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Real-Time Needle Force Modeling for VR-Based Renal Biopsy Training with Respiratory Motion Using Direct Clinical Data
المؤلفون المشاركون
Li, Feiyan
Tai, Yonghang
Li, Qiong
Peng, Jun
Huang, Xiaoqiao
Chen, Zaiqing
Shi, Junsheng
المصدر
Applied Bionics and Biomechanics
العدد
المجلد 2019، العدد 2019 (31 ديسمبر/كانون الأول 2019)، ص ص. 1-14، 14ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2019-06-25
دولة النشر
مصر
عدد الصفحات
14
التخصصات الرئيسية
الملخص EN
Realistic tool-tissue interactive modeling has been recognized as an essential requirement in the training of virtual surgery.
A virtual basic surgical training framework integrated with real-time force rendering has been recognized as one of the most immersive implementations in medical education.
Yet, compared to the original intraoperative data, there has always been an argument that these data are represented by lower fidelity in virtual surgical training.
In this paper, a dynamic biomechanics experimental framework is designed to achieve a highly immersive haptic sensation during the biopsy therapy with human respiratory motion; it is the first time to introduce the idea of periodic extension idea into the dynamic percutaneous force modeling.
Clinical evaluation is conducted and performed in the Yunnan First People’s Hospital, which not only demonstrated a higher fitting degree (AVG: 99.36%) with the intraoperation data than previous algorithms (AVG: 87.83%, 72.07%, and 66.70%) but also shows a universal fitting range with multilayer tissue.
27 urologists comprising 18 novices and 9 professors were invited to the VR-based training evaluation based on the proposed haptic rendering solution.
Subjective and objective results demonstrated higher performance than the existing benchmark training simulator.
Combining these in a systematic approach, tuned with specific fidelity requirements, haptically enabled medical simulation systems would be able to provide a more immersive and effective training environment.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Li, Feiyan& Tai, Yonghang& Li, Qiong& Peng, Jun& Huang, Xiaoqiao& Chen, Zaiqing…[et al.]. 2019. Real-Time Needle Force Modeling for VR-Based Renal Biopsy Training with Respiratory Motion Using Direct Clinical Data. Applied Bionics and Biomechanics،Vol. 2019, no. 2019, pp.1-14.
https://search.emarefa.net/detail/BIM-1114739
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Li, Feiyan…[et al.]. Real-Time Needle Force Modeling for VR-Based Renal Biopsy Training with Respiratory Motion Using Direct Clinical Data. Applied Bionics and Biomechanics No. 2019 (2019), pp.1-14.
https://search.emarefa.net/detail/BIM-1114739
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Li, Feiyan& Tai, Yonghang& Li, Qiong& Peng, Jun& Huang, Xiaoqiao& Chen, Zaiqing…[et al.]. Real-Time Needle Force Modeling for VR-Based Renal Biopsy Training with Respiratory Motion Using Direct Clinical Data. Applied Bionics and Biomechanics. 2019. Vol. 2019, no. 2019, pp.1-14.
https://search.emarefa.net/detail/BIM-1114739
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1114739
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر
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