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

CANTO

書(shū)目名稱(chēng)Machine Learning in Medical Imaging影響因子(影響力)




書(shū)目名稱(chēng)Machine Learning in Medical Imaging影響因子(影響力)學(xué)科排名




書(shū)目名稱(chēng)Machine Learning in Medical Imaging網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱(chēng)Machine Learning in Medical Imaging網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱(chēng)Machine Learning in Medical Imaging被引頻次




書(shū)目名稱(chēng)Machine Learning in Medical Imaging被引頻次學(xué)科排名




書(shū)目名稱(chēng)Machine Learning in Medical Imaging年度引用




書(shū)目名稱(chēng)Machine Learning in Medical Imaging年度引用學(xué)科排名




書(shū)目名稱(chēng)Machine Learning in Medical Imaging讀者反饋




書(shū)目名稱(chēng)Machine Learning in Medical Imaging讀者反饋學(xué)科排名

使隔離

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.

斷言

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

準(zhǔn)則

純樸

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