-
公开(公告)号：US12094188B2
公开(公告)日：2024-09-17
申请号：US17565274
申请日：2021-12-29
发明人： Junhuan Li , Ruoping Li , Ling Hou , Pengfei Zhao , Yuwei Li , Kunlin Cao , Qi Song
IPC分类号： G06V10/774 , G06T7/00 , G06V10/776 , G06V10/82
CPC分类号： G06V10/7747 , G06T7/0012 , G06V10/776 , G06V10/82 , G06T2207/10081 , G06T2207/30048
摘要： The present disclosure relates to a training method and a training system for training a learning network for medical image analysis. The training method includes: acquiring an original training data set for a learning network with a predetermined structure; performing, by a processor, a pre-training on the learning network using the original training data set to obtain a pre-trained learning network; evaluating, by the processor, the pre-trained learning network to determine whether the pre-trained learning network has an evaluation defect; when the pre-trained learning network has the evaluation defect, performing, by the processor, a data augmentation on the original training data set for the existing evaluation defect; and performing, by the processor, a refined training on the pre-trained learning network using a data augmented training data set. The present disclosure can evaluate and train the learning network in stages, therefore, the complexity of medical image processing is reduced, and the efficiency and accuracy of medical image analysis are improved.
-
公开(公告)号：US12026881B2
公开(公告)日：2024-07-02
申请号：US17567458
申请日：2022-01-03
发明人： Bin Kong , Youbing Yin , Xin Wang , Yi Lu , Haoyu Yang , Junjie Bai , Qi Song
IPC分类号： G06T7/12 , G06F18/213 , G06F18/214 , G06T7/00 , G06T7/73 , G06V10/44
CPC分类号： G06T7/0012 , G06F18/213 , G06F18/214 , G06T7/75 , G06V10/44 , G06T2207/20081 , G06T2207/30104 , G06V2201/03
摘要： Embodiments of the disclosure provide methods and systems for joint abnormality detection and physiological condition estimation from a medical image. The exemplary method may include receiving, by at least one processor, the medical image acquired by an image acquisition device. The medical image includes an anatomical structure. The method may further include applying, by the at least one processor, a joint learning model to determine an abnormality condition and a physiological parameter of the anatomical structure jointly based on the medical image. The joint learning model satisfies a predetermined constraint relationship between the abnormality condition and the physiological parameter.
-
3.发明授权公开(公告)号：US11847547B2
公开(公告)日：2023-12-19
申请号：US17692337
申请日：2022-03-11
发明人： Xin Wang , Youbing Yin , Qi Song , Junjie Bai , Yi Lu , Yi Wu , Feng Gao , Kunlin Cao
CPC分类号： G06N3/006 , G06F18/217 , G06N3/08 , G06T19/00 , G06V10/42 , G06V10/776
摘要： Methods and Systems for generating a centerline for an object in an image and computer readable medium are provided. The method includes receiving an image containing the object. The method also includes generating the centerline of the object, by a processor, using a reinforcement learning network configured to predict movement of a virtual agent that traces the centerline in the image. The reinforcement learning network is further configured to perform at least one auxiliary task that detects a bifurcation in a trajectory of the object. The reinforcement learning network is trained by maximizing a cumulative reward and minimizing an auxiliary loss of the at least one auxiliary task. Additionally, the method includes displaying the centerline of the object.
-
公开(公告)号：US20230095242A1
公开(公告)日：2023-03-30
申请号：US17723863
申请日：2022-04-19
发明人： Shubao Liu , Junjie Bai , Youbing Yin , Feng Gao , Yue Pan , Qi Song
摘要： Embodiments of the disclosure provide methods and systems for multi-modality joint analysis of a plurality of vascular images. The exemplary system may include a communication interface configured to receive the plurality of vascular images acquired using a plurality of imaging modalities. The system may further include at least one processor, configured to extract a plurality of vessel models for a vessel of interest from the plurality of vascular images. The plurality of vessel models are associated with the plurality of imaging modalities, respectively. The at least one processor is also configured to fuse the plurality of vessel models associated with the plurality of imaging modalities to generate a fused model for the vessel of interest. The at least one processor is further configured to provide a diagnostic analysis result based on the fused model of the vessel of interest.
-
公开(公告)号：US11574122B2
公开(公告)日：2023-02-07
申请号：US16544837
申请日：2019-08-19
发明人： Feng Gao , Changsheng Liu , Yue Pan , Youbing Yin , Kunlin Cao , Qi Song
IPC分类号： G06F40/295 , G06N3/08 , G16H10/60
摘要： Embodiments of the disclosure provide systems and methods for processing unstructured texts in a medical record. A disclosed system includes at least one processor configured to determine a plurality of word representations of an unstructured text and tag entities in the unstructured text by performing a named entity recognition task on the plurality of word representations. The at least one processor is further configured to determine position embeddings based on positions of words in the unstructured text relative to positions of the tagged entities and concatenate the plurality of word representations with the position embeddings. The at least one processor is also configured to determine relation labels between pairs of tagged entities by performing a relationship extraction task on the concatenated word representations and position embeddings.
-
公开(公告)号：US20230005113A1
公开(公告)日：2023-01-05
申请号：US17741098
申请日：2022-05-10
发明人： Guang LI , Jinchen LI , Chengwei SUN , Cong CHEN , Kunlin CAO , Qi SONG
摘要： A method for medical image data enhancement is provided. The method includes: receiving a medical image sample set related to an object to be detected; based on an attribute of the object lacking in the medical image sample set, selecting a first medical image and a second medical image from the medical image sample set, where the first medical image contains the object lacking the attribute, and the second medical image does not contain the object lacking the attribute; determining a first area image block containing the lacking attribute; determining a second area image block not containing the lacking attribute; generating a composite area image block by fusing the first area image block and the second area image block based on a mask including an object part and a peripheral part around the object part; embedding the composite area image block back into the second medical image to obtain a third medical image; including the third medical image in the medical image sample set to obtain a data-enhanced medical image sample set.
-
公开(公告)号：US20220301154A1
公开(公告)日：2022-09-22
申请号：US17408321
申请日：2021-08-20
发明人： Ruoping LI , Pengfei ZHAO , Junhuan LI , Bin OUYANG , Yuwei LI , Kunlin CAO , Qi SONG
摘要： The present disclosure relates to a medical image analysis method, a medical image analysis device, and a computer-readable storage medium. The medical image analysis method includes receiving a medical image acquired by a medical imaging device; determining a navigation trajectory by performing navigation processing on the medical image based on an analysis requirement, the analysis requirement indicating a disease to be analyzed; extracting an image block set along the navigation trajectory; extracting image features using a first learning network based on the image block set; and determining an analysis result using a second learning network based on the image features and the navigation trajectory.
-
8.发明申请公开(公告)号：US20220091568A1
公开(公告)日：2022-03-24
申请号：US17468040
申请日：2021-09-07
发明人： Bin Kong , Youbing Yin , Xin Wang , Yi Lu , Qi Song
摘要： The disclosure relates to a method and device for predicting a physical parameter based on input physical information, and medium. The method may include predicting, by a processor, an intermediate variable based on the input physical information with an intermediate sub-model, which incorporates a constraint on the intermediate variable according to prior information of the physical parameter. The method may also include transforming, by the processor, the intermediate variable predicted by the intermediate sub-model to the physical parameter with a transformation sub-model.
-
公开(公告)号：US20210082580A1
公开(公告)日：2021-03-18
申请号：US17107881
申请日：2020-11-30
发明人： Bin Ma , Ying Xuan Zhi , Xiaoxiao Liu , Xin Wang , Youbing Yin , Qi Song
IPC分类号： G16H50/50 , A61B5/0275 , A61B5/026 , A61B6/00
摘要： The present disclosure is directed to a method and system for automatically predicting a physiological parameter based on images of vessel. The method includes receiving the images of a vessel acquired by an imaging device. The method further includes determining a sequence of temporal features at a sequence of positions on a centerline of the vessel based on the images of the vessel, and determining a sequence of structure-related features at the sequence of positions on the centerline of the vessel. The method also includes fusing the sequence of structure-related features and the sequence of temporal features at the sequence of positions respectively. The method additionally includes determining the physiological parameter for the vessel at the sequence of positions, by using a sequence-to-sequence neural network configured to capture sequential dependencies among the sequence of fused features.
-
公开(公告)号：US10937549B2
公开(公告)日：2021-03-02
申请号：US16048272
申请日：2018-07-28
发明人： Bin Ma , Ying Xuan Zhi , Xiaoxiao Liu , Xin Wang , Youbing Yin , Qi Song
摘要： The present disclosure is directed to a method and device for automatically predicting FFR based on images of vessel. The method for automatically predicting FFR based on images of a vessel. The method comprises a step of receiving the images of a vessel acquired by an imaging device. Then, a sequence of flow speeds at a sequence of positions on a centerline of the vessel is acquired by a processor. A sequence of first features at the sequence of positions on a centerline of the vessel are acquired by the processor, by fusing structure-related features and flow speeds and using a convolutional neural network. Then, a sequence of FFR at the sequence of positions is determined by the processor through using a sequence-to-sequence neural network on the basis of the sequence of first features.
-
-
-
-
-
-
-
-
-
搜索结果
69 条记录 (耗时 0.024 秒)
