR) technologies, combined with advanced rendering techniques, offer potential enhancement in depth perception and navigational support. The study aims to evaluate a MR-based guidance system for the atrial septal puncture (ASP) procedure utilizing a phantom anatomical model. A novel MR-based guidance system using a modified Monte Carlo-based rendering approach for 3D echocardiographic visualization was introduced and evaluated against standard clinical 3D echocardiographic display on a flat screen. The objective was to guide the ASP procedure by facilitating catheter placement and puncture across four specific atrial septum quadrants. To assess the system's feasibility and performance, a user study involving four experienced interventional cardiologists was conducted using a phantom model. Results show that participants accurately punctured the designated quadrant in 14 out of 16 punctures using MR and 15 out of 16 punctures using the flat screen of the ultrasound machine. The geometric mean puncture time for MR was 31 s and 26 s for flat screen guidance. User experience ratings indicated MR-based guidance to be easier to navigate and locate tents of the atrial septum. The study demonstrates the feasibility of MR-guided atrial septal puncture. User experience data, particularly with respect to navigation, imply potential benefits for more complex procedures and educational purposes. The observed performance difference suggests an associated learning curve for optimal MR utilization.</p>","PeriodicalId":56051,"journal":{"name":"Computer Assisted Surgery","volume":"29 1","pages":"2403444"},"PeriodicalIF":1.5,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142301865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Early postoperative efficacy of a fully automated orthopedic robotic system-assisted percutaneous pedicle screw fixation for isthmic spondylolisthesis.","authors":"Li Zongze,Cheng Yongquan,Zeng Guanjie,Zhu Yongjian,Cui Yuhui,Jiang Hui,Chen Jianting","doi":"10.1080/24699322.2024.2399502","DOIUrl":"https://doi.org/10.1080/24699322.2024.2399502","url":null,"abstract":"To assess the feasibility of percutaneous pedicle screw fixation assisted by a fully automated orthopedic robotic system for the treatment of isthmic spondylolisthesis and evaluate its early postoperative outcome. Totally 20 patients with isthmic spondylolisthesis who underwent surgical procedure by the same medical group from March 2020 to March 2023 were retrospectively analyzed, including 10 patients in the robot-assisted group (RA group) and the other 10 patients in the conventional free-hand technique group (FH group). Accuracy of screw insertion was determined using the Gertzbein-Robbins Scale. The accuracy of the novel robotic system was evaluated by comparing the screw position in the preoperative planning and measuring the entry point deviation distance and the trajectory rotation. The differences in operative time, intraoperative blood loss, radiographic fluoroscopy time and fluoroscopic dosage, and length of hospital stay were compared between the two groups. The lumbar visual analog scale scores before and 7 days after operation were analyzed to evaluate the improvement of low back pain as the early postoperative outcome. A total of 84 pedicle screws were placed. In the RA group, 97.5% of screws were Grade A, and 2.5% were Grade B. In the FH group, 88.6% of screws were Grade A, 9.1% were Grade B, and 2.3% were Grade C. No statistical difference was found in the operation time between two groups. The RA group showed a significant reduction in intraoperative blood loss, radiographic fluoroscopy time and fluoroscopic dosage, and length of hospital stay compared to the FH group. The low back pain in both groups was significantly improved after the operation. The novel orthopedic robotic system-assisted percutaneous pedicle screw fixation, with accurate intraoperative screw placement, less surgical damage, less fluoroscopy and shorter length of hospital stay, can be safe and effective for the surgical treatment of isthmic spondylolisthesis.","PeriodicalId":56051,"journal":{"name":"Computer Assisted Surgery","volume":"27 1","pages":"2399502"},"PeriodicalIF":2.1,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142193996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Virtual surgical planning in craniomaxillofacial surgery: a structured review.","authors":"Kaye Velarde, Rentor Cafino, Armando Isla, Karen Mae Ty, Xavier-Lewis Palmer, Lucas Potter, Larry Nadorra, Luchin Valrian Pueblos, Lemuel Clark Velasco","doi":"10.1080/24699322.2023.2271160","DOIUrl":"10.1080/24699322.2023.2271160","url":null,"abstract":"<p><p>Craniomaxillofacial (CMF) surgery is a challenging and very demanding field that involves the treatment of congenital and acquired conditions of the face and head. Due to the complexity of the head and facial region, various tools and techniques were developed and utilized to aid surgical procedures and optimize results. Virtual Surgical Planning (VSP) has revolutionized the way craniomaxillofacial surgeries are planned and executed. It uses 3D imaging computer software to visualize and simulate a surgical procedure. Numerous studies were published on the usage of VSP in craniomaxillofacial surgery. However, the researchers found inconsistency in the previous literature which prompted the development of this review. This paper aims to provide a comprehensive review of the findings of the studies by conducting an integrated approach to synthesize the literature related to the use of VSP in craniomaxillofacial surgery. Twenty-nine related articles were selected as a sample and synthesized thoroughly. These papers were grouped assigning to the four subdisciplines of craniomaxillofacial surgery: orthognathic surgery, reconstructive surgery, trauma surgery and implant surgery. The following variables - treatment time, the accuracy of VSP, clinical outcome, cost, and cost-effectiveness - were also examined. Results revealed that VSP offers advantages in craniomaxillofacial surgery over the traditional method in terms of duration, predictability and clinical outcomes. However, the cost aspect was not discussed in most papers. This structured literature review will thus provide current findings and trends and recommendations for future research on the usage of VSP in craniomaxillofacial surgery.</p>","PeriodicalId":56051,"journal":{"name":"Computer Assisted Surgery","volume":"28 1","pages":"2271160"},"PeriodicalIF":2.1,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49685405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance assessment of surgical tracking systems based on statistical process control and longitudinal QA.","authors":"I Butz, M Fernandez, A Uneri, N Theodore, W S Anderson, J H Siewerdsen","doi":"10.1080/24699322.2023.2275522","DOIUrl":"10.1080/24699322.2023.2275522","url":null,"abstract":"<p><p>A system for performance assessment and quality assurance (QA) of surgical trackers is reported based on principles of geometric accuracy and statistical process control (SPC) for routine longitudinal testing. A simple QA test phantom was designed, where the number and distribution of registration fiducials was determined drawing from analytical models for target registration error (TRE). A tracker testbed was configured with open-source software for measurement of a TRE-based accuracy metric <math><mi>ε</mi></math> and Jitter (<math><mi>J</mi></math>). Six trackers were tested: 2 electromagnetic (EM - Aurora); and 4 infrared (IR - 1 Spectra, 1 Vega, and 2 Vicra) - all NDI (Waterloo, ON). Phase I SPC analysis of Shewhart mean (<math><mrow><mrow><mrow><mover><mrow><mi>x</mi></mrow><mo>¯</mo></mover></mrow></mrow></mrow></math>) and standard deviation (<math><mi>s</mi></math>) determined system control limits. Phase II involved weekly QA of each system for up to 32 weeks and identified Pass, Note, Alert, and Failure action rules. The process permitted QA in <1 min. Phase I control limits were established for all trackers: EM trackers exhibited higher upper control limits than IR trackers in <math><mi>ε</mi></math> (EM: <math><mrow><msub><mrow><mrow><mrow><mrow><mover><mrow><mi>x</mi></mrow><mo>¯</mo></mover></mrow></mrow></mrow></mrow><mrow><mi>ε</mi></mrow></msub></mrow><mi> </mi><mo>∼</mo></math>2.8-3.3 mm, IR: <math><mrow><msub><mrow><mrow><mrow><mrow><mover><mrow><mi>x</mi></mrow><mo>¯</mo></mover></mrow></mrow></mrow></mrow><mrow><mi>ε</mi></mrow></msub></mrow><mi> </mi><mo>∼</mo></math>1.6-2.0 mm) and Jitter (EM: <math><mrow><msub><mrow><mrow><mrow><mrow><mover><mrow><mi>x</mi></mrow><mo>¯</mo></mover></mrow></mrow></mrow></mrow><mrow><mi>jitter</mi></mrow></msub></mrow><mi> </mi><mo>∼</mo></math>0.30-0.33 mm, IR: <math><mrow><msub><mrow><mrow><mrow><mrow><mover><mrow><mi>x</mi></mrow><mo>¯</mo></mover></mrow></mrow></mrow></mrow><mrow><mi>jitter</mi></mrow></msub></mrow><mi> </mi><mo>∼</mo></math>0.08-0.10 mm), and older trackers showed evidence of degradation - e.g. higher Jitter for the older Vicra (<i>p</i>-value < .05). Phase II longitudinal tests yielded 676 outcomes in which a total of 4 Failures were noted - 3 resolved by intervention (metal interference for EM trackers) - and 1 owing to restrictive control limits for a new system (Vega). Weekly tests also yielded 40 Notes and 16 Alerts - each spontaneously resolved in subsequent monitoring.</p>","PeriodicalId":56051,"journal":{"name":"Computer Assisted Surgery","volume":"28 1","pages":"2275522"},"PeriodicalIF":2.1,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71523503","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on augmented reality navigation of in vitro fenestration of stent-graft based on deep learning and virtual-real registration.","authors":"Fengfeng He, Xiaoyu Qi, Qingmin Feng, Qiang Zhang, Ning Pan, Chao Yang, Shenglin Liu","doi":"10.1080/24699322.2023.2289339","DOIUrl":"10.1080/24699322.2023.2289339","url":null,"abstract":"<p><strong>Objectives: </strong><i>In vitro</i> fenestration of stent-graft (IVFS) demands high-precision navigation methods to achieve optimal surgical outcomes. This study aims to propose an augmented reality (AR) navigation method for IVFS, which can provide <i>in situ</i> overlay display to locate fenestration positions.</p><p><strong>Methods: </strong>We propose an AR navigation method to assist doctors in performing IVFS. A deep learning-based aorta segmentation algorithm is used to achieve automatic and rapid aorta segmentation. The Vuforia-based virtual-real registration and marker recognition algorithm are integrated to ensure accurate <i>in situ</i> AR image.</p><p><strong>Results: </strong>The proposed method can provide three-dimensional <i>in situ</i> AR image, and the fiducial registration error after virtual-real registration is 2.070 mm. The aorta segmentation experiment obtains dice similarity coefficient of 91.12% and Hausdorff distance of 2.59, better than conventional algorithms before improvement.</p><p><strong>Conclusions: </strong>The proposed method can intuitively and accurately locate fenestration positions, and therefore can assist doctors in performing IVFS.</p>","PeriodicalId":56051,"journal":{"name":"Computer Assisted Surgery","volume":"28 1","pages":"2289339"},"PeriodicalIF":2.1,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138500344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}