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公开(公告)号：US10803354B2
公开(公告)日：2020-10-13
申请号：US16258751
申请日：2019-01-28
发明人： Yu Zhao , Yimo Gao , Shu Liao , Liang Zhao , Zhennan Yan , Yiqiang Zhan , Xiang Sean Zhou
摘要： A framework for cross-modality image synthesis. A first and second model may be trained using respective first and second pairs of complementary images and corresponding first and second ground truth images that represent first and second views of a region of interest. The first and second pairs of complementary images may be acquired by a first modality and the first and second ground truth images may be acquired by a second modality. A combinational network may further be trained to combine features from the first and second models. At least one synthetic second modality image may then be generated by passing current images through the trained first or second model and the combinational network, wherein the current images are acquired by the first modality and represent the first or second view of the region of interest.
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公开(公告)号：US20190311228A1
公开(公告)日：2019-10-10
申请号：US16258751
申请日：2019-01-28
发明人： Yu Zhao , Yimo Gao , Shu Liao , Liang Zhao , Zhennan Yan , Yiqiang Zhan , Xiang Sean Zhou
摘要： A framework for cross-modality image synthesis. A first and second model may be trained using respective first and second pairs of complementary images and corresponding first and second ground truth images that represent first and second views of a region of interest. The first and second pairs of complementary images may be acquired by a first modality and the first and second ground truth images may be acquired by a second modality. A combinational network may further be trained to combine features from the first and second models. At least one synthetic second modality image may then be generated by passing current images through the trained first or second model and the combinational network, wherein the current images are acquired by the first modality and represent the first or second view of the region of interest.
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