Medical image segmentation by convolutional neural network

The goal of this study will be to analyze outstanding deep learning network structures in the medical image processing field, thereby coming up with proposing a better network model that can improve performance productivity and quality of medical image segmentation challenges. In this study, the Une...

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Tác giả chính:	Trần Song Toàn
Tác giả khác:	Prof. Don-Gey Liu (người hướng dẫn khoa học); Prof. Ching-Hwa Cheng (người hướng dẫn khoa học)
Ngôn ngữ:	eng
Được phát hành:	逢甲大學 2022
Truy cập trực tuyến:	https://opac.tvu.edu.vn/pages/opac/wpid-detailbib-id-39393.html
Các nhãn:	Thêm thẻ Không có thẻ, Là người đầu tiên thẻ bản ghi này!

Thư viện lưu trữ:	Trung tâm Học liệu – Phát triển Dạy và Học, Trường Đại học Trà Vinh

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spelling	https:--opac.tvu.edu.vn:9090-api-oai:393932022-03-07T06:22:30Z Medical image segmentation by convolutional neural network Trần Song Toàn The goal of this study will be to analyze outstanding deep learning network structures in the medical image processing field, thereby coming up with proposing a better network model that can improve performance productivity and quality of medical image segmentation challenges. In this study, the Unet model is used as the backbone architecture. The analysis will focus on the disadvantages of Unet and Unet-based models, thereby proposing methods to overcome the weaknesses and improve the efficiency of the proposed model. 逢甲大學 Prof. Don-Gey Liu (người hướng dẫn khoa học); Prof. Ching-Hwa Cheng (người hướng dẫn khoa học) 2022-03-07T06:22:30Z pdf https://opac.tvu.edu.vn/pages/opac/wpid-detailbib-id-39393.html eng
institution	Trung tâm Học liệu – Phát triển Dạy và Học, Trường Đại học Trà Vinh
collection	Thư viện số
language	eng
description	The goal of this study will be to analyze outstanding deep learning network structures in the medical image processing field, thereby coming up with proposing a better network model that can improve performance productivity and quality of medical image segmentation challenges. In this study, the Unet model is used as the backbone architecture. The analysis will focus on the disadvantages of Unet and Unet-based models, thereby proposing methods to overcome the weaknesses and improve the efficiency of the proposed model.
author2	Prof. Don-Gey Liu (người hướng dẫn khoa học); Prof. Ching-Hwa Cheng (người hướng dẫn khoa học)
author_facet	Prof. Don-Gey Liu (người hướng dẫn khoa học); Prof. Ching-Hwa Cheng (người hướng dẫn khoa học) Trần Song Toàn
author	Trần Song Toàn
spellingShingle	Trần Song Toàn Medical image segmentation by convolutional neural network
author_sort	Trần Song Toàn
title	Medical image segmentation by convolutional neural network
title_short	Medical image segmentation by convolutional neural network
title_full	Medical image segmentation by convolutional neural network
title_fullStr	Medical image segmentation by convolutional neural network
title_full_unstemmed	Medical image segmentation by convolutional neural network
title_sort	medical image segmentation by convolutional neural network
publisher	逢甲大學
publishDate	2022
url	https://opac.tvu.edu.vn/pages/opac/wpid-detailbib-id-39393.html
_version_	1812601600266469376

Medical image segmentation by convolutional neural network

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