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VGU RESEARCH REPOSITORY


Please use this identifier to cite or link to this item: https://epub.vgu.edu.vn/handle/dlibvgu/997
Title: Brain tumour segmentation using dense convolutional neural network
Authors: Doan Thai Thien Loc 
Keywords: Artificial intelligence;Machine learning;Deep learning
Issue Date: 2020
Publisher: Vietnamese-German University
Abstract: 
Brain tumour is a very hard to treat disease. It is dangerous and requires a lot of expertise to medicate. Brain experts need the tumour segmentation to keep track of the effectiveness of the treatment. Manual segmentation labeling can be time-consuming and error-prone due to human inaccuracy. Automated segmentation of brain tumour using 3D magnetic resonance images (MRI) is favored for diagnosis, treatment controlling and method planning. Lately, deep learning have been exceeding human accuracy in highly conceptual task like brain tumour segmentation. In this paper, I will introduce some deep learning networks using DenseNet, a recent success deep learning method for the task brain tumour segmentatio
URI(1): http://epub.vgu.edu.vn/handle/dlibvgu/997
Rights: Attribution-NonCommercial 4.0 International
Appears in Collections:Computer Science (CS)

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