公开(公告)号：EP4428812A1

公开(公告)日：2024-09-11

申请号：EP24158147.9

申请日：2024-02-16

申请人： SCREEN Holdings Co., Ltd. ,  Cyfuse Biomedical K. K.

发明人： HASEBE, Ryo ,  MAEKAWA, Toshihiko ,  INOUE, Ayu

IPC分类号： G06T7/00

CPC分类号： G06T7/0012 ,  G06T2207/1010120130101 ,  G06T2207/2008120130101 ,  G06T2207/3002420130101 ,  G06T2207/3005620130101

摘要： According to this evaluation method, first, spheroids obtained by three-dimensional culture of multiple kinds of liver-derived cells are imaged by optical coherence photography (image acquisition step), a localization region is extracted from the photographic image (region extraction step), the localization region is analyzed (analysis step), and the condition of the spheroid is evaluated (evaluation step). The analysis step includes a first calculation step (S41) of calculating the area of the entire spheroid in the photographic image, a second calculation step (S42) of calculating the area of the localization region, a third calculation step (S43) of calculating the ratio of the localization region on the basis of the two areas, and a fourth calculation step (S44) of calculating an evaluation parameter on the basis of the ratio. With the use of this evaluation parameter, there is provided an evaluation method that makes it possible to noninvasively observe a localization region of a spheroid used in a bio 3D printer and evaluate the condition of the spheroid without processing cells by staining or the like.

公开(公告)号：EP4386669A1

公开(公告)日：2024-06-19

申请号：EP22212885.2

申请日：2022-12-12

申请人： Koninklijke Philips N.V.

发明人： PEZZOTTI, Nicola ,  NIELSEN, Tim ,  GESSERT, Nils Thorben

IPC分类号： G06T7/20 ,  G06T5/00

CPC分类号： G06T7/20 ,  G06T2207/2020120130101 ,  G06T2207/1001620130101 ,  G06T2207/1007220130101 ,  G06T2207/1013220130101 ,  G06T2207/2008420130101 ,  G06T2207/2008120130101 ,  G06T2207/3005620130101 ,  G06T5/73

摘要： A computer-implemented method for registration of image data comprising a plurality of voxels relating to an image coordinate and a time point; the method comprising optimizing a parametric function by optimizing an optimization term, wherein the optimization term comprises a difference between the voxel value at a first image coordinate and at a first time point corresponding to a first image frame, and the voxel value at a second image coordinate, obtained by adding a motion vector to the first image coordinate, at a second time point corresponding to a second image frame, wherein the added motion vector is the output of the parametric function when inputting the first image coordinate, and wherein the parametric function is optimized by calculating the optimization term for a plurality of voxels at the first and second time points and iteratively adapting the parametric function.

公开(公告)号：EP4428811A1

公开(公告)日：2024-09-11

申请号：EP24154633.2

申请日：2024-01-30

申请人： SCREEN Holdings Co., Ltd. ,  Cyfuse Biomedical K. K.

发明人： HASEBE, Ryo ,  MAEKAWA, Toshihiko ,  INOUE, Ayu

IPC分类号： G06T7/00 ,  G06T7/12 ,  G06T7/136 ,  G06T7/62

CPC分类号： G06T7/0012 ,  G06T7/12 ,  G06T7/136 ,  G06T7/62 ,  G06T2207/1010120130101 ,  G06T2207/2008420130101 ,  G06T2207/2022420130101 ,  G06T2207/3002420130101 ,  G06T2207/3005620130101

摘要： According to an evaluation method, first, a biological sample is taken an image, and an image in which intensity values are distributed is acquired. After that, a localization region corresponding to a fibrotic region is extracted from the taken image. At that time, a region of which intensity value satisfies a predetermined requirement in the taken image is extracted as the localization region. Alternatively, the taken image is input to a trained model created in advance, and a localization region output from the trained model is obtained. This makes it possible to noninvasively observe the fibrotic region of the biological sample, to evaluate the condition of the biological sample, without processing cells by staining or the like.

公开(公告)号：EP3961484B1

公开(公告)日：2024-07-17

申请号：EP20793969.5

申请日：2020-03-27

IPC分类号： G06V10/42 ,  G06V10/82 ,  G06V10/44 ,  G06V10/80 ,  G06T7/11 ,  G06T7/174

CPC分类号： G06T7/11 ,  G06T7/174 ,  G06T2207/1008120130101 ,  G06T2207/1008820130101 ,  G06T2207/2001620130101 ,  G06T2207/2002120130101 ,  G06T2207/2008120130101 ,  G06T2207/2008420130101 ,  G06T2207/2022120130101 ,  G06T2207/3005620130101 ,  G06V2201/03120220101 ,  G06V10/42 ,  G06V10/44 ,  G06V10/82 ,  G06V10/811 ,  G06N3/08 ,  G06N3/045

公开(公告)号：EP3646240B1

公开(公告)日：2024-09-04

申请号：EP18824396.8

申请日：2018-06-26

IPC分类号： G06T7/11 ,  G06T7/00 ,  G06T7/187 ,  G06T7/194 ,  G06N3/082 ,  G06N20/20 ,  G06V10/44 ,  G06F18/2413 ,  G06F18/243 ,  G06F18/25 ,  G06N3/045 ,  G06N5/01 ,  G06N7/01 ,  G06V10/764 ,  G06V10/80

CPC分类号： G06T7/0012 ,  G06T7/194 ,  G06T7/11 ,  G06T7/187 ,  G06T2207/3009620130101 ,  G06T2207/1008120130101 ,  G06T2207/1008820130101 ,  G06T2207/2007620130101 ,  G06T2207/2010420130101 ,  G06T2207/2010120130101 ,  G06T2207/3005620130101 ,  G06T2207/2012820130101 ,  G06T2207/2008120130101 ,  G06T2207/2008420130101 ,  G06N20/20 ,  G06N3/082 ,  G06V10/454 ,  G06V2201/1020220101 ,  G06V2201/0320220101 ,  G06V10/764 ,  G06V10/809 ,  G06N5/01 ,  G06N7/01 ,  G06N3/048 ,  G06N3/045 ,  G06F18/2413 ,  G06F18/24323 ,  G06F18/254

公开(公告)号：EP3505070B1

公开(公告)日：2024-05-22

申请号：EP18248051.7

申请日：2018-12-27

IPC分类号： A61B8/00 ,  A61B8/08 ,  G06T7/10 ,  G06T7/00 ,  G06T7/12 ,  G16H50/30

CPC分类号： A61B8/463 ,  A61B8/5223 ,  G06T7/0012 ,  G06T2207/1013220130101 ,  G06T2207/3005620130101 ,  G06T2207/3008420130101 ,  G06T7/12 ,  G16H50/30

公开(公告)号：EP4428815A1

公开(公告)日：2024-09-11

申请号：EP23160524.7

申请日：2023-03-07

申请人： Koninklijke Philips N.V.

发明人： OKEL, Sanne Emmarentia

IPC分类号： G06T7/11

CPC分类号： G06T7/11 ,  G06T2207/1010420130101 ,  G06T2207/1010820130101 ,  G06T2207/2008120130101 ,  G06T2207/2008420130101 ,  G06T2207/2009220130101 ,  G06T2207/3005620130101 ,  G06T2207/3009620130101

摘要： An input data preprocessor (IDP) and related methods for facilitating image segmentation. The preprocessor may comprise an input port (IN) for receiving an input image to be segmented by an interactive machine learning based segmentor (SEG). A subset specifier (SS) determines, based on the input image, a size specification (b) for an in-image subset. An output interface (OUT) passes the size specification to a user interface (UI) for interaction with the segmentor (SEG). The proposed input data preprocessor (IDP) may preferably be used in interactive segmentation, to reduce the number of iteration cycles.

公开(公告)号：EP4387531A1

公开(公告)日：2024-06-26

申请号：EP22857185.7

申请日：2022-08-18

申请人： Sonic Incytes Medical Corp.

发明人： HONARVAR, Mohammad ,  SCHNEIDER, Caitlin Marie ,  LOBO, Julio Raul ,  STACHNIAK, Brian Peter

IPC分类号： A61B8/00 ,  G06N3/04 ,  G06N3/08 ,  G06T7/10 ,  G16H30/40

CPC分类号： A61B8/485 ,  A61B8/085 ,  A61B8/5223 ,  A61B8/463 ,  G06T7/0002 ,  G06T2207/3005620130101 ,  G06T2207/3016820130101 ,  G06T2207/2008420130101 ,  G06T2207/1013220130101 ,  G06T7/11

公开(公告)号：EP4379658A1

公开(公告)日：2024-06-05

申请号：EP23193684.0

申请日：2023-08-28

申请人： FUJITSU LIMITED

发明人： OKA, Ayaka ,  BABA, Takayuki ,  ISHIHARA, Masaki ,  KARASUDANI, Ayu ,  YAMAGUCHI, Tatsuya

IPC分类号： G06T7/11 ,  G06T7/00

CPC分类号： G06T2207/3009620130101 ,  G06T2207/3005620130101 ,  G06T7/11 ,  G06T2207/2008420130101 ,  G06T2207/1008120130101 ,  G06T2207/1008820130101 ,  G06T7/0012

摘要： An image processing method is executed by a computer and the method includes: extracting an organ region representing an organ and a tumor candidate region having a feature for identifying a tumor in the organ from image data obtained by capturing an image of the organ; generating a non-organ region representing a region where the organ is not present using the image data; and removing, from the extracted tumor candidate region, a tumor candidate region being present only at an outer edge portion of the non-organ region in the organ region.

公开(公告)号：EP4442196A1

公开(公告)日：2024-10-09

申请号：EP23213400.7

申请日：2023-11-30

申请人： Qi, Xiaolong

发明人： QI, Xiaolong ,  WANG, Chengyan ,  HUANG, Yifei

IPC分类号： A61B5/02 ,  G06T7/00 ,  G06T7/60 ,  G06V10/82 ,  G16H30/40 ,  G16H50/20 ,  G16H50/70 ,  G06T7/11 ,  G06V10/26 ,  G06V10/25 ,  G06V10/44

CPC分类号： Y02A90/10 ,  G06T7/0012 ,  G16H30/40 ,  A61B5/02007 ,  G06T7/60 ,  G06V10/82 ,  G16H50/20 ,  G16H50/70 ,  G06T2207/1008120130101 ,  G06T2207/1008820130101 ,  G06T2207/2008120130101 ,  G06T2207/3010120130101 ,  G06T2207/3005620130101 ,  G06T7/11 ,  G06T2207/2008420130101 ,  G06T2207/2007220130101 ,  G06T2207/3017620130101 ,  G06V10/454 ,  G06V10/26 ,  G06V10/25 ,  G06V2201/03120220101 ,  A61B5/021 ,  A61B5/4244 ,  A61B5/7267 ,  A61B5/004

摘要： The present disclosure relates to the technical field of medical diagnosis, and particularly provides cirrhotic portal hypertension diagnosing method, apparatus, device, and medium, which process an input MRI image or CT image using a trained liver vessel three-dimensional segmentation model, to obtain a liver contour image of a patient, wherein the liver contour image includes a portal vascular tree, a hepatic vein vascular tree, an aortic vascular tree, and an inferior vena cava vascular tree; automatically extract corresponding vascular geometric parameters from each vascular tree in the obtained liver contour image; process input vascular geometric parameters using the trained cirrhotic portal hypertension diagnostic model, to obtain a cirrhotic portal hypertension diagnosis result of the patient. Thus, the cirrhotic portal hypertension is diagnosed through the vascular geometric characteristics, so that on one hand, the diagnosis result is more accurate, and on the other hand, powerful pathophysiological explanations can be supplemented to a model result.