Siemens Medical Solutions Usa, Inc.

Siemens Aktiengesellschaft

Alexander Hans Vija

Amos Yahil

Michal Cachovan

Miesher Rodrigues

Francesc dAssis Massanes Basi

Xinhong Ding

Jun Ma

Xing Rong

Guenter Hahn

Manjit Ray

James Chester Sanders, Iii

Raymond Shi Xu

Steffen Kappler

James Frank Caruba

Ronald E Malmin

Ansgar Graw

Jinhun Joung

Dennis Steibel, Jr

Grant Arthur Albert

Darrell Burckhardt

Douglas Jay Wagenaar

James C Sanders, Iii

Maximilian Reymann

Amos Yahill

James C Sanders

Francesc Dassis Massanes Basi

A multi-modality imaging system allows for selectable photoelectric effect and/or Compton effect detection. The camera or detector is a module with a catcher detector. Depending on the use or design, a scatter detector and/or a coded physical aperture are positioned in front of the catcher detector relative to the patient space. For low energies, emissions passing through the scatter detector continue through the coded aperture to be detected by the catcher detector using the photoelectric effect. Alternatively, the scatter detector is not provided. For higher energies, some emissions scatter at the scatter detector, and resulting emissions from the scattering pass by or through the coded aperture to be detected at the catcher detector for detection using the Compton effect. Alternatively, the coded aperture is not provided. The same module may be used to detect using both the photoelectric and Compton effects where both the scatter detector and coded aperture are provided with the catcher detector. Multiple modules may be positioned together to form a larger camera, or a module is used alone. By using modules, any number of modules may be used to fit with a multi-modality imaging system. One or more such modules may be added to another imaging system (e.g., CT or MR) for a multi-modality imaging system.

Multi-modal compton and single photon emission computed tomography medical imaging system

For controlling reconstruction in emission tomography, the quality of data for detected emissions and/or the application controls the settings used in reconstruction. For example, a count density of the detected emissions is used to control the number of iterations in reconstruction to more likely avoid over and under fitting. The count density may be adaptively determined by re-binning through pixel size adjustment to find a smallest pixel size providing a sufficient count density. As another example, the detected data may have poor quality due to motion or high body mass index (BMI) of the patient, so the reconstruction is set to perform differently (e.g., less smoothing for high motion or a different number of iterations for high BMI). The quality of the data may be used in conjunction with the application or task for imaging the patient to control the reconstruction.

Data driven reconstruction in emission tomography

Multi-modal Compton and single photon emission computed tomography medical imaging system

A framework for characterization of a collimator. In accordance with one aspect, first and second sides of the collimator are photographed to generate first and second image data. An optical characterization map (OCM) may be generated based on the first and second image data, wherein the optical characterization map characterizes the individual channels of the collimator. Quality assessment or image reconstruction may then be performed based on the OCM.

Individual channel characterization of collimator

For calibration in medical emission tomography, the dosimeter and/or detector is calibrated in the field, such as at the clinic or other patient scanning location. To allow for a fewer number of calibration sources used in calibrating and/or assist in calibration for multispectral emission tomography, a calibration source includes multiple isotopes and/or a proxy source or isotope is used instead of the same isotope used in factory calibration.

General purpose, wide energy range calibration source for medical emission tomography

For partial volume correction, the partial volume effect is simulated using patient-specific segmentation. An organ or other object of the patient is segmented using anatomical imaging. For simulation, the locations of the patient-specific object or objects are sub-divided, creating artificial boundaries in the object. A test activity is assigned to each sub-division and forward projected. The difference of the forward projected activity to the test activity provides a location-by-location partial volume correction map. This correction map is used in reconstruction from the measured emissions, resulting in more accurate activity estimation with less partial volume effect.

Partial volume correction in multi-modality emission tomography

A system and method include training of an artificial neural network to generate an output three-dimensional image volume based on input two-dimensional projection images, the training based on a plurality of subsets of two-dimensional projection images of each of a plurality of sets of two-dimensional projection images and associated ones of three-dimensional image volumes reconstructed from each of the plurality of sets of two-dimensional projection images.

Network determination of limited-angle reconstruction

A system and method includes acquisition of a plurality of images, each of the plurality of images representing radiotracer concentration in a respective volume at a respective time period, and training of a neural network, based on the plurality of images, to output data indicative of radiation dose associated with a first volume over a first time period based on a first image representing radiotracer concentration in the first volume over a second time period, the second time period being shorter than the first time period.

Neural network-assisted dose assessment based on activity image

A system and method include an array of sensors electrically coupled to a material capable of converting a gamma ray to electrical charge, where distances between a center of a first sensor and centers of each sensor immediately-adjacent to the first sensor are substantially equal. Signals are collected from each sensor immediately-adjacent to the first sensor, and one of a plurality of logical sub-pixels of the first sensor is determined based on the signals collected from each sensor immediately-adjacent to the first sensor.

Sensor layout for direct converter detector

A detector used for tomography imaging is mobile, allowing the detector to move about an object (e.g., patient to be imaged). A swarm of such detectors, such as a swarm of drones with detectors, may be used for tomography imaging. The trajectory or trajectories of the mobile detectors may account for the pose and/or movement of the object being imaged. The trajectory or trajectories may be based, in part, on the sampling for desired tomography. An image of an internal region of the object is reconstructed from detected signals of the mobile detectors using tomography.

Mobile tomography imaging

A system and method includes determination of a region of interest of an imaging subject, generation of a first linear attenuation coefficient map of the imaging subject, the first linear attenuation coefficient map generated to associate voxels of the region of interest of the imaging subject with greater linear attenuation coefficients than voxels of other regions of the imaging subject, attenuation-correction of a plurality of tomographic frames of the imaging subject based on the first linear attenuation coefficient map to generate a second plurality of tomographic frames, and determination of tomographic inconsistency of the second plurality of tomographic frames. Some aspects further include generation of a second linear attenuation coefficient map of the imaging subject, attenuation-correction of the plurality of tomographic frames based on the second linear attenuation coefficient map to generate a third plurality of tomographic frames, and reconstruction of a three-dimensional image based on the third plurality of tomographic frames and the determined tomographic inconsistency.

Attenuation correction-based weighting for tomographic inconsistency detection

A Compton camera for medical imaging is divided into segments with each segment including part of the scatter detector, part of the catcher detector, and part of the electronics. The different segments may be positioned together to form the Compton camera arcing around part of the patient space. By using segments, any number of segments may be used to fit with a multi-modality imaging system.

Compton camera with segmented detection modules

A framework for quality-driven image processing. In accordance with one aspect, image data and anatomical data of a region of interest are received. Zonal information is generated based on the anatomical data. Image processing is performed based on the image data to generate an intermediate image. One or more image quality metrics may then be determined for the intermediate image data using the zonal information. A processing action may be performed based on the one or more image quality metrics to generate a final image.

Quality-driven image processing

For gamma ray detection, 3D tiling is made possible by modules that include a gamma ray detector with at least some electronics extending away from the detector as a side wall, leaving an air or low attenuation gap behind the gamma ray detector. The modules may be stacked to form arrays of any shape in 3D, including stacking to form a Compton detector with a scatter detector separated from the catcher detector by the low attenuation gap where the electronics form at least one side wall between the detectors. The modules may be stacked so that the detectors from the different modules are in different planes and/or not part of a same surface (e.g., same surface provided with just 1D or 2D tiling).

Three-dimensional tileable gamma ray detector

For calibration of internal dose in nuclear imaging, the dose model used for estimating internal dose in a patient is calibrated. One or more values of the dose model (e.g., a physics simulation, dose kernels, or a transport model) are set based on measured dose. The dose may be measured relative to specific tissues and/or isotopes, providing for tracer and tissue specific calibration. For example, dose from the tracer to be injected into the patient is estimated from emissions as well as measured by a dosimeter in a tissue mimicking tissue mimicking object. These doses are used to calibrate the dose model, which calibrated dose model is then used to determine internal dose for the patient.

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Evanston, IL, United States of America

Alexander Hans Vija