Auxiliary method for evaluating fibrosis of peripheral glomerular tissue based on deep learning and computer equipment

The invention discloses an auxiliary method for evaluating fibrosis of peripheral glomerular tissues based on deep learning, computer equipment and a computer readable storage medium, the method can be used for assisting in evaluating fibrosis of the peripheral glomerular tissues and the degree ther...

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Main Authors WANG TAIPING, ZHANG MINFEI
Format Patent
LanguageChinese
English
Published 10.05.2022
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Abstract The invention discloses an auxiliary method for evaluating fibrosis of peripheral glomerular tissues based on deep learning, computer equipment and a computer readable storage medium, the method can be used for assisting in evaluating fibrosis of the peripheral glomerular tissues and the degree thereof, the accuracy is high, and the efficiency is high; the method provided by the invention can provide an accurate basis for subsequent diagnosis and treatment. According to the method based on deep learning, the model has better robustness and generalization ability, and compared with an existing detection method, better accuracy can be obtained. 本发明公开了一种基于深度学习的用于评估肾小球周围组织纤维化的辅助方法、计算机设备及计算机可读存储介质,本发明方法能够用于辅助评估肾小球周围组织纤维化及其程度,准确度高,效率高;本发明方法可以为后续的诊断与治疗提供准确的依据。本申请基于深度学习的方法,使得模型具有更好的鲁棒性和泛化能力,相比现有的检测法能够获得较好的准确性。
AbstractList The invention discloses an auxiliary method for evaluating fibrosis of peripheral glomerular tissues based on deep learning, computer equipment and a computer readable storage medium, the method can be used for assisting in evaluating fibrosis of the peripheral glomerular tissues and the degree thereof, the accuracy is high, and the efficiency is high; the method provided by the invention can provide an accurate basis for subsequent diagnosis and treatment. According to the method based on deep learning, the model has better robustness and generalization ability, and compared with an existing detection method, better accuracy can be obtained. 本发明公开了一种基于深度学习的用于评估肾小球周围组织纤维化的辅助方法、计算机设备及计算机可读存储介质,本发明方法能够用于辅助评估肾小球周围组织纤维化及其程度,准确度高,效率高;本发明方法可以为后续的诊断与治疗提供准确的依据。本申请基于深度学习的方法,使得模型具有更好的鲁棒性和泛化能力,相比现有的检测法能够获得较好的准确性。
Author WANG TAIPING
ZHANG MINFEI
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Snippet The invention discloses an auxiliary method for evaluating fibrosis of peripheral glomerular tissues based on deep learning, computer equipment and a computer...
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Title Auxiliary method for evaluating fibrosis of peripheral glomerular tissue based on deep learning and computer equipment
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