Jing Niu
Taiyuan University of Technology
4 Papers
Jing Niu is an academic researcher from Taiyuan University of Technology. The author has contributed to research in topics: Computer science & Deep learning. The author has an hindex of 2, co-authored 4 publications.
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Papers
New convolutional neural network model for screening and diagnosis of mammograms
TL;DR: A multi-view feature fusion network model for classification of mammograms from two views is constructed and a multi-scale attention DenseNet is proposed as the backbone network for feature extraction through convolutional neural network.
Classification of breast mass in two-view mammograms via deep learning
TL;DR: This study proposes a two-view mammograms classification model consist-ing of convolutional neural network (CNN) and recurrent Neural network (RNN), which is used to classify benign and malignant breast masses.
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Multi-scale attention-based convolutional neural network for classification of breast masses in mammograms.
TL;DR: Wang et al. as discussed by the authors used CNN to classify benign and malignant breast masses in the mammograms, and achieved the accuracy, sensitivity, AUC and corresponding standard deviation of their method are 0.9554 ± 0.068 and 0.9468 ± 0.,0085, respectively.
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Combining multi-scale feature fusion with multi-attribute grading, a CNN model for benign and malignant classification of pulmonary nodules
TL;DR: This study constructed a multi-stream multi-task network (MSMT), which combined multi-scale feature with multi-attribute classification for the first time, and applied it to the classification of benign and malignant pulmonary nodules in CT images.