Esophagus Tumor Segmentation Using Fully Convolutional Neural Network and Graph Cut

2017 ◽  
pp. 413-420 ◽  
Author(s):  
Zhaojun Hao ◽  
Jiwei Liu ◽  
Jianfei Liu
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Graph Cut ◽  
Tumor Segmentation

scholarly journals Brain Tumor Segmentation using K-Means Clustering and Detection using Convolutional Neural Network

2020 ◽  
Vol 9 (5) ◽  
pp. 1452-1455
Keyword(s):  
Neural Network ◽  
Image Processing ◽  
Brain Tumor ◽  
Convolutional Neural Network ◽  
Clustering Algorithm ◽  
Tumor Segmentation ◽  
Brain Tumor Segmentation ◽  
Mri Scans ◽  
Two Phases ◽  
Processing Techniques

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.

Whole Tumor Segmentation from Brain MR images using Multi-view 2D Convolutional Neural Network

2021 ◽  
Author(s):  
Ritu Lahoti ◽  
Sunil Kumar Vengalil ◽  
Punith B Venkategowda ◽  
Neelam Sinha ◽  
Vinod Veera Reddy
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Tumor Segmentation ◽  
Mr Images ◽  
Brain Mr Images
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