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公开(公告)号：US20230351646A1
公开(公告)日：2023-11-02
申请号：US17965289
申请日：2022-10-13
Inventor： Jinyi QI , Tiantian LI , Zhaoheng XIE , Wenyuan QI , Li YANG , Chung CHAN , Evren ASMA
CPC classification number: G06T11/005 , G06V10/44 , G06V10/7635 , G06V10/82 , G06V20/49 , G06T7/20 , G06T2207/10104 , G06T2207/20081
Abstract: A method, apparatus, and computer instructions stored on a computer-readable medium perform latent image feature extraction by performing the functions of receiving image data acquired during an imaging of a patient, wherein the image data includes motion by the patient during the imaging; segmenting the image data to include M image data segments corresponding to at least N motion phases having shorter durations than a duration of the motion by the patient during the imaging, wherein M is a positive integer greater than or equal to a positive integer N; producing, from the M image data segments, at least N latent feature vectors corresponding to the motion by the patient during the imaging; and performing a gated reconstruction of the N motion phases by reconstructing the image data based on the at least N latent feature vectors.
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公开(公告)号：US20230206516A1
公开(公告)日：2023-06-29
申请号：US17682738
申请日：2022-02-28
Inventor： Jinyi QI , Tiantian LI , Zhaoheng XIE , Wenyuan QI , Li YANG , Chung CHAN , Evren ASMA
CPC classification number: G06T11/005 , G06T3/40 , G06T7/0014 , A61B6/5282 , A61B6/027 , A61B6/032 , A61B6/037 , G06T2207/20081 , G06T2207/20084 , G06T2207/10104 , G06T2207/10081 , G06T2207/30004 , G06T2210/41 , G06T2211/40
Abstract: A method, system, and computer readable medium to perform nuclear medicine scatter correction estimation, sinogram estimation and image reconstruction from emission and attenuation correction data using deep convolutional neural networks. In one embodiment, a Deep Convolutional Neural network (DCNN) is used, although multiple neural networks can be used (e.g., for angle-specific processing). In one embodiment, a scatter sinogram is directly estimated using a DCNN from emission and attenuation correction data. In another embodiment a DCNN is used to estimate a scatter-corrected image and then the scatter sinogram is computed by a forward projection.
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公开(公告)号：US20210335022A1
公开(公告)日：2021-10-28
申请号：US16857916
申请日：2020-04-24
Applicant: CANON MEDICAL SYSTEMS CORPORATION
Inventor： Li YANG , Wenyuan QI , Evren ASMA
IPC: G06T11/00
Abstract: A method of imaging includes obtaining a plurality of dynamic sinograms, each dynamic sinogram representing detection events of gamma rays at a plurality of detector elements, summing the plurality of dynamic sinograms to generate an activity map based on a radioactivity level of the gamma rays; reconstructing, using the plurality of dynamic sinograms, a plurality of dynamic images, each of the plurality of dynamic images corresponding to one of the each of the plurality of dynamic sinograms, and generating, using the plurality of dynamic sinograms and the activity map, at least one parametric image.
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4.发明申请公开(公告)号：US20210304457A1
公开(公告)日：2021-09-30
申请号：US17180182
申请日：2021-02-19
Inventor： Jinyi QI , Tiantian LI , Zhaoheng XIE , Wenyuan QI , Li YANG , Chung CHAN , Evren ASMA
Abstract: To reduce the effect(s) caused by patient breathing and movement during PET data acquisition, an unsupervised non-rigid image registration framework using deep learning is used to produce motion vectors for motion correction. In one embodiment, a differentiable spatial transformer layer is used to warp the moving image to the fixed image and use a stacked structure for deformation field refinement. Estimated deformation fields can be incorporated into an iterative image reconstruction process to perform motion compensated PET image reconstruction. The described method and system, using simulation and clinical data, provide reduced error compared to at least one iterative image registration process.
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5.发明公开公开(公告)号：US20240225585A1
公开(公告)日：2024-07-11
申请号：US18336807
申请日：2023-06-16
Inventor： Wenyuan QI , Li YANG , Jeffrey KOLTHAMMER , Yu-Jung TSAI , Evren ASMA , Maria IATROU , Jinyi QI , Tiantian LI
Abstract: A method for performing single gating in a positron emission tomography (PET) system includes: receiving list-mode data acquired by scanning an imaging object using the PET system, the list-mode data being affected by quasi-periodic motion of the imaging object; producing a plurality of vectors based on the received list-mode data; generating a reference vector based on the produced plurality of vectors; selecting, from the produced plurality of vectors, a set of vectors corresponding to a single gate, based on respective differences compared with the generated reference vector; and generating an image of the imaging object based on the selected set of vectors.
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Patent Agency Ranking
6.发明公开公开(公告)号：US20230260171A1
公开(公告)日：2023-08-17
申请号：US17674063
申请日：2022-02-17
Applicant: CANON MEDICAL SYSTEMS CORPORATION
Inventor： Wenyuan QI , Qiang YI , Evren ASMA , Li YANG , Peng PENG
CPC classification number: G06T11/006 , A61B6/037 , A61B6/5282 , G01T1/2985 , G06T11/005 , G06T2211/421
Abstract: Upon receiving list-mode data by detecting radiation emitted from a radiation source positioned with a field of view of a medical imaging scanner, each photon included in the list-mode data can be classified according to one or more interaction properties, such as energy or number of crystals interacted with. Grouped pairs of photons can be generated based on the classifying, and a corresponding interaction-property-specific correction kernel (e.g., a corresponding interaction-property-specific point spread function correction kernel) can be selected for each group. Corresponding interaction-property-specific correction kernels can then be utilized to generate higher quality images.
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公开(公告)号：US20220113437A1
公开(公告)日：2022-04-14
申请号：US17557710
申请日：2021-12-21
Applicant: CANON MEDICAL SYSTEMS CORPORATION
Inventor： Wenyuan QI , Yi QIANG , Evren ASMA , Xiaoli LI , Li YANG , Peng PENG , Jeffrey KOLTHAMMER
IPC: G01T1/29
Abstract: A method of normalizing detector elements in an imaging system is described herein. The method includes a line source that is easier to handle for a user, and decouples the normalization of the detector elements into a transaxial domain and an axial domain in order to isolate errors due to positioning of the line source. Additional simulations are performed to augment the real scanner normalization. A simulation of a simulated line source closely matching the real line source can be performed to isolate errors due to physical properties of the crystals and position of the crystals in the system, wherein the simulated detector crystals are otherwise modeled uniformly. A simulation of a simulated cylinder source can be performed to determine errors due to other effects stemming from gaps between the detector crystals.
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公开(公告)号：US20240037814A1
公开(公告)日：2024-02-01
申请号：US17878413
申请日：2022-08-01
Applicant: CANON MEDICAL SYSTEMS CORPORATION
Inventor： Chung CHAN , Li YANG , Xiaoli LI , Wenyuan QI , Evren ASMA , Jeffrey KOLTHAMMER
IPC: G06T11/00
CPC classification number: G06T11/005 , G06T2211/412
Abstract: A dynamic frame reconstruction apparatus and method for medical image processing is disclosed which reduces the computationally expensive reconstruction of images but which retains the accuracy of the image reconstruction. A convolutional neural network is used to cluster the dynamic data into groups of frames, each group sharing similar radiotracer distribution. In one embodiment, groups of frames that have similar reconstruction parameters are determined, and scatter and random estimations are computed once and shared among each of the frames in the same frame group.
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9.发明公开公开(公告)号：US20230237638A1
公开(公告)日：2023-07-27
申请号：US17961365
申请日：2022-10-06
Inventor： Tiantian LI , Zhaoheng XIE , Wenyuan QI , Li YANG , Evren ASMA , Jinyi QI
CPC classification number: G06T7/0004 , G06T5/002 , G06T2207/10104 , G06T2207/10088 , G06T2207/10081 , G06T2207/20081 , G06T2207/20084
Abstract: A method, apparatus, and non-transitory computer-readable storage medium for image denoising whereby a deep image prior (DIP) neural network is trained to produce a denoised image by inputting the second medical image to the DIP neural network and combining a converging noise and an output of the DIP network during the training such that the converging noise combined with the output of the DIP network approximates the first medical image at the end of the training, wherein the output of the DIP network represents the denoised image.
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公开(公告)号：US20220327665A1
公开(公告)日：2022-10-13
申请号：US17225672
申请日：2021-04-08
Applicant: CANON MEDICAL SYSTEMS CORPORATION
Inventor： Chung CHAN , Li YANG , Wenyuan Ql , Evren ASMA , Jeffrey KOLTHAMMER , Yi QIANG
Abstract: Existing, low quality images can be restored using reconstruction or a combination of post-reconstruction techniques to generate a real patient phantom. The real patient phantom (RPP) can then be simulated in Monte Carlo simulations of a higher performance system and a lower performance system. Alternatively, the RPP can be simulated in the higher performance system, and a real scan can be performed by an existing, lower performance system. The higher performance system can be differentiated from the lower performance system in a variety of ways, including a higher resolution time of flight measurement capability, a greater sensitivity, smaller detector crystals, or less scattering. A neural network can be trained using the images produce by the higher performance system as the target, and the images produced by the lower performance system as the input. After training, the trained neural network can be used to output input images taken in a lower performance system with higher performance system characteristics.
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