Please use this identifier to cite or link to this item: https://dspace.ctu.edu.vn/jspui/handle/123456789/45368
Title: Automatic Liver Damage Segmentation on 3D Images Using VGG16 and ResNet-50 Neural Networks
Authors: Phan, Thượng Cang
Phan, Anh Cang
Trần, Thị Vàng Y
Keywords: CÔNG NGHỆ THÔNG TIN
Issue Date: 2021
Publisher: Trường Đại Học Cần Thơ
Abstract: Liver cancer is the second most dangerous cancer in the world. Medical experts still manually do most liver segmentations of Computed Tomography scans. Automatic segmentation of the liver and lesions is an important step towards computer-aided decision support systems. This thesis can be the basic foundation for developing related research at Can Tho University in the future. The topic has made positive scientific contributions to apply information technology into medicine. At the same time, it brings a big meaning to the society in general and the public health sector in particular. In this thesis, we have successfully deployed an algorithm for segmenting the liver and its lesions using two cascaded segmentation networks and one detector with VGG-16 and ResNet-50 Neural Networks. The liver images result illustrates the liver damage per each liver slice.
Description: 56 Tr
URI: https://dspace.ctu.edu.vn/jspui/handle/123456789/45368
Appears in Collections:Trường Công nghệ Thông tin & Truyền thông

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