Titlebook: Augmented Reality Environments for Medical Imaging and Computer-Assisted Interventions; International Worksh Hongen Liao,Cristian A. Linte,

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書目名稱Augmented Reality Environments for Medical Imaging and Computer-Assisted Interventions影響因子(影響力)




書目名稱Augmented Reality Environments for Medical Imaging and Computer-Assisted Interventions影響因子(影響力)學(xué)科排名




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書目名稱Augmented Reality Environments for Medical Imaging and Computer-Assisted Interventions網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Augmented Reality Environments for Medical Imaging and Computer-Assisted Interventions被引頻次




書目名稱Augmented Reality Environments for Medical Imaging and Computer-Assisted Interventions被引頻次學(xué)科排名




書目名稱Augmented Reality Environments for Medical Imaging and Computer-Assisted Interventions年度引用




書目名稱Augmented Reality Environments for Medical Imaging and Computer-Assisted Interventions年度引用學(xué)科排名




書目名稱Augmented Reality Environments for Medical Imaging and Computer-Assisted Interventions讀者反饋




書目名稱Augmented Reality Environments for Medical Imaging and Computer-Assisted Interventions讀者反饋學(xué)科排名

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Real-Time Marker-Free Patient Registration and Image-Based Navigation Using Stereovision for Dental mounted to the surgical tool for instrument tracking, which can be seen by the camera at all times during the operation. The patient registration is achieved by patient tracking and 3D contour matching with the preoperative patient model, requiring no fiducial marker and reference marker. In additi

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Intensity-Based 3D-2D Mesh-to-Image Registration Using Mesh-Based Digitally Reconstructed Radiograpvel ray-casting strategy that takes GPU architecture into consideration for high computational efficiency. Validation results show that the proposed mesh-based DRR simulates X-ray images with a high fidelity, and intensity-based 3D-2D registration using the resulting mesh-based DRR achieves satisfac

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Toward Accurate and Robust 2-D/3-D Registration of Implant Models to Single-Plane Fluoroscopy,nsity-based similarity measure between the fluoroscopic image and the simulated X-ray image. In the iterative registration, we use a novel two-layer hierarchical optimization strategy to achieve a high accuracy in depth estimation, to which the projection image is very insensitive. The proposed appr

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物種起源

Brain-Cloud: A Generalized and Flexible Registration Framework for Brain MR Images,espective . images (similar images in terms of intensity appearance) in the cloud, we predict the initial deformation between the fixed and moving images by the deformation pathway between the two .images. Thus, the remaining small deformation can be efficiently refined via most existing deformable

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