12 results about "Correction for attenuation" patented technology

A system includes an attenuation corrector configured to generate Computed Tomography-(CT-) based attenuation correction data from CT image data, a Positron Emission Tomography (PET) reconstructor configured to reconstruct first PET image data based on PET projection data and the CT-based attenuation correction data, an attenuation correction artifact mitigator configured to analyze the first PET image data for a presence of attenuation correction artifact, an inference engine configured to predict attenuation correction data based on non-attenuation corrected PET image data in response to the presence of attenuation correction artifact in the first PET image data, and an attenuation correction data updater configured to generate modified attenuation correction data based on the CT-based attenuation correction data and the predicted attenuation correction data. The PET reconstructor is further configured to reconstruct second PET image data based on the PET projection data and the modified attenuation correction data.

The invention discloses a PET / MR (positron emission tomography / magnetic resonance) all-in-one machine-based dynamic attenuation correction and respiratory and cardiac dual motion correction method. The method comprises the following steps of: generating a dynamic mu graph of a respiratory cycle; mR cardiac function movie sequence scanning of the cardiac cycle; accurately segmenting the cardiac muscle; 6, performing tissue segmentation on the dynamic mu graph; clustering the PET data; pET data space-time registration is carried out; merging PET data of the same time phase; performing frame-by-frame dynamic attenuation correction; respiratory movement correction; correcting a partial volume effect; carrying out myocardial MR image space standardization on different time phases of the cardiac cycle; and carrying out spatial standardization on the myocardial PET image of different time phases in the cardiac cycle. According to the method, the mu graph of the respiration and cardiac cycles is reconstructed through time-phase sharing and is accurately registered with the PET data, so that the high-quality attenuation correction of the heart PET image is realized and the motion correction is completed at the same time.

In emission imaging, one, two, or a few topograms without a full CT scan are used to localize, such as through triangulation, and / or generate an attenuation map, such as based on model fitting. A limited radiation exposure, rather than a longer, larger full CT exposure, is needed to localize and / or provide attenuation correction for emission imaging, such as cardiac SPECT imaging.

A method includes obtaining emission-tomography functional image data and a corresponding reconstructed anatomical image volume including at least one organ having natural motion; pre-determining a dedicated model for spatial mismatch correction of the at least one organ; performing initial image reconstruction of the emission-tomography functional image data to generate a reconstructed emission-tomography functional image volume utilizing attenuation correction based on the corresponding reconstructed anatomical image volume; and identifying relevant anatomical regions, within both image volumes, where functional image quality may be affected by the natural motion of the at least one organ. The method includes identifying and evaluating potential attenuation-correction image artifacts in the reconstructed emission-tomography functional image volume; estimating model parameters based on confirmed attenuation-correction image artifacts; correcting the corresponding reconstructed anatomical image volume to generate a corrected anatomical image volume; and reconstructing the emission-tomography functional image data utilizing attenuation correction based on the corrected anatomical image volume.

The invention is suitable for the technical field of medical images, and provides a correction method and device for a single photon emission type computed tomography image, electronic equipment and a storage medium, and the method comprises the steps: obtaining a training sample set which comprises a plurality of training samples, each training sample comprises an uncorrected SPECT image, a CT image registered with the uncorrected SPECT image, an attenuation image obtained by converting the CT image, and a corrected SPECT image obtained by performing attenuation correction on the uncorrected SPECT image by using the attenuation image; the training sample set is used for training a first correction network and a first generation network, the first correction network is used for generating a corrected SPECT image according to the input uncorrected SPECT image, and the second generation network is used for generating a target image according to the input corrected SPECT image; and performing iterative cascade fine tuning on the trained first correction network and the first generation network by using the training sample set to obtain a second correction network and a second generation network.

A system and method includes determining a region of interest of an imaged object, generating a first linear attenuation coefficient map of the imaged object, the first linear attenuation coefficient map being generated to associate voxels of the region of interest of the imaged object with a greater linear attenuation coefficient than voxels of other regions of the imaged object, attenuation correcting a plurality of tomographic frames of the imaged object based on the first linear attenuation coefficient map to generate a second plurality of tomographic frames, and determining a tomographic inconsistency of the second plurality of tomographic frames. Some aspects further include generating a second linear attenuation coefficient map of the imaged object, attenuation correcting the plurality of tomographic frames based on the second linear attenuation coefficient map to generate a third plurality of tomographic frames, and reconstructing a three-dimensional image based on the third plurality of tomographic frames and the determined tomographic inconsistency.

Systems and methods for generating registered attenuation maps are disclosed. For example, positron emission tomography (PET) measurement data, and co-modality measurement data from an anatomy modality, such as computed tomography (CT) data, is received from an image scanning system. A histo-image is generated based on the PET measurement data, and a co-modality image is generated based on the co-modality measurement data. A trained machine learning process is applied to the histo-image and the co-modality image. The trained machine learning process is configured to correct for misalignment between the histo-image and the co-modality image. Based on the application of the trained machine learning process to the histo-image and the co-modality image, a registered attenuation map is generated. In some examples, a PET image is reconstructed using the registered attenuation map.

The invention relates to the technical field of nuclear medicine imaging, and particularly provides an SPECT image reconstruction method and device applying scattered photons and a medium, and the method comprises the steps: determining an energy window group according to radionuclides, and obtaining an attenuation correction image and a DRR image based on a CT image; performing data acquisition based on the energy window group; inputting the DRR image and all the energy window data into a projection domain scatter correction model to enable the projection domain scatter correction model to output low-noise projection data without scattering photons, and then performing tomographic reconstruction on the low-noise projection data to generate a low-noise tomographic reconstruction image; or performing tomographic reconstruction on each piece of energy window data to obtain a tomographic reconstruction image corresponding to each piece of energy window data, and then inputting the attenuation correction image and all the tomographic reconstruction images into an image domain scatter correction model to enable the image domain scatter correction model to output a low-noise tomographic reconstruction image; the method can effectively improve the application value of the SPECT technology in precision medical treatment and quantitative analysis.

A system based upon artificial neural networks generates attenuation-corrected SPECT from non-attenuation-corrected SPECT (single photon emission computed tomography) without or with an intermediate step of attenuation map estimation. The system includes a SPECT scanner with CZT cameras for dynamic SPECT imaging. The system also includes a machine learning system including a 3D Dual Squeeze-and-Excitation Residual Dense Network for generating attenuation-corrected SPECT or attenuation maps from non-attenuation-corrected SPECT. The machine learning system reconstructs images from photopeak window and one or more scatter windows of the SPECT scanner are fed to the 3D Dual Squeeze-and-Excitation Residual Dense Network to generate attenuation-corrected SPECT or attenuation maps.

PET imaging (406) accounts for attenuation by MR hardware (110). A camera (112) captures the MR hardware (110) as positioned on or by the patient (116). For example, MR local coils to be or as positioned between the emission sources in the patient (116) and the PET detector are optically imaged (402). Image processing is used to determine (404) the position of the MR hardware (110). The attenuation of the MR hardware (110) is accounted for in attenuation correction for PET imaging (402) based on the determined position.

The embodiment of the invention provides an attenuation correction method and system and a storage medium. The method comprises the following steps: acquiring transmission data; acquiring radiation coincidence event data of the target object; and based on the transmission data and the radiation coincidence event data, performing attenuation correction reconstruction on the radiation image of the target object to obtain a radiation image after attenuation correction. The attenuation correction system is used for realizing the attenuation correction method and comprises a first acquisition module used for acquiring transmission data; the second acquisition module is used for acquiring radiation coincidence event data of the target object; and the reconstruction module is used for performing attenuation correction reconstruction on the radiation image of the target object based on the transmission data and the radiation coincidence event data to obtain the radiation image after attenuation correction.

A system based upon artificial neural networks generates attenuation-corrected SPECT from non-attenuation-corrected SPECT (single photon emission computed tomography) without or with an intermediate step of attenuation map estimation. The system includes a SPECT scanner with CZT cameras for dynamic SPECT imaging. The system also includes a machine learning system including a 3D Dual Squeeze-and-Excitation Residual Dense Network for generating attenuation-corrected SPECT or attenuation maps from non-attenuation-corrected SPECT. The machine learning system reconstructs images from photopeak window and one or more scatter windows of the SPECT scanner are fed to the 3D Dual Squeeze-and-Excitation Residual Dense Network to generate attenuation-corrected SPECT or attenuation maps.