General Electric Company

Robert John Johnsen

Andras Kriston

Istvan Ubelhart

Pal Csongor Sprencz

Elizabeth Philps

Andrea Fazekas

Ferenc Kovacs

Tamas Blaskovics

Kathryn M Littlejohn

Michael Lee Spohn

Kenneth Vosniak

Burke D Brunet

Nicholas Waterton

Methods and systems are provided for medical imaging systems. In one embodiment, a method includes receiving one or more image reconstruction parameters defining an image reconstruction process for reconstructing one or more images from medical imaging data, identifying a target hardware allocation based on the one or more image reconstruction parameters, and reconstructing, via computing device hardware as specified by the target hardware allocation, one or more images from the medical imaging data according to the image reconstruction process.

Methods and systems for reconstructing images

Methods and systems for evaluating bone lesions include accessing a first dataset acquired from a patient with a first imaging modality and a second dataset acquired from the patient with a second imaging modality. A segmentation is performed on the first dataset to identify a subset of the first dataset corresponding to a skeletal structure of the patient and a patient skeletal metric representing a total bone volume of the patient is automatically calculated from the subset of the first dataset. The methods and systems further include detection of at least one lesion in the second dataset, classification of the at least one lesion as a bone or non-bone lesion, automatic calculation of a bone lesion metric based on the classification, and calculation of a lesion burden as a ratio of the bone lesion metric and the patient skeletal metric.

Methods and systems for evaluating bone lesions

A method for automatically displaying an organ of interest includes accessing a series of medical images acquired from a first imaging modality, receiving an input that indicates an organ of interest, automatically detecting the organ of interest within at least one image in the series of medical images, automatically placing a visual indicator in the region of interest, and automatically propagating the visual indicator to at least one image that is acquired using a second different imaging modality. A medical imaging system and a non-transitory computer readable medium are also described herein.

Systems and methods for performing image background selection

A method for predicting PMT failure in a gamma camera by generating historical data for each PMT in a gamma camera indicating high voltage gain values at which each PMT causes autotune failure. The historical data is analyzed to predict PMT failure accurately thereby allowing PMT maintenance prior to failure actually occurring.

Failure predictor for photomultiplier tubes

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Waukesha, WI, United States of America

Robert John Johnsen