Titlebook: Medical Image Computing and Computer Assisted Intervention – MICCAI 2019; 22nd International C Dinggang Shen,Tianming Liu,Ali Khan Conferen

figment

Lipoprotein

Lecture Notes in Computer Sciencehttp://image.papertrans.cn/m/image/629191.jpg

annexation

gastritis

单独

爱国者

ESO

Abdominal Adipose Tissue Segmentation in MRI with Double Loss Function Collaborative Learning9000 clinical quantitative MR images with numerical labels of the number of pixels in subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and Non-adipose tissues. Our approach achieves 94.3% and 90.8% segmentation accuracy for SAT and VAT respectively in the dataset with image labels,

弯弯曲曲

滋养

Generating Pareto Optimal Dose Distributions for Radiation Therapy Treatment Planning10 test patients and 60 training/validation patients. We then trained a hierarchically densely connected convolutional U-net (HD U-net), to take the PTV and avoidance map representing OARs masks and weights, and predict the optimized plan. The HD U-net is capable of accurately predicting the 3D Pare

Ganglion-Cyst

LSRC: A Long-Short Range Context-Fusing Framework for Automatic 3D Vertebra Localizationgrates the long-range contextual information of these two views. Two refined heat maps in the sagittal and coronal planes are generated by a globally-refining module, adjusting vertebra locations using the global location information in an attention manner. Experiments on a public dataset of 302 3D