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Titlebook: Computer-Assisted and Robotic Endoscopy; First International Xiongbiao Luo,Tobias Reichl,Timothy Soper Conference proceedings 2014 Springe

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書(shū)目名稱Computer-Assisted and Robotic Endoscopy
副標(biāo)題First International
編輯Xiongbiao Luo,Tobias Reichl,Timothy Soper
視頻videohttp://file.papertrans.cn/235/234470/234470.mp4
概述Up-to-date results.Fast track conference proceedings.State-of-the-art report.Includes supplementary material:
叢書(shū)名稱Lecture Notes in Computer Science
圖書(shū)封面Titlebook: Computer-Assisted and Robotic Endoscopy; First International  Xiongbiao Luo,Tobias Reichl,Timothy Soper Conference proceedings 2014 Springe
描述This book constitutes the refereed proceedings of the First International Workshop on Computer Assisted and Robotic Endoscopy, CARE 2014, held in conjunction with MICCAI 2014, in Boston, MA, USA, in September 2014. The 12 papers presented focus on recent technical advances associated with computer vision; graphics; robotics and medical imaging; external tracking systems; medical device control systems; information processing techniques; endoscopy; planning and simulation.
出版日期Conference proceedings 2014
關(guān)鍵詞computer vision; endoscopic video computing; endoscopy planning and simulation; endoscopy skill train a
版次1
doihttps://doi.org/10.1007/978-3-319-13410-9
isbn_softcover978-3-319-13409-3
isbn_ebook978-3-319-13410-9Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer International Publishing Switzerland 2014
The information of publication is updating

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Algorithms for Automated Pointing of Cardiac Imaging Catheters,of visualization capabilities, such as recording a sequence of ultrasound images and reconstructing them into 3D or 4D volumes for diagnosis and treatment. The algorithms were validated with a robotic test bed and the resulting images were reconstructed into 3D volumes. This capability may improve t
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,The FAP Model — The Strategic Index (SI), wall in this paper. Combined with the superposition model, we are able to depict the outer wall of colon in a natural way. We validated the proposed algorithm based on 60 CTC datasets. Compared with the GAC model, the new presented method is more reliable for the colon wall segmentation. Additional
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The Reordering Problem and Its Solutions,nformative’, which led to re-initialization of the algorithm, this was predictive for the result of dark region segmentation accuracy..In conclusion, the developed target detection algorithm provided accurate results and is thought to provide reliable assistance in the clinic. The clinical relevance
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