Residual network-based liver cancer multi-parameter nuclear magnetic resonance image classification method

The invention relates to a multi-parameter liver cancer nuclear magnetic image classification method based on a residual network. For nuclear magnetic data of an arterial phase, a delay phase and T2WI, in preprocessing, lesion parts of nuclear magnetic images of three parameters are segmented and fu...

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Main Authors YIN FANG, LIU YANGLING, HAO JINGANG, HE JIANFENG
Format Patent
LanguageChinese
English
Published 22.08.2023
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Abstract The invention relates to a multi-parameter liver cancer nuclear magnetic image classification method based on a residual network. For nuclear magnetic data of an arterial phase, a delay phase and T2WI, in preprocessing, lesion parts of nuclear magnetic images of three parameters are segmented and fused, and the image quality and the number can reach the training degree through image enhancement; and constructing a new camouflage classification residual network CCRNet for image classification. In the network, a multi-parameter feature extraction module MFE is provided, and the module is used for improving extraction of fused multi-parameter nuclear magnetic data complementary information; an improved asymmetric receptive field ARF is provided to enhance the distinguishability of the features, and the lesion feature information is further accurately identified; a multi-level feature fusion module MLFF is provided to combine feature information from each level to form a more discriminative fusion feature. Accord
AbstractList The invention relates to a multi-parameter liver cancer nuclear magnetic image classification method based on a residual network. For nuclear magnetic data of an arterial phase, a delay phase and T2WI, in preprocessing, lesion parts of nuclear magnetic images of three parameters are segmented and fused, and the image quality and the number can reach the training degree through image enhancement; and constructing a new camouflage classification residual network CCRNet for image classification. In the network, a multi-parameter feature extraction module MFE is provided, and the module is used for improving extraction of fused multi-parameter nuclear magnetic data complementary information; an improved asymmetric receptive field ARF is provided to enhance the distinguishability of the features, and the lesion feature information is further accurately identified; a multi-level feature fusion module MLFF is provided to combine feature information from each level to form a more discriminative fusion feature. Accord
Author HE JIANFENG
LIU YANGLING
YIN FANG
HAO JINGANG
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DocumentTitleAlternate 一种基于残差网络的肝癌多参数核磁共振图像分类方法
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Snippet The invention relates to a multi-parameter liver cancer nuclear magnetic image classification method based on a residual network. For nuclear magnetic data of...
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Title Residual network-based liver cancer multi-parameter nuclear magnetic resonance image classification method
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