公开(公告)号：WO2022241323A1

公开(公告)日：2022-11-17

申请号：PCT/US2022/029478

申请日：2022-05-16

Applicant: EDDA TECHNOLOGY, INC.

Inventor： ZANG, Xiaonan ,  WEI, Guo-Qing ,  LIANG, Cheng-Chung ,  FAN, Li ,  ZENG, Xiaolan ,  QIAN, Jianzhong

IPC: A61B90/00 ,  A61B1/313 ,  A61B1/00009 ,  A61B1/0005 ,  A61B1/00057 ,  A61B1/3132 ,  A61B2034/105 ,  A61B34/10 ,  G06T17/20 ,  G06T19/006 ,  G06T19/20 ,  G06T2207/10016 ,  G06T2207/10068 ,  G06T2207/20092 ,  G06T2207/30004 ,  G06T2210/41 ,  G06T2219/2004 ,  G06T2219/2016 ,  G06T7/344 ,  G06T7/50 ,  G06T7/75 ,  G06T7/80

Abstract: The present teaching relates to method, system, medium, and implementations for estimating 3D coordinate of a 3D virtual model. Two pairs of feature points are obtained. Each of the pairs includes a respective 2D feature point on an organ observed in a 2D image, acquired during a medical procedure, and a respective corresponding 3D feature point from a 3D virtual model, constructed for the organ prior to the procedure based on a plurality of images of the organ. The first and the second 3D feature points have different depths. A 3D coordinate of a 3D feature point is determined based on the pairs of feature points so that a projection of the 3D virtual model from the 3D coordinate substantially matches the organ observed in the 2D image.

公开(公告)号：WO2022001237A1

公开(公告)日：2022-01-06

申请号：PCT/CN2021/083154

申请日：2021-03-26

Applicant: 广州柏视医疗科技有限公司 ,  广州柏视数据科技有限公司

Inventor： 魏军 ,  朱德明 ,  谢培梁

IPC: G06T7/11 ,  G06T2207/10081 ,  G06T2207/10088 ,  G06T2207/30096 ,  G06T7/136 ,  G06T7/30 ,  G06T7/344 ,  G06V10/267

Abstract: 一种鼻咽癌原发肿瘤图像自动识别方法及系统，以被测者的CT三维图像为基础，辅以MR序列三维图像，构成了语义分割网络模型的一个多模态输入，实现在CT上的鼻咽癌原发肿瘤识别。结合CT三维图像与MR序列三维图像，能有效提高输入数据的质量，并学习到高分辨率图像的全局信息和细节信息，能有效提高语义分割网络模型的预测准确度和泛化能力，并具备输入端与输出端的灵活性，进而有效提高医疗工作者的工作效率。

公开(公告)号：WO2022241321A1

公开(公告)日：2022-11-17

申请号：PCT/US2022/029474

申请日：2022-05-16

Applicant: EDDA TECHNOLOGY, INC.

Inventor： ZANG, Xiaonan ,  WEI, Guo-Qing ,  LIANG, Cheng-Chung ,  FAN, Li ,  ZENG, Xiaolan ,  QIAN, Jianzhong

IPC: A61B90/00 ,  A61B1/313 ,  A61B1/00009 ,  A61B1/0005 ,  A61B1/00057 ,  A61B1/3132 ,  A61B2034/105 ,  A61B34/10 ,  G06T17/20 ,  G06T19/006 ,  G06T19/20 ,  G06T2207/10016 ,  G06T2207/10068 ,  G06T2207/20092 ,  G06T2207/30004 ,  G06T2210/41 ,  G06T2219/2004 ,  G06T2219/2016 ,  G06T7/344 ,  G06T7/50 ,  G06T7/75 ,  G06T7/80

Abstract: The present teaching relates to method, system, medium, and implementations for estimating 3D coordinate of a 3D virtual model. Two pairs of feature points are obtained. A first 3D coordinate of the first 3D feature point and a second 3D coordinate of the second 3D feature point are automatically determined based on the pairs of feature points so that a first distance between the determined first 3D coordinate and the determined second 3D coordinate equals to a second distance between a first actual 3D coordinate of the first 3D feature point and a second actual 3D coordinate of the second 3D feature point in the 3D virtual model.

公开(公告)号：WO2021252246A1

公开(公告)日：2021-12-16

申请号：PCT/US2021/035554

申请日：2021-06-02

Applicant: KLA CORPORATION

Inventor： BRAUER, Bjorn ,  JIN, Huan ,  LI, Xiaochun

IPC: H01L21/66 ,  G06T7/30 ,  G06T7/90 ,  G06K9/62 ,  G01N21/95 ,  G06T2207/10152 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30148 ,  G06T7/0004 ,  G06T7/001 ,  G06T7/32 ,  G06T7/344

Abstract: Methods and systems for determining one or more alignment parameters for use in a process performed on a specimen are provided. One method includes determining measures of similarity between images generated by an imaging system for corresponding locations in each of two or more pairs of dies on a specimen and performing cluster analysis based on the determined measures of similarity to identify the images that are most similar to each other and to assign different subsets of the images that are most similar to each other to different die clusters, respectively. The method also includes separately determining one or more alignment parameters for two or more of the different die clusters. The one or more alignment parameters are used for aligning images generated by the imaging system for the specimen or another specimen to a common reference.

公开(公告)号：WO2021087364A8

公开(公告)日：2021-05-06

申请号：PCT/US2020/058366

申请日：2020-10-30

Applicant: SKIA ,  KIM, Mincheol

Inventor： NA, Seungwon ,  EUN, Wonki ,  LEE, Jun, Woo ,  KWON, Hyuk ,  LEE, Jong, Myoung

IPC: G06T7/00 ,  G06T7/33 ,  G06T19/00 ,  G06T7/174 ,  A61B2017/00203 ,  A61B2017/00207 ,  A61B2034/105 ,  A61B2034/2048 ,  A61B2090/363 ,  A61B2090/365 ,  A61B2090/367 ,  A61B2090/372 ,  A61B2090/374 ,  A61B2090/3762 ,  A61B34/10 ,  A61B46/20 ,  A61B5/0077 ,  A61B90/36 ,  A61B90/37 ,  G06T15/08 ,  G06T19/006 ,  G06T19/20 ,  G06T2207/10072 ,  G06T2207/30088 ,  G06T2207/30204 ,  G06T2210/41 ,  G06T2219/2021 ,  G06T7/0012 ,  G06T7/344 ,  G16H10/60 ,  G16H30/20 ,  G16H30/40

Abstract: The present disclosure provides a method of medical procedure using augmented reality for superimposing a patient's medical images (e.g., CT or MRI) over a real-time camera view of the patient. Prior to the medical procedure, the patient's medical images are processed to generate a 3D model that represents a skin contour of the patient's body. The 3D model is further processed to generate a skin marker that comprises only selected portions of the 3D model. At the time of the medical procedure, 3D images of the patient's body are captured using a camera, which are then registered with the skin marker. Then, the patient's medical images can be superimposed over the real-time camera view that is presented to the person performing the medical procedure.

公开(公告)号：WO2022272166A1

公开(公告)日：2022-12-29

申请号：PCT/US2022/035130

申请日：2022-06-27

Applicant: INTRINSIC INNOVATION LLC

Inventor： VENKATARAMAN, Kartik ,  KALRA, Agastya ,  KADAMBI, Achuta ,  RASKAR, Ramesh

IPC: G06V10/145 ,  G06V10/24 ,  G06V10/774 ,  G06V10/82 ,  G06V20/64 ,  G06V10/26 ,  G06V10/74 ,  G02B27/288 ,  G06N3/08 ,  G06T17/00 ,  G06T2207/10028 ,  G06T2207/20081 ,  G06T2207/30108 ,  G06T7/344 ,  G06T7/50 ,  G06T7/75 ,  G06V10/761 ,  G06V20/653 ,  G06V2201/06 ,  G06V2201/12

Abstract: A system for collecting data for training a computer vision model for shape estimation includes: an imaging system configured to capture one or more images; and a processing system including a processor and memory storing instructions that, when executed by the processor, cause the processor to: receive one or more input images from the imaging system; estimate a pose of an object depicted in the one or more images; render a shape estimate from a 3-D model of the object posed in accordance with the pose of the object; and generate a data point of a training dataset, the data point including one or more images based on the one or more input images and a label corresponding to the one or more images, the label including the shape estimate.

公开(公告)号：WO2022237225A1

公开(公告)日：2022-11-17

申请号：PCT/CN2022/072166

申请日：2022-01-14

Applicant: 广东三姆森科技股份有限公司

Inventor： 颜昌亚 ,  卢少武 ,  周向东 ,  李振瀚 ,  唐小琦 ,  张庆祥 ,  陈英滔 ,  谭辉 ,  汤胜水 ,  郑晓泽

IPC: G06T7/33 ,  G06T7/62 ,  G06T7/66 ,  G06T7/73 ,  G06K9/62 ,  G06F18/22 ,  G06T2207/10028 ,  G06T7/344

Abstract: 一种针对具有平面基准但不完整的三维扫描点云的在线实时配准方法，包括S1：标准模型预处理，输入标准模型，得到标准模型中的平面图元集合以及每个图元的相关几何信息；S2：数据准备，输入三维扫描点云模型数据；标准模型文件；标准模型特征模板文件；S3：对三维扫描点云模型数据调用RANSAC形状识别算法识别出其中的平面图元；S4：为三维扫描的点云模型的每个平面图元，建立与标准模型中的所有平面图元配对列表；S5：根据平面图元，建立所有的三平面图元组；S6：通过在点云模型的三平面组合与标准模型中对应的所有可能的三平面组合之间进行配准计算，来获最优配准齐次坐标变换矩阵。本发明无须考虑所有点云数据的配准，只需考虑标准模型与实际点云模型中的平面特征进行识别和匹配；以此来减低搜索循环的次数，以到达加速的目标。

公开(公告)号：WO2021133700A1

公开(公告)日：2021-07-01

申请号：PCT/US2020/066286

申请日：2020-12-21

Applicant: ALIBABA GROUP HOLDING LIMITED

Inventor： YANG, Han

IPC: G06T7/00 ,  G06N3/08 ,  G06T2207/10072 ,  G06T7/0012 ,  G06T7/344 ,  G16H30/20

Abstract: Methods, devices and storage media for data processing are provided. One of the methods include: obtaining a target image, wherein the target image comprises at least one tubular image; determining a spatial distribution feature and an image feature of each of the at least one tubular image; obtaining, based on a tubular structure recognition model, at least one fusion feature respectively corresponding to the at least one tubular image by fusing the spatial distribution feature and the image feature of each of the at least one tubular image; and recognizing, based on the tubular structure recognition model and the at least one fusion feature respectively corresponding to the at least one tubular image, at least one tubular structure respectively corresponding to the at least one tubular image.

公开(公告)号：WO2022241319A1

公开(公告)日：2022-11-17

申请号：PCT/US2022/029469

申请日：2022-05-16

Applicant: EDDA TECHNOLOGY, INC.

Inventor： ZANG, Xiaonan ,  WEI, Guo-Qing ,  LIANG, Cheng-Chung ,  FAN, Li ,  ZENG, Xiaolan ,  QIAN, Jianzhong

IPC: A61B90/00 ,  A61B1/313 ,  A61B1/00009 ,  A61B1/0005 ,  A61B1/00057 ,  A61B1/3132 ,  A61B2034/105 ,  A61B34/10 ,  G06T17/20 ,  G06T19/006 ,  G06T19/20 ,  G06T2207/10016 ,  G06T2207/10068 ,  G06T2207/20092 ,  G06T2207/30004 ,  G06T2210/41 ,  G06T2219/2004 ,  G06T2219/2016 ,  G06T7/344 ,  G06T7/50 ,  G06T7/75 ,  G06T7/80

Abstract: The present teaching relates to method, system, medium, and implementations for fusing a 3D virtual model with a 2D image associated with an organ of a patient. A key-pose is determined as an approximate position and orientation of a medical instrument with respect to the patient's organ. Based on the key-pose, an overlay is generated on a 2D image of the patient's organ, acquired by the medical instrument, by projecting the 3D virtual model on to the 2D image. A pair of feature points includes a 2D feature point from the 2D image and a corresponding 3D feature point from the 3D virtual model. The 3D coordinate of the 3D feature point is determined based on the 2D coordinate of the 2D feature point. The depth of the 3D coordinate is on a line of sight of the 2D feature point.

公开(公告)号：WO2021258386A1

公开(公告)日：2021-12-30

申请号：PCT/CN2020/098306

申请日：2020-06-26

Applicant: INTEL CORPORATION ,  WANG, Shandong ,  KANG, Yangyuxuan ,  YAO, Anbang ,  LU, Ming ,  CHEN, Yurong

Inventor： WANG, Shandong ,  KANG, Yangyuxuan ,  YAO, Anbang ,  LU, Ming ,  CHEN, Yurong

IPC: G06T7/70 ,  G06T17/00 ,  G06T2207/10016 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30196 ,  G06T2207/30221 ,  G06T2207/30241 ,  G06T7/344 ,  G06T7/38

Abstract: Apparatus and methods for three-dimensional pose estimation are disclosed herein. An apparatus includes an image synchronizer (214) to synchronize a first image (114) generated by a first image capture device (104) and a second image (116) generated by a second image capture device (106), the first image (114) and the second image (116) including a subject (102); a two-dimensional pose detector (216) to predict first positions of keypoints of the subject (102) based on the first image (114) and by executing a first neural network model to generate first two-dimensional data and predict second positions of the keypoints based on the second image (116) and by executing the first neural network model to generate second two-dimensional data; and a three-dimensional pose calculator (218) to generate a three-dimensional graphical model (1100) representing a pose of the subject (102) in the first image (114) and the second image (116) based on the first two-dimensional data, the second two-dimensional data, and by executing a second neural network model.