An Autocontouring Method for the Kidneys Using an Adaptive Weighted Multikernel Support Vector Machines

In radiotherapy, the location of the target area is very important. If the target area is small, the treatment is not complete, so the location of the target area is generally larger than the actual cancerous site. However, the damage of radiotherapy to normal cells is the same. In order to reduce t...

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Main Authors: Yi Gu, Bo Li
Format: Article
Language:English
Published: Hindawi Limited 2021-01-01
Series:Scientific Programming
Online Access:http://dx.doi.org/10.1155/2021/1885512
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spelling doaj-1d7fa03cdc38488d99b9a52bbb393ab72021-07-26T00:33:56ZengHindawi LimitedScientific Programming1875-919X2021-01-01202110.1155/2021/1885512An Autocontouring Method for the Kidneys Using an Adaptive Weighted Multikernel Support Vector MachinesYi Gu0Bo Li1School of Artificial Intelligence and Computer ScienceSchool of Artificial Intelligence and Computer ScienceIn radiotherapy, the location of the target area is very important. If the target area is small, the treatment is not complete, so the location of the target area is generally larger than the actual cancerous site. However, the damage of radiotherapy to normal cells is the same. In order to reduce the damage to the body as much as possible, we need to complete the most suitable target area. This paper uses an adaptive weighted multikernel support vector machine, which solves the parameter problem in the traditional multikernel support vector machine. The new AW-SVM can adjust the kernel weights adaptively. We completed our experiment on the abdominal MR dataset, using DSI as an evaluation indicator, and the experimental results showed its excellent classification performance. The minimum value of DSI in all results is 0.9654 (more than 0.7 is acceptable).http://dx.doi.org/10.1155/2021/1885512
collection DOAJ
language English
format Article
sources DOAJ
author Yi Gu
Bo Li
spellingShingle Yi Gu
Bo Li
An Autocontouring Method for the Kidneys Using an Adaptive Weighted Multikernel Support Vector Machines
Scientific Programming
author_facet Yi Gu
Bo Li
author_sort Yi Gu
title An Autocontouring Method for the Kidneys Using an Adaptive Weighted Multikernel Support Vector Machines
title_short An Autocontouring Method for the Kidneys Using an Adaptive Weighted Multikernel Support Vector Machines
title_full An Autocontouring Method for the Kidneys Using an Adaptive Weighted Multikernel Support Vector Machines
title_fullStr An Autocontouring Method for the Kidneys Using an Adaptive Weighted Multikernel Support Vector Machines
title_full_unstemmed An Autocontouring Method for the Kidneys Using an Adaptive Weighted Multikernel Support Vector Machines
title_sort autocontouring method for the kidneys using an adaptive weighted multikernel support vector machines
publisher Hindawi Limited
series Scientific Programming
issn 1875-919X
publishDate 2021-01-01
description In radiotherapy, the location of the target area is very important. If the target area is small, the treatment is not complete, so the location of the target area is generally larger than the actual cancerous site. However, the damage of radiotherapy to normal cells is the same. In order to reduce the damage to the body as much as possible, we need to complete the most suitable target area. This paper uses an adaptive weighted multikernel support vector machine, which solves the parameter problem in the traditional multikernel support vector machine. The new AW-SVM can adjust the kernel weights adaptively. We completed our experiment on the abdominal MR dataset, using DSI as an evaluation indicator, and the experimental results showed its excellent classification performance. The minimum value of DSI in all results is 0.9654 (more than 0.7 is acceptable).
url http://dx.doi.org/10.1155/2021/1885512
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