公开(公告)号：US12125208B2

公开(公告)日：2024-10-22

申请号：US17446732

申请日：2021-09-02

Applicant: SIEMENS HEALTHINEERS AG

Inventor： Zhoubing Xu ,  Sasa Grbic ,  Dominik Neumann ,  Guillaume Chabin ,  Bruce Spottiswoode ,  Fei Gao ,  Günther Platsch

IPC: G06T7/11 ,  G06T7/00 ,  G06T7/187

CPC classification number: G06T7/11 ,  G06T7/0012 ,  G06T7/187 ,  G06T2207/10081 ,  G06T2207/10088 ,  G06T2207/10136 ,  G06T2207/20081 ,  G06T2207/30016 ,  G06T2207/30056 ,  G06T2207/30061 ,  G06T2207/30101

Abstract: The invention describes a method for automatically localizing organ segments in a three-dimensional image comprising the following steps: providing a three-dimensional image showing at least one organ and at least one tubular network comprising a plurality of tubular structures, the organ comprising organ segments; performing automatic separation of the organ from other parts of the image; performing automatic tracing of the tubular network to obtain a branch map; performing automatic analysis of the branch map to identify specific tubular structures; performing automatically assigning regions of the organ to the specific tubular structures to segment the organ into localized organ segments; and outputting the localized organ segments and the traced and analyzed tubular network as image data. The invention further describes a localization arrangement and a medical imaging system.

公开(公告)号：US20240233360A1

公开(公告)日：2024-07-11

申请号：US18617046

申请日：2024-03-26

Applicant: SINOSTEEL MAANSHAN GENERAL INSTITUTE OF MINING RESEARCH CO., LTD

Inventor： Wen NIE ,  Canming YUAN ,  Chuanhua XU ,  Bibo DAI ,  Junxing ZHU ,  Xuemin ZENG ,  Xiaogang WU ,  Xing WANG

IPC: G06V10/70 ,  G06T7/00 ,  G06T7/136 ,  G06T7/187 ,  G06V10/26 ,  G06V10/80

CPC classification number: G06V10/87 ,  G06T7/0002 ,  G06T7/136 ,  G06T7/187 ,  G06V10/267 ,  G06V10/80 ,  G06T2207/20004

Abstract: Provided are a method and a system for image batch processing recognition. Improved adaptive threshold segmentation, regional growth segmentation and global threshold segmentation methods are used to recognize red sandstone samples in a process of uniaxial compression failure in a certain area of Yunnan. In an embodiment, batch recognition times and relative errors of partial recognition images are calculated.

公开(公告)号：US20240220584A1

公开(公告)日：2024-07-04

申请号：US18501904

申请日：2023-11-03

Applicant: Illumina, Inc.

Inventor： Eric Jon OJARD ,  Abde Ali Hunaid KAGALWALLA ,  Rami MEHIO ,  Nitin UDPA ,  Gavin Derek PARNABY ,  John S. VIECELI

IPC: G06F18/2411 ,  G06F18/2135 ,  G06T7/187 ,  G06V10/50

CPC classification number: G06F18/2411 ,  G06F18/21355 ,  G06T7/187 ,  G06V10/507

Abstract: The technology disclosed corrects inter-cluster intensity profile variation for improved base calling on a cluster-by-cluster basis. The technology disclosed accesses current intensity data and historic intensity data of a target cluster, where the current intensity data is for a current sequencing cycle and the historic intensity data is for one or more preceding sequencing cycles. A first accumulated intensity correction parameter is determined by accumulating distribution intensities measured for the target cluster at the current and preceding sequencing cycles. A second accumulated intensity correction parameter is determined by accumulating intensity errors measured for the target cluster at the current and preceding sequencing cycles. Based on the first and second accumulated intensity correction parameters, next intensity data for a next sequencing cycle is corrected to generate corrected next intensity data, which is used to base call the target cluster at the next sequencing cycle.

公开(公告)号：US12008740B2

公开(公告)日：2024-06-11

申请号：US17396568

申请日：2021-08-06

Applicant: Niantic, Inc.

Inventor： Carl Sebastian Toft ,  Daniyar Turmukhambetov ,  Gabriel J. Brostow

IPC: G06T5/80 ,  G06T3/00 ,  G06T7/187 ,  G06T7/50 ,  G06T7/73 ,  H04N5/262 ,  A63F13/216 ,  A63F13/65

CPC classification number: G06T5/80 ,  G06T3/00 ,  G06T7/187 ,  G06T7/50 ,  G06T7/74 ,  H04N5/2628 ,  A63F13/216 ,  A63F13/65 ,  A63F2300/69 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30244

Abstract: An image localization system receives an image of a scene and generates a depth map for the image by inputting the image to a model trained for generating depth maps for images. The system determines surface normal vectors for the pixels in the depth map. The system clusters the surface normal vectors to identify regions in the image corresponding to planar surfaces. The system partitions the image into patches, each of which is a region of connected pixels in the image and corresponds to a cluster of surface normal vectors. The system rectifies the perspective distortion of patches and extracts perspective corrected features from the rectified patches. The system matches the perspective corrected features of the image with perspective corrected features of other images for three-dimensional re-localization.

公开(公告)号：US11995835B2

公开(公告)日：2024-05-28

申请号：US17229980

申请日：2021-04-14

Applicant: Hitachi Systems, Ltd.

Inventor： Yuki Inoue ,  Hiroto Nagayoshi ,  Masato Nakamura

IPC: G06T7/00 ,  G06N5/04 ,  G06N20/00 ,  G06T7/11 ,  G06T7/136 ,  G06T7/187 ,  G06V10/25

CPC classification number: G06T7/11 ,  G06N5/04 ,  G06N20/00 ,  G06T7/136 ,  G06T7/187 ,  G06V10/25 ,  G06T2200/24 ,  G06T2207/20076 ,  G06T2207/20081

Abstract: A pixel-level object detection system that detects an object at a pixel level, includes: an imaging unit that acquires an inference image that is an image that captures a detection target; an area detection unit that detects an area including a detection target from the inference image; a detail detection unit that detects the detection target using only local information from the inference image; and a result integration processing unit that integrates an output of the area detection unit with an output of the detail detection unit to output a segmentation map indicating, as a probability map, which pixel in the image corresponds to the detection object.

公开(公告)号：US11972571B2

公开(公告)日：2024-04-30

申请号：US17497954

申请日：2021-10-10

Applicant: Infervision Medical Technology Co., Ltd.

Inventor： Enyou Liu ,  Shaokang Wang ,  Kuan Chen

IPC: G06T7/11 ,  G06F18/21 ,  G06F18/213 ,  G06F18/25 ,  G06N3/045 ,  G06T5/70 ,  G06T7/187 ,  G06T7/194

CPC classification number: G06T7/11 ,  G06F18/213 ,  G06F18/217 ,  G06F18/253 ,  G06N3/045 ,  G06T5/70 ,  G06T7/187 ,  G06T7/194 ,  G06T2207/20021 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/20212 ,  G06T2207/30101 ,  G06V2201/03

Abstract: The method for image segmentation includes: acquiring, according to an image to be segmented including a background, a mediastinum, an artery and a vein, a first segmentation result of the mediastinum, the artery, the vein and the background in a mediastinum region of the image to be segmented; acquiring, according to the image to be segmented, a second segmentation result of a blood vessel and the background in an epitaxial region of the image to be segmented; and acquiring, according to the first segmentation result and the second segmentation result, a segmentation result of the mediastinum, the artery, the vein and the background of the image to be segmented, so that the segmentation accuracy and the segmentation efficiency of the artery and the vein may be improved.

公开(公告)号：US11967082B2

公开(公告)日：2024-04-23

申请号：US17403959

申请日：2021-08-17

Applicant: NEUROPHET INC.

Inventor： Dong Hyeon Kim

IPC: G06T7/11 ,  G06T7/187 ,  G06T17/00

CPC classification number: G06T7/11 ,  G06T7/187 ,  G06T17/00 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30016

Abstract: Provided is a method, performed by a computer, for correcting a brain image by using a brain structure. The method comprises: a step for obtaining a head image including the brain of a subject; a step for dividing the head image into a plurality of regions on the basis of the brain structure; and a step for performing a correction on the plurality of regions by using a layer arrangement condition of the brain.

公开(公告)号：US11961227B2

公开(公告)日：2024-04-16

申请号：US17168884

申请日：2021-02-05

Applicant: Ping An Technology (Shenzhen) Co., Ltd.

Inventor： Yue Wang ,  Bin Lv ,  Chuanfeng Lv

IPC: G06T7/00 ,  A61B5/00 ,  A61B6/03 ,  G06F18/21 ,  G06F18/214 ,  G06F18/2415 ,  G06F18/25 ,  G06T7/11 ,  G06T7/136 ,  G06T7/187 ,  G06T7/73 ,  G06V10/764 ,  G06V10/774 ,  G06V10/776 ,  G06V10/80 ,  G06V10/82

CPC classification number: G06T7/0012 ,  A61B5/0066 ,  A61B5/4887 ,  A61B5/7267 ,  A61B5/7275 ,  A61B6/032 ,  G06F18/2148 ,  G06F18/217 ,  G06F18/2415 ,  G06F18/253 ,  G06T7/11 ,  G06T7/136 ,  G06T7/187 ,  G06T7/73 ,  G06V10/764 ,  G06V10/774 ,  G06V10/776 ,  G06V10/806 ,  G06V10/82 ,  G06T2207/20081 ,  G06T2207/30096 ,  G06V2201/03

Abstract: A method for detecting and locating a lesion in a medical image is provided. A target medical image of a lesion is obtained and input into a deep learning model to obtain a target sequence. A first feature map output from the last convolution layer in the deep learning model is extracted. A weight value of each network unit corresponding to each preset lesion type in a fully connected layer is extracted. For each preset lesion type, a fusion feature map is calculated according to the first feature map and the corresponding weight value and resampled to the size of the target medical image to generate a generic activation map. The maximum connected area in each generic activation map is determined, and a mark border surrounding the maximum connected area is created. A mark border corresponding to each preset lesion type is added to the target medical image.

公开(公告)号：US11948305B2

公开(公告)日：2024-04-02

申请号：US17342192

申请日：2021-06-08

Applicant: GE Precision Healthcare LLC

Inventor： Yingbin Nie ,  Zhoushe Zhao ,  Chen Zhang

IPC: G06T7/187 ,  G06T5/30 ,  G06T7/11 ,  G06T7/155

CPC classification number: G06T7/11 ,  G06T5/30 ,  G06T7/155 ,  G06T7/187 ,  G06T2207/10081 ,  G06T2207/20081 ,  G06T2207/20132 ,  G06T2207/20221 ,  G06T2207/30061 ,  G06T2207/30101

Abstract: The present disclosure relates to a method, a system, and a storage medium for segmenting a lung image. The method for segmenting a lung image comprises: obtaining medical image data containing a lung region; performing lung lobe segmentation on the medical image data to generate a plurality of lung lobe data subsets; generating updated lung image data based on one or a plurality of lung lobe data subsets in the plurality of lung lobe data subsets; and performing nidus segmentation on the updated lung image data to generate a segmentation image that identifies a pneumonia nidus.

公开(公告)号：US11887291B2

公开(公告)日：2024-01-30

申请号：US18112303

申请日：2023-02-21

Applicant: Mistras Group, Inc.

Inventor： Kelly Morris ,  Elliott Morris ,  John Musgrave

IPC: G06T7/00 ,  G06T7/187 ,  F16L55/26 ,  G06T5/00 ,  G06T11/60 ,  H04N23/70 ,  F16L101/30

CPC classification number: G06T7/0002 ,  F16L55/26 ,  G06T5/003 ,  G06T7/187 ,  G06T11/60 ,  H04N23/70 ,  F16L2101/30

Abstract: Systems and methods for generating and processing images captured while inspecting above-ground pipelines are disclosed. Embodiments may include a robotic crawler or other devices which carry imaging equipment and traverse a target pipe which are configured to capture image data simultaneously from a plurality of angles. Such systems may substantially reduce and in some cases overcome the need to take multiple traversals of a pipeline under inspection. Embodiments may also be directed toward control systems for such devices as well as image processing systems which process the multiple image sets to produce a composite imaging result.