3 papers
cs.CV2023
AttenScribble: Attentive Similarity Learning for Scribble-Supervised Medical Image Segmentation
Mu Tian, Qinzhu Yang, Yi Gao
The success of deep networks in medical image segmentation relies heavily on massive labeled training data. However, acquiring dense annotations is a time-consuming process. Weakly…
cs.CV2023
A dynamic interactive learning framework for automated 3D medical image segmentation
Mu Tian, Xiaohui Chen, Yi Gao
Many deep learning based automated medical image segmentation systems, in reality, face difficulties in deployment due to the cost of massive data annotation and high latency in mo…
cs.CV2020
MCMC Guided CNN Training and Segmentation for Pancreas Extraction
Jinchan He, Xiaxia Yu, Chudong Cai +1
Efficient organ segmentation is the precondition of various quantitative analysis. Segmenting the pancreas from abdominal CT images is a challenging task because of its high anatom…