Titlebook: Machine Learning in Medical Imaging; 11th International W Mingxia Liu,Pingkun Yan,Xiaohuan Cao Conference proceedings 2020 Springer Nature

CANTO

书目名称Machine Learning in Medical Imaging影响因子(影响力)




书目名称Machine Learning in Medical Imaging影响因子(影响力)学科排名




书目名称Machine Learning in Medical Imaging网络公开度




书目名称Machine Learning in Medical Imaging网络公开度学科排名




书目名称Machine Learning in Medical Imaging被引频次




书目名称Machine Learning in Medical Imaging被引频次学科排名




书目名称Machine Learning in Medical Imaging年度引用




书目名称Machine Learning in Medical Imaging年度引用学科排名




书目名称Machine Learning in Medical Imaging读者反馈




书目名称Machine Learning in Medical Imaging读者反馈学科排名

使隔离

蜿蜒而流

A Novel fMRI Representation Learning Framework with GAN,the mapping between mind and brain. The proposed framework is evaluated on Human Connectome Project (HCP) task functional MRI (tfMRI) data. This novel framework proves that GAN can learn meaningful representations of tfMRI and promises better understanding of the brain function.

断言

3D Segmentation Networks for Excessive Numbers of Classes: Distinct Bone Segmentation in Upper Bodimodifications in network architecture, loss function, and data augmentation. As a result, we demonstrate the robustness of our method by automatically segmenting over one hundred distinct bones simultaneously in an end-to-end learnt fashion from a CT-scan.

Arteriography

Decibel

Segmentation to Label: Automatic Coronary Artery Labeling from Mask Parcellation,orrespondingly. Finally, a self-contained loss is proposed to supervise labeling process. At experiment section, we conduct comprehensive experiments on collected 526 CCTA scans and exhibit stable and promising results.

Ganglion-Cyst

Organization

准则

纯朴

Error Attention Interactive Segmentation of Medical Image Through Matting and Fusion,e automatic segmentation to get higher accuracy for clinical use. Current methods usually transform user clicks to geodesic distance hint maps as guidance, then concatenate them with the raw image and coarse segmentation, and feed them into a refinement network. Such methods are insufficient in refi