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1.发明授权公开(公告)号：US11928782B2
公开(公告)日：2024-03-12
申请号：US17613487
申请日：2020-10-30
发明人： Chan Zeng , Ge Li , Guanju Cheng , Peng Gao , Guotong Xie
CPC分类号： G06T19/00 , G06T5/70 , G06T7/0012 , G06T7/73 , G06T2200/04 , G06T2207/10081 , G06T2207/20084 , G06T2207/30012 , G06T2219/004
摘要： The present disclosure provides a method of positioning vertebra in a CT image, an apparatus, a computer device, and a computer readable storage medium. The method includes: pre-processing vertebra CT image data; inputting the pre-processed vertebra CT image data into a pre-trained neural network to obtain regression results of heat maps of key points corresponding to the pre-processed vertebra CT image data; regressing of 3D heat maps corresponding to the positions of the key points of the vertebra mass center based on the regression results of the heat maps of the key points and the pre-processed vertebra CT image data; serving 3D heat maps corresponding to the positions of the key points of the vertebra mass center as labels, and networked regressing 3D heat map information to position the vertebra. Effects caused by scanning machine difference and scanning noise are avoided, and the vertebra with complex forms is accurately positioned.
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2.发明公开公开(公告)号：US20230186566A1
公开(公告)日：2023-06-15
申请号：US17613487
申请日：2020-10-30
发明人： Chan Zeng , Ge Li , Guanju Cheng , Peng Gao , Guotong Xie
CPC分类号： G06T19/00 , G06T7/73 , G06T5/002 , G06T7/0012 , G06T2207/10081 , G06T2207/30012 , G06T2207/20084 , G06T2200/04 , G06T2219/004
摘要： The present disclosure provides a method of positioning vertebra in a CT image, an apparatus, a computer device, and a computer readable storage medium. The method includes: pre-processing vertebra CT image data; inputting the pre-processed vertebra CT image data into a pre-trained neural network to obtain regression results of heat maps of key points corresponding to the pre-processed vertebra CT image data; regressing of 3D heat maps corresponding to the positions of the key points of the vertebra mass center based on the regression results of the heat maps of the key points and the pre-processed vertebra CT image data; serving 3D heat maps corresponding to the positions of the key points of the vertebra mass center as labels, and networked regressing 3D heat map information to position the vertebra. Effects caused by scanning machine difference and scanning noise are avoided, and the vertebra with complex forms is accurately positioned.
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公开(公告)号：US12086982B2
公开(公告)日：2024-09-10
申请号：US17612566
申请日：2020-10-30
发明人： Ge Li , Guanju Cheng , Chan Zeng , Peng Gao , Guotong Xie
CPC分类号： G06T7/0012 , G06T7/11 , G06T7/12 , G06T7/62 , G06T2207/20084 , G06T2207/30041
摘要： The present disclosure relates to an artificial intelligence field using a neural network, and publishes a method for confirming a cup-disc ratio based on a neural network, an apparatus, a computer device, and a computer readable storage medium. The method includes: obtaining a retinal image, and detecting an optical disc region in the retinal image to obtain the optical disc region; inputting the optical disc region into a pre-trained neural network to obtain a prediction cup-disc ratio and segment images of an optical cup and an optical disc; computing a cup-disc ratio based on the segment images of the optical cup and the optical disc; and confirming a practical cup-disc ratio based on the prediction cup-disc ratio and the computed cup-disc ratio.
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公开(公告)号：US20220309654A1
公开(公告)日：2022-09-29
申请号：US17612566
申请日：2020-10-30
发明人： Ge Li , Guanju Cheng , Chan Zeng , Peng Gao , Guotong Xie
摘要： The present disclosure relates to an artificial intelligence field using a neural network, and publishes a method for confirming a cup-disc ratio based on a neural network, an apparatus, a computer device, and a computer readable storage medium. The method includes: obtaining a retinal image, and detecting an optical disc region in the retinal image to obtain the optical disc region; inputting the optical disc region into a pre-trained neural network to obtain a prediction cup-disc ratio and segment images of an optical cup and an optical disc; computing a cup-disc ratio based on the segment images of the optical cup and the optical disc; and confirming a practical cup-disc ratio based on the prediction cup-disc ratio and the computed cup-disc ratio.
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