3 papers
cs.CV2019
Unsupervised Visual Representation Learning with Increasing Object Shape Bias
Zhibo Wang, Shen Yan, Xiaoyu Zhang +1
(Very early draft)Traditional supervised learning keeps pushing convolution neural network(CNN) achieving state-of-art performance. However, lack of large-scale annotation data is…
eess.IV2019
Scribble-based Hierarchical Weakly Supervised Learning for Brain Tumor Segmentation
Zhanghexuan Ji, Yan Shen, Chunwei Ma +1
The recent state-of-the-art deep learning methods have significantly improved brain tumor segmentation. However, fully supervised training requires a large amount of manually label…
cs.CV2019
Brain Tumor Segmentation on MRI with Missing Modalities
Yan Shen, Mingchen Gao
Brain Tumor Segmentation from magnetic resonance imaging (MRI) is a critical technique for early diagnosis. However, rather than having complete four modalities as in BraTS dataset…