公开(公告)号：EP3132291B1

公开(公告)日：2018-06-06

申请号：EP15717774.2

申请日：2015-04-09

Applicant: Siemens Aktiengesellschaft

Inventor： SUN, Shanhui ,  ERNST, Jan ,  SAPKOTA, Archana ,  RITZHAUPT-KLEISSL, Eberhard ,  WILES, Jeremy Ralph ,  CHEN, Terrence

IPC: G01W1/10

CPC classification number: G01W1/10 ,  G01J1/4204 ,  G01W1/12

Abstract: A method for predicting short-term cloud coverage includes a computer calculating an estimated cloud velocity field at a current time value based on sky images. The computer determines a segmented cloud model based on the sky images, a future sun location corresponding to a future time value, and sun pixel locations at the future time value based on the future sun location. Next, the computer applies a back-propagation algorithm to the sun pixel locations using the estimated cloud velocity field to yield propagated sun pixel locations corresponding to a previous time value. Then, the computer predicts cloud coverage for the future sun location based on the propagated sun pixel locations and the segmented cloud model.

公开(公告)号：EP3268894A1

公开(公告)日：2018-01-17

申请号：EP15712751.5

申请日：2015-03-11

Applicant: Siemens Aktiengesellschaft

Inventor： WAN, Shaohua ,  SUN, Shanhui ,  CHEN, Terrence ,  GEORGESCU, Bogdan ,  KAMEN, Ali

IPC: G06K9/00

CPC classification number: G06K9/6259 ,  G06K9/00134 ,  G06K9/00147 ,  G06K9/6249 ,  G06T7/0014 ,  G06T2207/10016 ,  G06T2207/10056 ,  G06T2207/30016 ,  G06T2207/30096

Abstract: A method for performing cellular classification includes using a convolution sparse coding process to generate a plurality of feature maps based on a set of input images and a plurality of biologically-specific filters. A feature pooling operation is applied on each of the plurality of feature maps to yield a plurality of image representations. Each image representation is classified as one of a plurality of cell types.

公开(公告)号：EP3132291A1

公开(公告)日：2017-02-22

申请号：EP15717774.2

申请日：2015-04-09

Applicant: Siemens Aktiengesellschaft

Inventor： SUN, Shanhui ,  ERNST, Jan ,  SAPKOTA, Archana ,  RITZHAUPT-KLEISSL, Eberhard ,  WILES, Jeremy Ralph ,  CHEN, Terrence

IPC: G01W1/10

CPC classification number: G01W1/10 ,  G01J1/4204 ,  G01W1/12

Abstract: A method for predicting short-term cloud coverage includes a computer calculating an estimated cloud velocity field at a current time value based on sky images. The computer determines a segmented cloud model based on the sky images, a future sun location corresponding to a future time value, and sun pixel locations at the future time value based on the future sun location. Next, the computer applies a back-propagation algorithm to the sun pixel locations using the estimated cloud velocity field to yield propagated sun pixel locations corresponding to a previous time value. Then, the computer predicts cloud coverage for the future sun location based on the propagated sun pixel locations and the segmented cloud model.

Abstract translation: 一种用于预测短期云覆盖的方法包括计算机基于天空图像计算当前时间值的估计云速度场。 计算机基于天空图像，未来太阳位置对应于未来时间值，以及基于未来太阳位置的未来时间值的太阳像素位置来确定分段云模型。 接下来，计算机使用估计的云速度场向太阳像素位置应用反向传播算法，以产生对应于先前时间值的传播的太阳像素位置。 然后，计算机基于传播的太阳像素位置和分段云模型预测未来太阳位置的云覆盖。

公开(公告)号：EP3332357A1

公开(公告)日：2018-06-13

申请号：EP16750307.7

申请日：2016-07-22

Applicant: Siemens Aktiengesellschaft

Inventor： BHATTACHARYA, Subhabrata ,  CHEN, Terrence ,  KAMEN, Ali ,  SUN, Shanhui

IPC: G06K9/46 ,  G06K9/00

CPC classification number: G06K9/00147 ,  A61B5/0042 ,  A61B5/0084 ,  G06K9/4609 ,  G06K9/4676 ,  G06K9/6223 ,  G06K9/6247 ,  G06K9/6255 ,  G06K9/6262 ,  G06K2209/05

Abstract: Independent subspace analysis (ISA) is used to learn (42) filter kernels for CLE images in brain tumor classification. Convolution (46) and stacking are used for unsupervised learning (44, 48) with ISA to derive the filter kernels. A classifier is trained (56) to classify CLE brain images based on features extracted using the filter kernels. The resulting filter kernels and trained classifier are used (60, 64) to assist in diagnosis of occurrence of brain tumors during or as part of neurosurgical resection. The classification may assist a physician in detecting whether CLE examined brain tissue is healthy or not and/or a type of tumor.

公开(公告)号：EP3265956A1

公开(公告)日：2018-01-10

申请号：EP15716647.1

申请日：2015-03-30

Applicant: Siemens Aktiengesellschaft

Inventor： WAN, Shaohua ,  SUN, Shanhui ,  KLUCKNER, Stefan ,  CHEN, Terrence ,  KAMEN, Ali

IPC: G06K9/00

CPC classification number: G06K9/00147 ,  A61B1/00009 ,  A61B1/04 ,  A61B90/20 ,  G02B21/0076 ,  G02B21/008 ,  G06K9/0014 ,  G06K9/6223 ,  G06K9/6276

Abstract: A method for performing cellular classification includes extracting a plurality of local feature descriptors from a set of input images and applying a coding process to covert each of the plurality of local feature descriptors into a multi-dimensional code. A feature pooling operation is applied on each of the plurality of local feature descriptors to yield a plurality of image representations and each image representation is classified as one of a plurality of cell types.

公开(公告)号：EP3274915A1

公开(公告)日：2018-01-31

申请号：EP16716344.3

申请日：2016-03-24

Applicant: Siemens Aktiengesellschaft

Inventor： WAN, Shaohua ,  SUN, Shanhui ,  BHATTACHARYA, Subhabrata ,  CHEN, Terrence ,  KAMEN, Ali

IPC: G06K9/00

CPC classification number: G06K9/00147 ,  A61B1/00009 ,  A61B5/4255 ,  G06K9/6255 ,  G06T7/0012

Abstract: A method and system for classifying tissue endomicroscopy images are disclosed. Local feature descriptors are extracted from an endomicroscopy image. Each of the local feature descriptors is encoded using a learnt discriminative dictionary. The learnt discriminative dictionary includes class-specific sub-dictionaries and penalizes correlation between bases of sub-dictionaries associated with different classes. Tissue in the endomicroscopy image is classified using a trained machine learning based classifier based on the coded local feature descriptors encoded using a learnt discriminative dictionary.