86 results about "Positron emission tomography" patented technology

A multiplexing scheme for both energy and timing information is provided for a particle detection system having a photosensor array with multiple photosensors. Each photosensor is associated with multiple scintillator modules. The system has a segmented pseudo-prismatic light guide with multiple pseudo-prismatic segments. Each segment is associated with multiple photosensors, and the photosensors are adjacent. Each scintillator module contacts its associated photosensor at one end and its associated segment at the other end. Each of the multiple photosensors may be connected to an energy readout channel, such that photosensors associated with the same segment are not connected to the same energy readout channel. Each energy readout channel has at least two timestamps associated therewith.

A positron emission tomography (PET) scanner may include a plurality of gamma radiation detector modules arranged to form a detector ring. Each detector module may include an array of elongated scintillation crystals. With respect to the detector ring, each elongated scintillation crystal includes a proximal end-face, two axially oriented lateral faces, two transaxially oriented lateral faces, and a distal end-face radially oriented into the detector ring to receive a gamma photon. An array of photosensors is positioned along a first of the axially oriented lateral faces of each elongated scintillation crystal to detect scintillation photons. A reflective material is positioned on the proximal end-face, the distal end-face, the transaxially oriented lateral faces, and a second of the axially oriented lateral faces of each elongated scintillation crystal to internally reflect scintillation photons. In various embodiments, a dual-channel processing circuit provides distinct timing and energy signals from the photosensors.

The present invention relates to novel, selective compounds with affinity to TDP-43, and to novel, selective radiolabelled TDP-43 ligands which are useful for imaging TDP-43 aggregates, using positron-emission tomography (PET). The invention is also directed to compositions comprising such compounds, to processes for preparing such compounds and compositions, to the use of such compounds and compositions for imaging TDP-43 aggregates in a tissue or a subject, in vitro or in vivo, and to precursors of said compounds.

Combining positron emission tomography (PET) scan 111 and computed tomography (CT) scan 121 of portion of body (i.e. lung) into combined image scan 132 for segmentation. Training machine learning for

This invention relates to a convolution-based method for noise suppression in positron emission tomography (PET) flow field images, comprising the following steps: S1, obtaining consistent data through CFD flow field simulation and GATE detection system simulation, and reconstructing a low-resolution initial image of the PET flow field containing noise using the OSEM algorithm; S2, constructing a noise suppressor model, inputting the low-resolution initial image into the model, and outputting a noise-suppressed flow field feature image using a deep convolutional network and multi-scale feature fusion technology; S3, constructing a multi-loss fusion evaluation system, using mean squared error loss, minimum absolute value deviation loss, and perceptual loss to jointly constrain model training, and iteratively updating the weights using the Adam optimizer. This invention not only improves the enhancement model's ability to distinguish noise information, thereby enhancing the model's ability to remove noise information from PET images, but also significantly improves evaluation metrics such as PSNR and SSIM.

The invention belongs to the technical field of inorganic scintillator materials, and particularly relates to a multi-element co-doped yttrium lutetium silicate scintillator and a preparation method and application thereof, and the material has excellent comprehensive performance of high light output, short decay time, high radiation hardness, high matching degree of emission spectrum and novel photoelectric sensors and the like. The invention further relates to a preparation method of the scintillator material and application of the scintillator material in radiation detection fields such as positron emission tomography (PET), time flight PET (TOF-PET), interaction depth PET (DOI-PET), single photon emission computed tomography (SPECT), high-energy physical experiments, nuclear medicine imaging, industrial nondestructive inspection, safety detection (such as luggage and cargo container inspection) and the like.

The present invention relates to novel, selective compounds with affinity to TDP-43, and to novel, selective radiolabelled TDP-43 ligands which are useful for imaging TDP-43 aggregates, using positron-emission tomography (PET). The invention is also directed to compositions comprising such compounds, to processes for preparing such compounds and compositions, to the use of such compounds and compositions for imaging TDP-43 aggregates in a tissue or a subject, in vitro or in vivo, and to precursors of said compounds.

This application discloses a three-dimensional dose reconstruction method and related equipment based on in-beam positron emission tomography (PET) data. The method includes: acquiring list-pattern data during proton therapy beam exit; performing conformation processing on the list-pattern data and reconstructing a three-dimensional activity distribution map; performing multi-nucleus dynamic deconvolution processing on the activity time series corresponding to the three-dimensional activity distribution map according to the physical half-life of the target nuclide and preset biological elution parameters to obtain the initial activity distribution corresponding to the target nuclide; mapping the initial activity distribution to a three-dimensional relative dose distribution using a preset dose mapping algorithm; converting the three-dimensional relative dose distribution into a three-dimensional absolute dose distribution according to a pre-established water phantom calibration curve; and generating a cumulative dose distribution report based on the three-dimensional absolute dose distribution. The embodiments of this application can reconstruct the three-dimensional absolute dose distribution with high accuracy and support inter-session dose accumulation analysis. This application can be widely applied in the field of dose reconstruction technology.

This invention discloses a radioactive molecular probe for targeting CSPG4 / NG2, its preparation method, and its application. The radioactive molecular probe comprises the structure shown in Formula I or Formula II. The technical solution of this invention uses a radioactive molecular probe to specifically recognize CSPG4 / NG2 in vivo through the target polypeptide portion, thereby achieving specific nuclear medicine positron emission tomography (PET) or single-photon emission computed tomography (SPECT) imaging diagnosis of CSPG4 / NG2 positive tumors or CSPG4 / NG2 positive lesions, such as autoimmune diseases and cardiovascular and cerebrovascular diseases, thereby realizing early diagnosis and efficacy evaluation of malignant tumors.

A method for performing dynamic positron emission tomography (PET) is disclosed. The method includes collecting volumetric radioactive measurement data associated with an administered radioactive tracer present in a target site of a subject over multiple scanning intervals, capturing a magnetic resonance image of the target site, and performing a motion correction process to the volumetric radioactive measurement data to produce motion corrected PET data. The method further includes co-registering the magnetic resonance image and motion corrected data to generate a co-registered dynamic PET volume, and applying a model corrected input function (MCIF) to the co-registered dynamic PET volume to calibrate an uptake amount of the radioactive tracer in the target site.

The present disclosure provides a modular radiation therapy apparatus comprising a plurality of modules configured to sequentially interlock within one another in an annular arrangement, wherein the plurality of modules are individually extractable from the annular arrangement and at least a subset of the plurality of modules comprise computing elements configured to communicate with one another, the plurality of modules comprising a collimator module comprising a multi-leaf collimator (MLC) and at least one sensor, a linear accelerator (LINAC) module comprising at least one of a magnetron or a klystron, at least one imaging module comprising at least one of an image detector, an imaging source, a magnetic imaging system, a single photon emission computed tomography (SPECT) system, or a positron emission tomography (PET) system, a patient tracking module, a cooling module, and a vacuum module, and performing at least one of: monitoring a respective status of the plurality of modules via onboard sensors and computing elements to determine whether any module is in an error state and provisioning status information and module identifiers to a remote computing environment; or distributing computational workloads among the plurality of modules and communicating with a remote computing environment to offload processing tasks using federated processing operations.

The invention belongs to the technical field of artificial intelligence assisted medical treatment, and particularly relates to a PET / CT tumor imaging examination result prediction system based on a large language model. The system comprises an input module used for inputting information of a patient; the prediction module is used for analyzing the information of the patient according to the large language model to obtain a prediction result that the patient is possibly positive in PET / CT tumor imaging examination; and the output module is used for outputting the prediction result. The method can assist a doctor in deciding whether a patient needs to be subjected to PET / CT examination or not, so that the PET / CT examination is more reasonable, and the positive rate of the PET / CT examination is effectively improved. Therefore, the method has a good application prospect.

Provided are a fluorine-18-labeled positron emission tomography (PET) radiotracer for diagnosing neuroinflammation, stroke or cerebral infarction and a method for diagnosing cancer in a subject including administering a fluorine-18-labeled PET radiotracer a subject, obtaining in vivo PET images of the uptake of the fluorine-18-labeled positron emission tomography (PET) radiotracer in a lesion in the subject, and evaluating the uptake of the fluorine-18-labeled radiotracer in the lesion.

The invention belongs to the technical field of PET (positron emission tomography), and relates to a PET probe extensive field image multi-model adaptive deformation and FPGA (field programmable gate array) curing method, which comprises the following steps of: acquiring single-lift event data of a PET probe; generating an original extensive field image based on the single-lift event data; performing coordinate traversal transformation on the original extensive field images by adopting an image deformation model in a preset multi-model transformation library; performing off-line analysis on each model and the parameters thereof in the multi-model transformation library by utilizing a preset evaluation index, and screening out an optimal model and an optimal parameter; and transforming the original pan-field image by using the optimal model and the optimal parameters to generate an enhanced image and a crystal position lookup table, and solidifying the enhanced image and the crystal position lookup table to the FPGA. The method has the beneficial effects that the local adhesion area can be stretched in a targeted manner through the nonlinear transformation model, the distinction degree of crystal event clusters is remarkably improved, and the LUT calibration precision is fundamentally improved.

The invention discloses a double-target small-molecule probe, a radionuclide-labeled double-target small-molecule probe as well as a preparation method and application of the radionuclide-labeled double-target small-molecule probe. The medicine < 68 > Ga-DOTA-PRE / RGD is obtained by labeling < 68 > Ga radionuclide, and is applied to PET / MR (positron emission tomography / magnetic resonance imaging) imaging of pancreatic cancer tumors. A radioactive product with high purity and high stability (greater than 93%) is obtained through a simple marking method; the obtained double-target radioactive small molecular probe 68Ga-DOTA-PRE / RGD has a huge potential for the accurate diagnosis of pancreatic cancer.

The application relates to the field of positron emission tomography technology, in particular to a multi-channel high-precision PET circuit acquisition system and a use method thereof, and the system comprises the following: an FPGA control board, which is used for controlling bias voltage programming output voltage values, controlling current programming output voltage values and current values according to DAC bias voltage values received from an upper computer, and sending DUT board configuration information received from the upper computer to a DUT board; and the DUT board, which comprises multi-channel high-precision PET circuits, each circuit is configured through an SPI protocol according to DUT board configuration information received from the upper computer, 16 channels are adopted to collect time electric signal information output by a PET detector, and 64 channels are adopted to collect energy electric signal information output by the PET detector. In the application, the multi-channel high-precision PET circuit acquisition software and the hardware of the control system are portable, the upper computer software program is programmable, and the operation is simple.

Systems and methods for reconstructing medical images based on the trained deep learning processes, and for training deep learning processes, are disclosed. In some examples, image measurement data is received. A histo-image is generated based on the image measurement data. Further, an attenuation map, such as a μ-map, is received. An attenuation histo-image is generated based on the attenuation map. Further, a trained machine learning process, such as a trained neural network, is applied to features generated from the histo-image and the attenuation histo-image. Based on the application of the machine learning process to the histo-image and the attenuation histo-image, output image data characterizing an image volume is generated. In some examples, a machine learning process is trained based on histo-images and corresponding attenuation histo-images. The trained machine learning process may be employed to reconstruct images, such as positron emission tomography (PET) images.

The invention belongs to the technical field of artificial intelligence assisted medical treatment, and particularly relates to a PET / CT report integrity automatic judgment method and system based on a large language model. The automatic judgment method comprises the following steps: analyzing the PET / CT report according to a large language model to obtain a prediction result of whether the PET / CT report is complete or not. The invention further constructs a PET / CT report integrity automatic discrimination system based on the method. According to the method, the integrity of the PET / CT report can be efficiently and accurately judged, the integrity of the PET / CT report can be improved, and the medical service quality can be improved. Therefore, the method has a good application prospect.

To provide a resource allocation system and method for managing the use of local and remote resources for medical image processing tasks.SOLUTION: A simplified medical imaging ecosystem 100 including various networked medical facilities includes a first medical facility 102 and a second medical facility 103 that are operated as part of a medical system 106. The medical facility 102 includes a CT scanner 110, which includes a LCI112 used to process acquired projections to reconstruct CT images, and an MR scanner 120, which includes a LCI122 and processes acquired projections to reconstruct MR images. Medical facility 103 includes a computed tomography (CT) scanner 130 that includes a LCI132 used to process acquired projections to reconstruct CT images and a positron emission tomography (PET) scanner 140 that includes a LCI142 used to process acquired projections to reconstruct PET images.SELECTED DRAWING: Figure 1

The invention discloses a PET (Positron Emission Tomography) image maximum likelihood reconstruction method based on variational auto-encoder constraint, and provides an innovative two-stage reconstruction framework in order to solve the problem of serious noise of a traditional maximum likelihood expectation maximization algorithm in low-dose PET reconstruction. In the first stage, a variational auto-encoder (VAE) is pre-trained, a decoder of the VAE is extracted to serve as a powerful image generation constraint model, and the model can map a low-dimensional latent vector into a clear PET image. In the second stage, given PET measurement data is not directly optimized in a pixel space, but an image is expressed as output of a decoder, namely x = D (z), and then an optimal latent vector z is searched in a low-dimensional latent space through a gradient descent method. According to the method, the solution space is constrained on the manifold defined by the depth generation model, so that the problem of noise amplification of a traditional method is greatly inhibited, and the signal-to-noise ratio and the structural fidelity of a reconstruction result are remarkably superior to those of a traditional MLEM method.

An electronic readout network topology for positron emission tomography is able to provide Time of Flight for photodetectors arranged in matrix arrays made up of a plurality of silicon photomultipliers. Each photodetector has anode and cathode terminals. The readout network topology ensures suitable polarisation of the set of photodetectors and provides a reduction diagram by creating a single connection to extract a unique time reference signal that is accurate and synched up in phase to a detection event at any position of the photodetector matrix instead of connecting to each individual photodetector. A fast amplifier with low input impedance is electrically coupled to this time reference signal, creating a path of low impedance for the rapid transition signals, reducing the total parasitic capacitance of the parallel arrangement of detectors, and improving the time response of the detector block. Moreover, the readout electronics creates a smaller number of positioning signals.

The present invention facilitates manufacturing of a scintillator array, a radiation detection device, and a positron emission tomography device. A scintillator array (11) is provided with at least one pair of scintillators (11Uia, 11Uib), a light reflection member (LA) disposed in a first location between the scintillators for preventing light from passing between the scintillators, and an air layer (LB) disposed in a second location between the scintillators for allowing light to pass between the scintillators.

The application relates to a PET report generation system based on segmented extraction reasoning learning, relates to the fields of medical image analysis and natural language processing, and aims to solve the problem that language models in the prior art are difficult to efficiently generate high-quality reports.The PET report generation system based on segmented extraction reasoning learning comprises a training data set acquisition module, a model acquisition module and a to-be-tested PET report generation module; the training data set acquisition module is used for acquiring PET reports, and a SERI training data set is constructed based on the PET reports; SERI is segmented extraction reasoning; the model acquisition module is used for training a model based on the SERI training data set to obtain a trained model; the to-be-tested PET report generation module is used for inputting a to-be-tested PET report into the trained model, and the trained model outputs extraction information and reasoning conclusions of the PET report; the PET is a positron emission tomography.

Provided herein are compounds useful as imaging agents. Exemplary compounds provided herein are useful as myeloperoxidase imaging agents using positron emission tomography or fluorescence imaging techniques. Methods for preparing the compounds provided herein and diagnostic methods using radiolabeled arid unlabeled compounds are also provided.

Methods for detecting a mold infection in a subject, comprising administering 18F-fluorodeoxysorbitol (18F-FDS) to the subject and taking an image, e.g., a positron emission tomography (PET) and computed tomography (CT) image, are disclosed. The mold infection can include, for example, an Aspergillus, a non-Aspergillus (galactomannan-negative), or an azole-resistant (Aspergillus calidoustus) mold infection, or other clinically relevant molds.

Compounds and their use for imaging a disease, condition, or disorder associated with one or more Complement system pathways are disclosed.

A positron emission tomography-magnetic resonance (PET-MR) system is provided. The PET-MR system includes an MR subsystem, a PET subsystem, and a protocol adjustment system. The protocol adjustment system includes a protocol adjustment computing device having at least one processor programmed to receive a protocol. The protocol includes a scanning task list including a PET scanning task of a bed and MR scanning tasks of the bed and to be performed simultaneously with the PET scanning task. The protocol also includes a combination list indicating MR data acquired by an MR scanning task of one bed are to be combined with MR data acquired by the same MR scanning task of another bed. The at least one processor is further programmed to adjust the protocol based on the combination list by processing the one or more MR scanning tasks based on the combination list.

The invention relates to the technical field of medicine synthesis, and discloses a positron medicine synthesis module mechanical structure and a control system.The positron medicine synthesis module mechanical structure comprises a bottom plate, a machine shell is installed on the upper surface of the bottom plate, an injection pump assembly is arranged on the machine shell and comprises a mounting plate, and the mounting plate is fixed in the machine shell; the device comprises a mounting plate, two symmetrically arranged fixing assemblies are arranged on the surface of the mounting plate, two symmetrically arranged connecting frames are slidably connected to the inner wall of the mounting plate, a moving assembly is arranged on one side of each connecting frame, syringes are placed in the fixing assemblies and the moving assemblies, and the moving assemblies are used for pushing the syringes to inject liquid medicine. According to the invention, through the dual positioning design of the fixed assembly and the moving assembly and the cooperation of the steel ball and the spring, the tight clamping of the shell and the push rod is realized, the offset and power transmission loss are avoided, and the high-precision characteristic of screw transmission is combined, so that the quantitative filling of the liquid medicine is realized, and the precision of the synthesis process is improved.

The present application relates to a kind of low-dose PET image enhancement method and system, belong to medical and industrial field positron emission tomography (PET) imaging, for solving prior art using anatomical structure information MR image as prior information when low-dose PET image data is generated normal dose PET image, effect is not good.This scheme is obtained from MR image and spatial anatomical arrangement information through spatial transformation anatomical structure spatial characteristics, by first using anatomical structure spatial characteristics with low-dose PET image characteristics to realize the adaptive enhancement of spatial region information and different modal fusion, to improve the anatomical structure display quality of low-dose image data, improve anatomical structure definition, provide effective reference for clinical diagnosis, reduce tracer usage, reduce economic cost, reduce patient radiation burden.

The invention belongs to the technical field of positron emission tomography, and relates to a PET probe extensive field image dot matrix self-adaptive recognition and anomaly detection method, which comprises the following steps: acquiring an original extensive field image of a PET probe and preprocessing the original extensive field image; performing global projection and peak searching based on the pre-processed extensive field image, and counting the number of projection peak values; judging whether the number of the projection peak values accords with expectation or not; on the basis of the number of projection peak values conforming to expectation, performing global adaptive grid division on the preprocessed image to obtain a plurality of sub-image regions; performing local bidirectional projection and Gaussian fitting on each sub-image area, and determining a positioning coordinate set of each point in the crystal array; and based on the positioning coordinate set, performing anomaly detection to generate a quality inspection report. The method has the beneficial effects that the adaptability is high, the method does not depend on a prior template, an accurate geometric template does not need to be provided during image quality screening, the dot matrix scale is automatically estimated by analyzing extensive field image data, and the universality and deployment convenience of the method are improved.