公开(公告)号：US11875898B2

公开(公告)日：2024-01-16

申请号：US17331251

申请日：2021-05-26

Applicant: MERATIVE US L.P.

Inventor： Luyao Shi ,  David James Beymer ,  Ehsan Dehghan Marvast ,  Deepta Rajan

IPC: G06T7/00 ,  G16H50/20 ,  G16H30/40 ,  G06F18/21

CPC classification number: G16H50/20 ,  G06F18/217 ,  G06T7/0014 ,  G16H30/40 ,  G06T2207/20076 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30061 ,  G06T2207/30101

Abstract: Methods and systems for training computer-aided condition detection systems. One method includes receiving a plurality of images for a plurality of patients, some of the images including an annotation associated with a condition; iteratively applying a first deep learning network to each of the images to produce an attention map, a feature map, and an image-level probability of the condition for each of the images; iteratively applying a second deep learning network to each feature map produced by the first network to produce a plurality of outputs; training the first network based on the attention map produced for each image; and training the second network based on the output produced for each of the patients. The second network includes a plurality of convolution layers and a plurality of convolutional long short-term memory (LSTM) layers. Each of the outputs includes a patient-level probability of the condition for one of the patients.