Abstract: Medical image segmentation is critical for disease diagnosis and treatment assessment. However, concerns regarding the reliability of segmentation regions persist among clinicians, mainly ...
Siqi Zhang*, Qizhe Zhang*, Shanghang Zhang*†, Xiaohong Liu*, Jingkun Yue*, Ming Lu, Huihuan Xu, Jiaxin Yao, Xiaobao Wei, Jiajun Cao, Xiang Zhang, Ming Gao, Jun Shen ...
Abstract: The success of deep learning in 3D medical image segmentation hinges on training with a large dataset of fully annotated 3D volumes, which are difficult and time-consuming to acquire.
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1 International College, Chongqing University of Posts and Telecommunications, Chongqing, China 2 Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States To ...
The color image of the fire hole is key for the working condition identification of the aluminum electrolysis cell (AEC). However, the image of the fire hole is difficult for image segmentation due to ...
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