General Electric Company

University of Washington

Zhongmin Steve Lin

Gopal Biligeri Avinash

Saad Ahmed Sirohey

Ananth P Mohan

Fausto J Espinal

Patrick Michael Virtue

Tamanna Nanavaty Bembenek

Satoshi Minoshima

A system comprising a memory device having a plurality of routines stored therein, a processor configured to execute the plurality of routines stored in the memory device, the plurality of routines comprising: a routine configured to effect, when executed, accessing of patient deviation scores indicative of differences between patient data and reference data representative of a population segment, wherein the patient deviation scores are derived from longitudinal data of the patient data such that the patient deviation scores include a plurality of sets of patient deviation scores, each set indicative of differences between patient data collected at a respective point in time and the reference data; a routine configured to effect, when executed, identifying a trend in the patient deviation scores for at least one clinical parameter; a routine configured to effect, when executed, generating of a report including a visual indication of the trend; and a routine configured to effect, when executed, outputting of the report. The report includes one or more views including Z, T, D, DT, and D feedback on T views, using image and non-image data.

System and method for integrated quantifiable detection, diagnosis and monitoring of disease using patient related time trend data

Methods and apparatus for determining brain cortical thickness are provided. One method includes determining an intensity profile at each of a plurality of cortical surface points of an imaged brain using brain tissue image data and calculating a cortical thickness based on a parametrically determined transition point of each intensity profile.

Methods and apparatus for determining brain cortical thickness

A system and method for analyzing and visualizing a local feature of interest includes access of a clinical image dataset comprising clinical image data acquired from a patient, identification of a region of interest (ROI) from the clinical image dataset, and extraction of at least one local feature corresponding to the ROI. The system and method also include definition of a local feature dataset comprising data representing at least one local feature, access of a pre-computed reference dataset comprising image data representing an expected value of the at least one identified derived characteristic of interest, and comparison of the characteristic dataset to the pre-computed reference dataset. Further, the system and method include calculation of at least one deviation metric from the comparison and output of a visualization of the at least one deviation metric.

System and method for analyzing and visualizing local clinical features

A method for navigating a three-dimensional (3D) image includes accessing a 3D image dataset, generating a 3D mesh corresponding to a 3D segmentation result using the 3D image dataset, displaying a 3D surface rendering of the 3D surface mesh, and navigating the 3D image based on a manual input received from a user indicated on the rendered 3D mesh.

Method and system for navigating, segmenting, and extracting a three-dimensional image

A system and method for correcting inhomogeneity of spatial intensity in 3D MR image data includes application of a 3D filter to the 3D MR image to generate a first set of data and a second set of data. The first set of data includes a high frequency component and a weak edge component, and the second set of data includes a low frequency component and a strong edge component. The system and method also include derivation of an inhomogeneity correction from the second set of data, application the inhomogeneity correction to the second set of data, and addition of the first set of data to the inhomogeneity corrected second set of data to create a corrected 3D MR image.

System and method for correcting inhomogeneity of spatial intensity in 3D MR image data

A system, method, and apparatus includes a computer readable storage medium with a computer program stored thereon having instructions that cause a computer to access a first anatomical image data set of an imaging subject acquired via a morphological imaging modality, access a functional image data set of the imaging subject acquired via a functional imaging modality, register the first anatomical image data set to the functional image data set, segment the functional image data set based on the functional image data set, define a binary mask based on the segmented functional image data set, and apply the binary mask to the first anatomical image data set to construct a second anatomical image data set and an image based thereon. The second anatomical image data set is substantially free of image data of the first anatomical image data set correlating to an area outside the region of physiological activity.

Apparatus and method for isolating a region in an image

A method for extracting a three-dimensional (3D) volume of interest from a three-dimensional (3D) image dataset includes accessing a 3D image dataset that includes a plurality of image slices, enclosing a 3D volume of interest in the 3D image dataset using a 3D mesh, automatically extracting the 3D volume of interest based on the 3D mesh, and generating a 3D image of the extracted 3D volume of interest. A computer and a non-transitory computer readable medium are also described herein.

A data processing technique is provided. In one embodiment, a computer-implemented method includes accessing reference deviation maps for a plurality of disease types. The reference deviation maps may include subsets of maps associated with severity levels of respective disease types, and a disease severity score may be associated with each severity level. The method may include selecting patient severity levels for multiple disease types based on the subsets of reference deviation maps. Also, the method may include automatically calculating a combined patient disease severity score based at least in part on the disease severity scores associated with the selected patient severity levels, and may include outputting a report based at least in part on the combined patient disease severity score. Additional methods, systems, and manufactures are also disclosed.

System and method for analysis of multiple diseases and severities

A data processing technique is provided. In one embodiment, a computer-implemented method includes accessing patient image and non-image deviation scores derived through respective comparisons of patient image and non-image data to standardized image and non-image data. The method may also include processing the image and non-image deviation scores to generate a visual output indicative of differences between the patient image and non-image data, and the standardized image and non-image data, respectively. Further, the method may include displaying the visual output. Additional methods, systems, and manufactures are also disclosed.

Medical data processing and visualization technique

A data processing technique is provided. In one embodiment, a computer-implemented method includes accessing individual patient deviation maps indicative of a structural difference and a functional difference, respectively, of at least one anatomical region of a patient with respect to standardized reference image data. The method may also include generating a composite patient deviation map indicative of both the structural difference and the functional difference based on at least the individual patient deviation maps, and outputting the composite patient deviation map. Additional methods, systems, and manufactures are also disclosed.

System and method for mapping structural and functional deviations in an anatomical region

A data processing technique is provided. In one embodiment, a computer-implemented method includes accessing patient deviation data of a structural difference between a patient anatomical feature and a standardized anatomical feature. The method may also include comparing the patient deviation data to reference deviation data sets representative of multiple disease types. Each reference deviation data set may be representative of an expected deviation from the standardized anatomical feature for a particular disease type. The method may further include automatically identifying one or more potential patient disease types based at least in part on the comparison. Additional methods, systems, and manufactures are also disclosed.

Growing community of inventors

New Berlin, WI, United States of America

Zhongmin Steve Lin