Titlebook: Medical Image Computing and Computer Assisted Intervention – MICCAI 2018; 21st International C Alejandro F. Frangi,Julia A. Schnabel,Gabor

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書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2018影響因子(影響力)




書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2018影響因子(影響力)學(xué)科排名




書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2018網(wǎng)絡(luò)公開度




書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2018網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2018被引頻次




書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2018被引頻次學(xué)科排名




書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2018年度引用




書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2018年度引用學(xué)科排名




書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2018讀者反饋




書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2018讀者反饋學(xué)科排名

manifestation

ascetic

Conditional Generative Adversarial Networks for Metal Artifact Reduction in CT Images of the Ear segmentations of intra-cochlear anatomical structures, which are obtained with a previously published method, in the real pre-implantation and the artifact-corrected CTs. We show that the proposed method leads to an average surface error of 0.18?mm which is about half of what could be achieved with

議程

Deep Convolutional Filtering for Spatio-Temporal Denoising and Artifact Removal in Arterial Spin Labn of perfusion, even in challenging datasets, this technique offers an exciting new approach for ASL pipelines, and might be used both for improving individual images and to increase the power of research studies using ASL.

殘酷的地方

DeepASL: Kinetic Model Incorporated Loss for Denoising Arterial Spin Labeled MRI via Deep Residual L mapping from noisy perfusion-weighted image and its subtraction (residual) from the clean image. Additionally, we incorporate the CBF estimation model in the loss function during training, which enables the network to produce high quality images while simultaneously enforcing the CBF estimates to b

Indict

Direct Estimation of Pharmacokinetic Parameters from DCE-MRI Using Deep CNN with Forward Physical Mon of PK parameters. Experiments on clinical brain DCE datasets demonstrate the efficacy of our approach in terms of fidelity of PK parameter reconstruction and significantly faster parameter inference compared to a model-based iterative reconstruction method.

不在灌木叢中

thalamus

organic-matrix

Blanch

Evaluation of Adjoint Methods in Photoacoustic Tomography with Under-Sampled Sensors BP have better performance on contrast and resolution, respectively. We also show that the integrand of TR includes additional side lobes which degrade axial resolution whereas that of BP conversely has relatively small amplitudes. Moreover, omnidirectional resolution is improved if more sensors ar