Siemens Medical Solutions Usa, Inc.

Toshiba Medical Systems Corporation

Kabushiki Kaisha Toshiba

Toshiba Medical Systmes Corporation

Miesher Rodrigues

Alexander Hans Vija

Yu Zou

Xiaolan Wang

Yuexing Zhang

Hao Yang

Gin Chung Wang

Liang Cai

Daniel Gagnon

Chunguang Cao

Srutarshi Banerjee

James Frank Caruba

Ronald E Malmin

Michal Cachovan

Francesc dAssis Massanes Basi

Sachin S Junnarkar

Alan Karr

Jimmy Wang

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 training to and/or estimating location, energy level, and/or time of occurrence of incident radiation on a solid-state detector, a machine-learned model, such as a neural network, performs the inverse problem. An estimate of the location, energy level, and/or time is output by the machine-learned model in response to input of the detected signal (e.g., voltage over time). The estimate may account for material property variation of the solid-state detector in a rapid and easily calculated way, and with a minimal amount of data.

Inverse neural network for particle detection in a solid-state-devices

Systems and methods to manufacture a collimator include deposition of a first layer of material in a first pattern, the first pattern comprising a first plurality of substantially parallel lines oriented in a first direction, and deposition of a second layer of material in a second pattern directly upon the first layer of material, the second pattern comprising a second plurality of substantially parallel lines oriented in a second direction different from the first direction. An area bounded by a first pair of the first plurality of substantially parallel lines and a second pair of the second plurality of substantially parallel lines intersecting the first pair defines a septum of the collimator.

Systems and methods of three-dimensional printing of collimators using additive approaches

To capture more emitted photons with a Compton camera, the scatter detector is tilted (non-orthogonal angle) relative to a radial from the isocenter of the imaging system. The tilt creates a greater volume for scatter interaction. To capture more scatter photons, the catcher detector is non-planar, such as a multi-faced detector at least partially surrounding a volume behind the scatter detector. The tilted scatter detector alone, the non-planar catcher detector alone, or the tilted scatter detector and the non-planar catcher detector are used in the Compton camera.

Near 2Pi Compton camera for medical imaging

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

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

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

To optimize an image quality and/or a sensitivity, a Compton camera is adaptable. A scatter detector and/or a catcher detector may move closer to and/or further away from a patient and/or each other. This adaptation allows a balancing of the image quality and the sensitivity by altering the geometry.

Adaptive Compton camera for medical imaging

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

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.

Calibration of radiation dose estimation in medical nuclear imaging

Systems and methods for dose calibration. A dose calibrator may include one or more radiation sources, one or more solid-state detectors and one or more plates positioned between the one or more radiation sources and the one or more solid-state detectors. The one or more solid-state detectors capture one or more images based on emissions received from the one or more radiation sources through the one or more plates for estimating activity of the one or more radiation sources.

Solid-state dose calibration system

A method of training a neural network modeling physical phenomena of semiconductor material includes receiving plurality of training pairs corresponding to a semiconductor material. Each training pair comprises an input charge to a distinct voxel of the semiconductor material and one or more output signals generated by the distinct voxel in response to the input charge. A neural network is trained using the training pairs. The neural network models the semiconductor material and each voxel is represented in the neural network by a tensor field defined by (i) a location of the voxel within the semiconductor material and (ii) one or more physics-based phenomena within the voxel at the location.

Space time electron-hole charge transport network for solid-state material studies

A method of manufacturing a collimator () on a three-dimensional printer () includes obtaining design specifications () for the collimator, the design specifications including a channel perimeter pattern and an overall collimator thickness, determining a first quantity of deposit layer permutation types based on the channel perimeter pattern, determining a respective second quantity of permutation layer elements () for each respective one of the deposit layer permutations, generating respective sets of sequences for each respective one of the deposit layer permutations, the number of sets equal to the respective second quantity for the corresponding deposit layer permutations, assembling the respective sets of sequences into a three-dimensional print file (), providing the three-dimensional file to the three-dimensional printer, and manufacturing the collimator by depositing additive layers of material based on contents of the three-dimensional file. A system for implementing the method and a non-transitory computer-readable medium are also disclosed.

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Buffalo Grove, IL, United States of America

Miesher Rodrigues