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

Coeval

短程旅游

chisel

厚臉皮

Multi-class Gradient Harmonized Dice Loss with Application to Knee MR Image Segmentation knee scans collected from local hospitals. The experimental results show that the Gradient Harmonized Dice Loss outperforms the popular loss functions, such as Dice loss and Focal loss, and achieves the state-of-the-art results on the validation data of ..

chapel

身體萌芽

0302-9743 nce on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019, held in Shenzhen, China, in October 2019...The 539 revised full papers presented were carefully reviewed and selected from 1730 submissions in a double-blind review process. The papers are organized in the following topi

假裝是我

PAN: Projective Adversarial Network for Medical Image Segmentationur adversarial network. For the clinical application we chose pancreas segmentation from CT scans. Our proposed framework achieved state-of-the-art performance without adding to the complexity of the segmentor.

暫時休息

Multi-scale GANs for Memory-efficient Generation of High Resolution Medical Imagesd of our method, arbitrarily large images of high resolution can be generated. Moreover, compared to common patch-based approaches, our multi-resolution scheme enables better image quality and prevents patch artifacts.

審問

Pairwise Semantic Segmentation via Conjugate Fully Convolutional Network and shape changes in a small number of training samples, a fusion module is designed to provide proxy supervision for the network training process. Quantitative evaluation shows that the proposed method has a significant performance improvement on pathological liver segmentation.

Agility