Siemens Aktiengesellschaft

Siemens Energy, Inc.

Siemens Corporation

Siemens Healthcare Gmbh

Technische Universitat Munchen

Jingdan Zhang

Shaohua Kevin Zhou

Dorin Comaniciu

Waheed A Abbasi

Xuefei Guan

Neil Birkbeck

El Mahjoub Rasselkorde

Michal Sofka

Michael J Metala

Chin-Sheng Lee

Ashley L Lewis

Steve H Radke

Bogdan Georgescu

Tommaso Mansi

Yefeng Zheng

Berthold Kiefer

Michael Kelm

Jerome Declerck

Larry C Himes

Felix Lugauer

Moritz Michael Knorr

Puneet Sharma

Ali Kamen

David D Liu

Viorel Mihalef

Gianluca Paladini

Mark William Fischer

Nikolai R Tevs

Martin Requardt

Jens Guehring

Andre De Oliveira

Thomas Boettger

Nancy H Ulerich

Jens Wetzl

Peter Gall

Nathan S Lay

Kai Kadau

Michael F Fair

Jens Kaftan

Scott A Karstetter

Shaolei Feng

Kristof Ralovich

Francois Carnis

Bernhard Fuerst

Artem Gritsenko

Hui Zhen

Timo Kohlberger

Christopher John William Adams

Chris Vierck

Peter Faltin

Daniel S Morgan

Yan Guo

Guozhen Li

Nam Eung Kim

A method dynamically reconstructing a stress and strain field of a turbine blade includes providing a set of response measurements from at least one location on a turbine blade, band-pass filtering the set of response measurements based on an upper frequency limit and a lower frequency limit, determining an upper envelope and a lower envelope of the set of response measurements from local minima and local maxima of the set of response measurements, calculating a candidate intrinsic mode function (IMF) from the upper envelope and the lower envelope of the set of response measurements, providing an N&#xd7;N mode shape matrix for the turbine blade, where N is the number of degrees of freedom of the turbine blade, when the candidate IMF is an actual IMF, and calculating a response for another location on the turbine blade from the actual IMF and mode shapes in the mode shape matrix.

Turbine blade fatigue life analysis using non-contact measurement and dynamical response reconstruction techniques

A method and software system for flaw identification, grouping and sizing for fatigue life assessment for rotors used in turbines and generators. The method includes providing ultrasonic data of a plurality of rotor slices and providing volume reconstruction of the ultrasonic data. The method also includes providing in-slice identification, grouping and sizing of flaw indications in the rotor based on the volume reconstruction. Further, the method includes providing inter-slice identification, grouping and sizing of the flaw indications based on the in-slice flaw indications and providing flaw location and size information. The method can be used in both phased-array and A-scan inspections.

System and method for identification, grouping and sizing of embedded flaws in rotor components using ultrasonic inspection

A method for probabilistic fatigue life prediction using nondestructive testing data considering uncertainties from nondestructive examination (NDE) data and fatigue model parameters. The method utilizes uncertainty quantification models for detection, sizing, fatigue model parameters and inputs. A probability of detection model is developed based on a log-linear model coupling an actual flaw size with a nondestructive examination (NDE) reported size. A distribution of the actual flaw size is derived for both NDE data without flaw indications and NDE data with flaw indications by using probabilistic modeling and Bayes theorem. A turbine rotor example with real world NDE inspection data is presented to demonstrate the overall methodology.

Probabilistic modeling and sizing of embedded flaws in ultrasonic nondestructive inspections for fatigue damage prognostics and structural integrity assessment

In a general methodology for insulation defect identification in a generator core, a Chattock coil is used to measure magnetic potential difference between teeth. Physical knowledge and empirical knowledge is combined in a model to predict insulation damage location and severity. Measurements are taken at multiple excitation frequencies to solve for multiple characteristics of the defect.

Insulation defect detection of high voltage generator stator core

A method for predicting fatigue crack growth in materials includes providing a prior distribution obtained using response measures from one or more target components using a fatigue crack growth model as a constraint function, receiving new crack length measurements, providing a posterior distribution obtained using the new crack length measurements, and sampling the posterior distribution to obtain crack length measurement predictions.

Construction of entropy-based prior and posterior probability distributions with partial information for fatigue damage prognostics

A method of fatigue life prediction including: calculating a critical crack size of an object of interest; identifying a first flaw in ultrasound data of the object of interest; determining that the first flaw interacts with a second flaw, the first flaw is to be merged with the second flaw, or the first flaw is isolated; calculating an initial crack size based on the determination; and calculating an increase in the initial crack size due to fatigue and creep to determine a number of load cycles until the initial crack size reaches the critical crack size.

Method and system of deterministic fatigue life prediction for rotor materials

A method is disclosed for segmentation of a calcified blood vessel in image data. An embodiment of the method includes providing a vesseltree representation of the blood vessel; providing a number of preliminary boundary representations of a number of cross-sections of the blood vessel; providing a number of intensity profiles in the image data in the number of cross-sections; determining a calcification in the cross-section based on the intensity profile; and correcting each preliminary boundary representation into a corrected boundary representation which excludes the calcification from an inner part of the blood vessel. A segmentation system is also disclosed.

Segmentation of a calcified blood vessel

A method and a segmentation system are disclosed. An embodiment of the method includes providing an image representation of the structure; providing a start surface model, including a mesh with a plurality of vertices connected by edges; defining for each vertex a ray normal to the surface model at the position of the vertex; assigning more than two labels to each vertex, each label representing a candidate position of the vertex on the ray; providing a representation of likelihoods for each candidate position the likelihood referring to whether the candidate position corresponds to a surface point of the structure in the image representation; and defining a first order Markow Random Field with discrete multivariate random variables, the random variables including the labels of the candidate positions and the representation of likelihoods, finding an optimal segmentation of the structure by using an maximum a posteriori estimation in this Markow Random Field.

Segmentation of a structure

A method and system for prediction of respiratory motion from 3D thoracic images is disclosed. A patient-specific anatomical model of the respiratory system is generated from 3D thoracic images of a patient. The patient-specific anatomical model of the respiratory system is deformed using a biomechanical model. The biomechanical model is personalized for the patient by estimating a patient-specific thoracic pressure force field to drive the biomechanical model. Respiratory motion of the patient is predicted using the personalized biomechanical model driven by the patient-specific thoracic pressure force field.

System and method for prediction of respiratory motion from 3D thoracic images

A method and system for fully automatic liver segmentation in a multi-channel magnetic resonance (MR) image is disclosed. An initial liver boundary in the multi-channel MR image, such as an MR Dixon scan. The segmented initial liver boundary in the multi-channel MR image is refined based on features extracted from multiple channels of the multi-channel MR image using a trained boundary detector. The features may be extracted from an opposed channel and a water channel of an MR Dixon scan.

Method and system for segmentation of the liver in magnetic resonance images using multi-channel features

A method and system for fully automatic segmentation the prostate in magnetic resonance (MR) image data is disclosed. Intensity normalization is performed on an MR image of a patient to adjust for global contrast changes between the MR image and other MR scans and to adjust for intensity variation within the MR image due to an endorectal coil used to acquire the MR image. An initial prostate segmentation in the MR image is obtained by aligning a learned statistical shape model of the prostate to the MR image using marginal space learning (MSL). The initial prostate segmentation is refined using one or more trained boundary classifiers.

Method and system for automatic prostate segmentation in magnetic resonance images

A method and system for patient-specific computational modeling and simulation for coupled hemodynamic analysis of cerebral vessels is disclosed. An anatomical model of a cerebral vessel is extracted from 3D medical image data. The anatomical model of the cerebral vessel includes an inner wall and an outer wall of the cerebral vessel. Blood flow in the cerebral vessel and deformation of the cerebral vessel wall are simulated using coupled computational fluid dynamics (CFD) and computational solid mechanics (CSM) simulations based on the anatomical model of the cerebral vessel.

Method and system for patient-specific computational modeling and simulation for coupled hemodynamic analysis of cerebral vessels

A method and system for automatic multi-organ segmentation in a 3D image, such as a 3D computed tomography (CT) volume using learning-base segmentation and level set optimization is disclosed. A plurality of meshes are segmented in a 3D medical image, each mesh corresponding to one of a plurality of organs. A level set in initialized by converting each of the plurality of meshes to a respective signed distance map. The level set optimized by refining the signed distance map corresponding to each one of the plurality of organs to minimize an energy function.

Method and system for multi-organ segmentation using learning-based segmentation and level set optimization

A method and system for automatic lung segmentation in magnetic resonance imaging (MRI) images and videos is disclosed. A plurality of predetermined key landmarks of a lung are detected in an MRI image. The key landmarks may be detected using discriminative joint contexts representing combinations of multiple key landmarks. A lung boundary is segmented in the MRI image based on the detected key landmarks. The landmark detection and the lung boundary segmentation can be repeated in each frame of an MRI video.

Method and system for automatic lung segmentation in magnetic resonance imaging videos

A method and system for segmenting multiple organs in medical image data is disclosed. A plurality of landmarks of a plurality of organs are detected in a medical image using an integrated local and global context detector. A global posterior integrates evidence of a plurality of image patches to generate location predictions for the landmarks. For each landmark, a trained discriminative classifier for that landmark evaluates the location predictions for that landmark based on local context. A segmentation of each of the plurality of organs is then generated based on the detected landmarks.

Method and system for joint multi-organ segmentation in medical image data using local and global context

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Plainsboro, NJ, United States of America

Jingdan Zhang