Automatic tumor segmentation in 3D automated breast ultrasound using convolutional neural network

Author(s):  
Yang Lei ◽  
Xiuxiu He ◽  
Tonghe Wang ◽  
Jincao Yao ◽  
Lijing Wang ◽  
...  
2020 ◽  
Vol 190 ◽  
pp. 105360 ◽  
Author(s):  
Woo Kyung Moon ◽  
Yao-Sian Huang ◽  
Chin-Hua Hsu ◽  
Ting-Yin Chang Chien ◽  
Jung Min Chang ◽  
...  

2021 ◽  
pp. 109608
Author(s):  
Ruey-Feng Chang ◽  
Huiling Xiang ◽  
Yao-Sian Huang ◽  
Chu-Hsuan Lee ◽  
Ting-Yin Chang Chien ◽  
...  

This paper presents brain tumor detection and segmentation using image processing techniques. Convolutional neural networks can be applied for medical research in brain tumor analysis. The tumor in the MRI scans is segmented using the K-means clustering algorithm which is applied of every scan and the feed it to the convolutional neural network for training and testing. In our CNN we propose to use ReLU and Sigmoid activation functions to determine our end result. The training is done only using the CPU power and no GPU is used. The research is done in two phases, image processing and applying neural network.


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