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公开(公告)号：US20220076116A1
公开(公告)日：2022-03-10
申请号：US17186323
申请日：2021-02-26
摘要： According to one embodiment, a learning apparatus includes processing circuitry. The processing circuitry acquires a plurality of learning samples to be learned and a plurality of target labels associated with the respective learning samples, iteratively learns a learning model so that a learning error between output data corresponding to the learning sample and the target label is small with respect to the learning model to which the output data is output by inputting the learning sample, and displays a layout image in which at least some of the learning samples are arranged based on a learning progress regarding the iterative learning of the learning model and a plurality of the learning errors.
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公开(公告)号：US20160054453A1
公开(公告)日：2016-02-25
申请号：US14832332
申请日：2015-08-21
发明人： Kenta MORIYASU , Taichiro SHIODERA , Shuhei NITTA , Tomoyuki TAKEGUCHI , Hidenori TAKESHIMA , Toshiyuki ONO , Takashi IDA , Hiroaki NAKAI
IPC分类号： G01T1/17 , G01N23/04 , G01N23/087 , G01T1/29
摘要： A photon counting X-ray CT apparatus according to an embodiment includes: data acquiring circuitry, and processing circuitry. The data acquiring circuitry is configured to allocate energy measured by signals output from a photon counting detector in response to incidence of X-ray photons to any of a plurality of first energy bins so as to acquire a first data group as count data of each of the first energy bins. The processing circuitry is configured to determine a plurality of second energy bins obtained by grouping the first energy bins in accordance with a decomposition target material that is a material to be decomposed in a imaging region, allocate the first data group to any of the second energy bins so as to generate a second data group, and use the second data group to generate an image representing a distribution of the decomposition target material.
摘要翻译： 根据实施例的光子计数X射线CT装置包括：数据获取电路和处理电路。 数据采集电路被配置为响应于X射线光子对多个第一能量箱中的任何一个的入射而分配从光子计数检测器输出的信号测量的能量，以便获取第一数据组作为每个的计数数据 第一个能量箱。 处理电路被配置为确定通过根据在成像区域中要分解的材料的分解目标材料对第一能量箱进行分组而获得的多个第二能量箱，将第一数据组分配给任何第二能量 以生成第二数据组，并且使用第二数据组来生成表示分解目标材料的分布的图像。
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公开(公告)号：US20150084959A1
公开(公告)日：2015-03-26
申请号：US14548902
申请日：2014-11-20
CPC分类号： G09G5/006 , A61B5/055 , A61B5/7425 , A61B6/463 , A61B6/503 , A61B8/0883 , A61B8/463 , A61B2576/023 , G06T11/60 , G06T15/08 , G06T2210/41 , G09G2340/14 , G09G2380/08
摘要： A medical image diagnosis apparatus according to an embodiment includes a controller. The controller generates a plurality of candidates for a first cross-sectional image from three-dimensional image data obtained by taking images of a heart. The controller generates, from the three-dimensional image data, one or more second cross-sectional images each of which intersects the candidates for the first cross-sectional image. The controller displays in parallel on a display, the candidates for the first cross-sectional image, as well as the second cross-sectional images on each of which information is superimposed. The information indicates positional relationships between the candidates for the first cross-sectional image and the second cross-sectional image.
摘要翻译： 根据实施例的医学图像诊断装置包括控制器。 控制器通过拍摄心脏图像获得的三维图像数据产生用于第一横截面图像的多个候选。 所述控制器从所述三维图像数据生成与所述第一横截面图像的候选物相交的一个或多个第二横截面图像。 控制器在显示器上平行显示，第一横截面图像的候选以及每个信息叠加的第二横截面图像。 该信息表示第一横截面图像和第二横截面图像的候选者之间的位置关系。
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公开(公告)号：US20240289635A1
公开(公告)日：2024-08-29
申请号：US18484949
申请日：2023-10-11
IPC分类号： G06N3/098
CPC分类号： G06N3/098
摘要： According to one embodiment, a learning system includes a plurality of local devices and a server. The plurality of local devices each includes processing circuitry configured to determine a federated local training condition indicating a training condition in federated learning of a local model based on preliminary local training information including a preliminary local training condition and a preliminary local training result in a case where a model is preliminarily trained using local data. The server includes processing circuitry configured to determine a global training condition of a global model based on the preliminary local training information.
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公开(公告)号：US20240005172A1
公开(公告)日：2024-01-04
申请号：US18169598
申请日：2023-02-15
发明人： Shuhei NITTA , Ryusuke HIRAI , Yoshiyuki KOKOJIMA
IPC分类号： G06N3/098
CPC分类号： G06N3/098
摘要： According to one embodiment, a learning system includes a plurality of local devices and a server. Each of the local devices includes a processor. The processor selects a mini-batch from local data. The processor trains a local model using the mini-batch. The processor generates local data information relating to the local data included in the mini-batch and indicating information different from a label. The processor transmits a local model parameter relating to the local model and the local data information to the server. The server includes a processor. The processor calculates an integrated parameter using the local data information acquired from each of the local devices. The processor updates a global model using the integrated parameter and the local model parameter acquired from each of the local devices.
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公开(公告)号：US20230090616A1
公开(公告)日：2023-03-23
申请号：US17652118
申请日：2022-02-23
发明人： Shuhei NITTA , Atsushi YAGUCHI , Akiyuki TANIZAWA
IPC分类号： G06N20/00
摘要： According to one embodiment, a learning system includes a plurality of local devices and a server. Each of the local devices includes a processor. The processor of the local device selects a first parameter set from a plurality of parameters related to the local model, and transmits the first parameter set to the server. At least one of the local devices is different from other local devices in a size of the local model in accordance with a resolution of input data. The server comprises a processor. The processor of the server integrates first parameter sets acquired from the local devices and update a global model. The processor of the server transmits the second parameter set to a local device that has transmitted the corresponding first parameter set.
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公开(公告)号：US20210060768A1
公开(公告)日：2021-03-04
申请号：US16799955
申请日：2020-02-25
发明人： Shuhei NITTA , Atsushi Yaguchi , Yukinobu Sakata , Akiyuki Tanizawa , Yasutoyo Takeyama , Tomoki Watanabe
摘要： A robot system according to an embodiment includes one or more processors. The processors acquire first input data predetermined as data affecting an operation of a robot. The processors calculate a calculation cost of inference processing using a machine learning model for inferring control data used for controlling the robot, on the basis of the first input data. The processors infer the control data by the machine learning model set according to the calculation cost. The processors control the robot using the inferred control data.
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公开(公告)号：US20150185302A1
公开(公告)日：2015-07-02
申请号：US14579532
申请日：2014-12-22
IPC分类号： G01R33/48
CPC分类号： G01R33/546
摘要： A magnetic resonance imaging apparatus according to an embodiment includes a processor and a memory. The memory stores processor-executable instructions that cause the processor to detect cross-sectional positions of a plurality of cross-sectional images to be acquired in an imaging scan from volume data; acquire the cross-sectional images in sequence based on the cross-sectional positions by executing the imaging scan; and after the first cross-sectional image is acquired in the imaging scan, generate a display image, and display the display image on a display, the display image being an image in which a cross-sectional position of a second cross-sectional image which is detected from the volume data is superimposed on the first cross-sectional image, the second cross-sectional image being a cross-sectional image before being acquired and intersecting with the first cross-sectional image.
摘要翻译： 根据实施例的磁共振成像装置包括处理器和存储器。 存储器存储处理器可执行指令，其使得处理器检测要从体积数据在成像扫描中获取的多个横截面图像的横截面位置; 通过执行成像扫描，基于横截面位置顺序获取截面图像; 并且在成像扫描中获取第一横截面图像之后，生成显示图像，并将显示图像显示在显示器上，所述显示图像是图像的第二横截面图像的横截面位置 从所述体积数据中检测到的所述第一截面图像被叠加在所述第一横截面图像上，所述第二横截面图像是被获取之前的横截面图像并且与所述第一横截面图像相交。
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9.发明申请公开(公告)号：US20230022566A1
公开(公告)日：2023-01-26
申请号：US17680984
申请日：2022-02-25
发明人： Yasutaka FURUSHO , Yukinobu SAKATA , Shuhei NITTA
IPC分类号： G06N3/08
摘要： According to one embodiment, a machine learning apparatus includes a processing circuit. The processing circuit trains a first learning: parameter of an extraction layer configured to extract feature data of the input data, based on a plurality of training data. The processing circuit trains a second learning parameter of a reconstruction layer configured to generate reconstructed data of the input data, based on a plurality of training feature data obtained by applying the trained extraction layer to the plurality of training data. The second learning parameter represents representative vectors as many as a dimension count of the feature data. The representative vectors as many as the dimension count are based on a weighted sum of the plurality of training data.
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公开(公告)号：US20200342266A1
公开(公告)日：2020-10-29
申请号：US16798543
申请日：2020-02-24
发明人： Shuhei NITTA
摘要： A data generation device includes one or more processors. The processors input input data into a neural network and obtain an inference result of the neural network The processors calculate a first loss and a second loss. The first loss becomes smaller in value as a degree of matching between the inference result and a target label becomes larger. The target label indicates a correct answer of the inference. The second loss is a loss based on a contribution degree to the inference result of a plurality of elements included in the input data and the target label. The processors update the input data based on the first loss and the second loss.
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