US 11,055,847 B2
Adversarial and dual inverse deep learning networks for medical image analysis
Shaohua Kevin Zhou, Princeton, NJ (US); Mingqing Chen, Plainsboro, NJ (US); Daguang Xu, Princeton, NJ (US); Zhoubing Xu, Plainsboro, NJ (US); and Dong Yang, Somerset, NJ (US)
Assigned to Siemens Healthcare GmbH, Erlangen (DE)
Filed by Siemens Healthcare GmbH, Erlangen (DE)
Filed on Mar. 18, 2020, as Appl. No. 16/822,101.
Application 16/822,101 is a division of application No. 15/868,062, filed on Jan. 11, 2017, granted, now 10,636,141.
Claims priority of provisional application 62/457,013, filed on Feb. 9, 2017.
Prior Publication US 2020/0219259 A1, Jul. 9, 2020
Int. Cl. G06K 9/00 (2006.01); G06T 7/00 (2017.01); G06K 9/66 (2006.01); G06T 7/11 (2017.01); G06N 7/00 (2006.01); G06N 3/04 (2006.01); G06K 9/62 (2006.01); G06N 3/08 (2006.01)
CPC G06T 7/0012 (2013.01) [G06K 9/6267 (2013.01); G06K 9/66 (2013.01); G06N 3/0454 (2013.01); G06N 3/084 (2013.01); G06N 7/005 (2013.01); G06T 7/11 (2017.01); G06K 2209/05 (2013.01); G06T 2207/10072 (2013.01); G06T 2207/10081 (2013.01); G06T 2207/10088 (2013.01); G06T 2207/10104 (2013.01); G06T 2207/10116 (2013.01); G06T 2207/10132 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01)] 15 Claims
OG exemplary drawing
 
1. A method for automatically performing a medical image analysis task on a medical image of a patient, comprising:
receiving a medical image of a patient;
inputting the medical image to a trained deep neural network; and
automatically estimating an output model that provides a result of a target medical image analysis task on the input medical image using the trained deep neural network, wherein the trained deep neural network is trained in a deep image-to-image dual inverse network.