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PROGRESSIVE AND MULTI-PATH HOLISTICALLY NESTED NETWORKS FOR SEGMENTATION
专利权人:
The United States of America; as represented by the Secretary Department of Health and Human Service
发明人:
Adam Patrick Harrison,Ziyue Xu,Le Lu,Ronald M. Summers,Daniel Joseph Mollura
申请号:
US16620464
公开号:
US20200184647A1
申请日:
2018.06.08
申请国别(地区):
US
年份:
2020
代理人:
摘要:
Methods include processing image data through a plurality of network stages of a progressively holistically nested convolutional neural network, wherein the processing the image data includes producing a side output from a network stage m, of the network stages, where m>;1, based on a progressive combination of an activation output from the network stage m and an activation output from a preceding stage m−;1. Image segmentations are produced. Systems include a 3D imaging system operable to obtain 3D imaging data for a patient including a target anatomical body, and a computing system comprising a processor, memory, and software, the computing system operable to process the 3D imaging data through a plurality of progressively holistically nested convolutional neural network stages of a convolutional neural network.
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