公开(公告)号：US20230177678A1

公开(公告)日：2023-06-08

申请号：US17806402

申请日：2022-06-10

Applicant: Tata Consultancy Services Limited

Inventor： MANU SHEORAN ,  MEGHAL DANI ,  MONIKA SHARMA ,  LOVEKESH VIG

IPC: G06T7/00 ,  G06V10/25 ,  G06V10/26 ,  G06V10/778 ,  G06V10/44

CPC classification number: G06T7/0012 ,  G06V10/25 ,  G06V10/26 ,  G06V10/778 ,  G06V10/454 ,  G06T2207/10081 ,  G06T2207/30096 ,  G06V2201/07 ,  G06V2201/032

Abstract: State of the art deep network based Universal Lesion Detection (ULD) techniques inherently depend on large number of datasets for training the systems. Moreover, these system are specifically trained for lesion detection in organs of a Region of interest (RoI) of a body. Thus, requires retraining when the RoI varies. Embodiments herein disclose a method and system for domain knowledge augmented multi-head attention based robust universal lesion detection. The method utilizes minimal number of Computer Tomography (CT) scan slices to extract maximum information using organ agnostic HU windows and a convolution augmented attention module for a computationally efficient ULD with enhanced prediction performance.

公开(公告)号：US20240331868A1

公开(公告)日：2024-10-03

申请号：US18573998

申请日：2022-06-22

Applicant: ANKON TECHNOLOGIES CO., LTD ,  ANX IP HOLDING PTE. LTD.

Inventor： Chukang ZHANG ,  Zhiwei HUANG ,  Hao ZHANG ,  Fanhua MING

IPC: G16H50/30 ,  G06T7/00 ,  G06V10/74 ,  G16H50/70

CPC classification number: G16H50/30 ,  G06T7/0012 ,  G06V10/74 ,  G16H50/70 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30092 ,  G06V2201/032

Abstract: The present invention provides a deep learning-based cancer prognosis survival prediction method and a device, and a storage medium. The method includes: data acquisition: acquiring sample data, where the sample data comprising pathological image data and clinical data of a sample; data preprocessing; prediction model training: training and evaluating a prediction model to obtain an optimal prediction model; and risk prediction: performing risk prediction on a new sample on the basis of an optimal classifier model and the optimal prediction model. In the method, data features of the pathological image data and clinical data are unified, the prediction model is trained and evaluated to obtain the optimal prediction model, and prognosis risk evaluation is performed on the new sample to enhance the efficiency of diagnosis and treatment in the clinical field and improve the accuracy of risk evaluation results.

公开(公告)号：US12082687B2

公开(公告)日：2024-09-10

申请号：US17257616

申请日：2019-07-10

Applicant: PLAQLESS LTD

Inventor： Yuval Shani ,  Tamir Ygal

IPC: A46B15/00 ,  A46B5/00 ,  A61B1/00 ,  A61B1/06 ,  A61B1/24 ,  A61B5/00 ,  A61C9/00 ,  G06F18/214 ,  G06T7/00 ,  G06T7/529 ,  A61C17/22

CPC classification number: A46B5/0095 ,  A46B15/0034 ,  A46B15/0038 ,  A61B1/00011 ,  A61B1/06 ,  A61B1/24 ,  A61B5/0022 ,  A61B5/0088 ,  A61B5/4547 ,  A61C9/0053 ,  G06F18/214 ,  G06T7/0012 ,  G06T7/529 ,  A46B2200/01 ,  A46B2200/1066 ,  A61C17/22 ,  G06T2207/20081 ,  G06T2207/30036 ,  G06V2201/032

Abstract: The present invention relates to an apparatus comprising an insertion member configured to be inserted to a user's mouth. The insertion member comprises one or more illumination sources, configured to illuminate a part of the user's mouth when inserted thereinto; one or more imaging devices configured to capture images of the user's mouth interior; and a processing module configured to receive images from the one or more imaging devices, process the images to data, and detect oral and/or dental anomalies from the processed images and send the processed images and data via wireless or wired connection to a physician or professional doctor for further analysis.

公开(公告)号：US20240257344A1

公开(公告)日：2024-08-01

申请号：US18520048

申请日：2023-11-27

Applicant: Fuel 3D Technologies Limited

Inventor： Chris Kane ,  Leonardo Rubio Navarro ,  Adeala Zabair ,  Anna Chabokdast ,  James Klatzow

IPC: G06T7/00 ,  A61B5/00 ,  G06F18/2431 ,  G06T3/40 ,  G06T7/11 ,  G06T7/12 ,  G06T7/174 ,  G06T7/187 ,  G06T7/40 ,  G06T7/50 ,  G06T7/62 ,  G06T7/64 ,  G06T19/20

CPC classification number: G06T7/0012 ,  A61B5/004 ,  A61B5/444 ,  A61B5/7264 ,  G06F18/2431 ,  G06T3/40 ,  G06T7/11 ,  G06T7/12 ,  G06T7/187 ,  G06T7/40 ,  G06T7/50 ,  G06T7/62 ,  G06T7/64 ,  G06T19/20 ,  A61B2503/40 ,  G06T7/174 ,  G06T2207/10048 ,  G06T2207/20084 ,  G06T2207/30088 ,  G06T2207/30096 ,  G06T2219/2021 ,  G06V2201/03 ,  G06V2201/032

Abstract: A method is proposed for identifying (“segmenting”) at least one portion of the skin of an animal which is a region of interest (e.g. a portion which is subject to an abnormality such as a tumor). The method uses at least a temperature dataset obtained by measuring the temperature of each of a plurality of points of a region of the skin. An initial segmentation may be performed using the temperature data based on a statistical model, in which each point is segmented based on its temperature and optionally that of its neighbors. The initial segmentation based on the temperature data may be improved using a three-dimensional model of the profile of the skin, and the enhanced segmentation may be used to improve the three-dimensional model.

公开(公告)号：US12039724B2

公开(公告)日：2024-07-16

申请号：US17545383

申请日：2021-12-08

Applicant: IMIDEX, INC.

Inventor： Richard Vlasimsky

IPC: G06T7/00 ,  A61B6/00 ,  A61B6/50 ,  G06N3/045 ,  G06T3/40 ,  G06T7/11 ,  G06V10/764 ,  G06V10/82 ,  G16H30/40 ,  G16H50/20

CPC classification number: G06T7/0012 ,  A61B6/50 ,  A61B6/5217 ,  G06N3/045 ,  G06T3/40 ,  G06T7/11 ,  G06V10/764 ,  G06V10/82 ,  G16H30/40 ,  G16H50/20 ,  G06T2207/10116 ,  G06T2207/20076 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30061 ,  G06T2207/30096 ,  G06T2207/30168 ,  G06V2201/032

Abstract: The present invention provides systems and methods for analyzing chronic pulmonary diseases, such as lung cancer, using machine learning (ML) systems that detect lung nodules in chest x-rays. The methods and systems of the invention allows for the detection of lung abnormalities in chest x-ray images using at least two neural networks.

公开(公告)号：US12026935B2

公开(公告)日：2024-07-02

申请号：US17569205

申请日：2022-01-05

Applicant: OLYMPUS CORPORATION

Inventor： Jun Ando

IPC: G06V10/774 ,  G06N3/045 ,  G06V10/764 ,  G06V10/776 ,  G06V10/82 ,  G06V10/98 ,  G16H30/40

CPC classification number: G06V10/774 ,  G06N3/045 ,  G06V10/764 ,  G06V10/776 ,  G06V10/82 ,  G06V10/98 ,  G16H30/40 ,  G06V2201/032

Abstract: An image processing method includes generating a first augmented image by applying first data augmentation on an input image, generating a second augmented image by applying second data augmentation on the input image, generating a first output by inputting the first augmented image to a neural network, generating a second output by inputting the second augmented image to the neural network, calculating an output difference indicating a degree of difference between the first output and the second output, and updating a weight coefficient of each layer of the neural network based on the output difference.

公开(公告)号：US11992357B2

公开(公告)日：2024-05-28

申请号：US17709799

申请日：2022-03-31

Applicant: Jianqiang Liu ,  Manat Maolinbay ,  Chwen-yuan Ku ,  Linbo Yang

Inventor： Jianqiang Liu ,  Manat Maolinbay ,  Chwen-yuan Ku ,  Linbo Yang

IPC: A61B6/00 ,  A61B6/02 ,  A61B6/03 ,  A61B6/04 ,  A61B6/06 ,  A61B6/08 ,  A61B6/40 ,  A61B6/42 ,  A61B6/46 ,  A61B6/58 ,  G01N23/044 ,  G01N23/083 ,  G01N23/18 ,  G06T7/00 ,  G06T7/11 ,  G06T11/00 ,  G06T17/00 ,  G06V10/25 ,  G06V10/62 ,  G16H10/60 ,  G16H30/20 ,  G16H50/20 ,  A61B6/50

CPC classification number: A61B6/541 ,  A61B6/025 ,  A61B6/032 ,  A61B6/035 ,  A61B6/0407 ,  A61B6/06 ,  A61B6/08 ,  A61B6/4007 ,  A61B6/4014 ,  A61B6/4021 ,  A61B6/405 ,  A61B6/4208 ,  A61B6/4283 ,  A61B6/4405 ,  A61B6/4441 ,  A61B6/4452 ,  A61B6/4476 ,  A61B6/4482 ,  A61B6/467 ,  A61B6/482 ,  A61B6/54 ,  A61B6/542 ,  A61B6/56 ,  A61B6/583 ,  G01N23/044 ,  G01N23/083 ,  G01N23/18 ,  G06T7/0012 ,  G06T7/0016 ,  G06T7/11 ,  G06T11/003 ,  G06T11/006 ,  G06T17/00 ,  G06V10/25 ,  G06V10/62 ,  G16H10/60 ,  G16H30/20 ,  G16H50/20 ,  A61B6/4275 ,  A61B6/502 ,  G01N2223/401 ,  G06T2200/24 ,  G06T2207/10076 ,  G06T2207/10081 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30064 ,  G06T2207/30096 ,  G06T2207/30168 ,  G06T2210/41 ,  G06V2201/032

Abstract: A transport system with curved track pair is constructed for multiple pulsed X-ray source-in-motion to perform fast digital tomosynthesis imaging. It includes a curved rigid track pair with predetermined curvature, a primary motor stage car loaded with X-ray sources and wheels loaded with tension or compression springs. The car is driven by primary motor mounted at base frame and an engaged gear mounted at the car. The car can carry heavy loads, travel with high precision and high repeatability at all installation orientations while motion vibration is minimal. It is also scalable to have a larger radius. Track angle span usually can be from about ten degrees to about 170 degrees. During imaging acquisition, X-ray sources can sweep precisely from one location to another. The car has enough clearance to move in its path without rubbing wheels on tracks. Better than 0.2 mm overall spatial precision can be achieved with the digital tomosynthesis imaging.

公开(公告)号：US11883186B2

公开(公告)日：2024-01-30

申请号：US17432925

申请日：2020-03-06

Applicant: San Diego State University (SDSU) Foundation ,  BLUE RESONANCE, LLC

Inventor： Edward Riley ,  Ganapathy Chockalingam

IPC: A61B5/00 ,  A61B5/107 ,  G06T7/00 ,  G06V10/25 ,  G06V40/16 ,  G16H30/20 ,  G16H50/20 ,  G16H50/50 ,  G16H30/40 ,  G06T19/00

CPC classification number: A61B5/4362 ,  A61B5/004 ,  A61B5/1079 ,  A61B5/7485 ,  G06T7/0012 ,  G06T19/006 ,  G06V10/25 ,  G06V40/165 ,  G06V40/171 ,  G16H30/20 ,  G16H50/20 ,  G16H50/50 ,  G06T2207/10016 ,  G06T2207/10028 ,  G06T2207/20081 ,  G06T2207/20092 ,  G06T2207/30201 ,  G06V2201/032 ,  G06V2201/07

Abstract: Computer-assisted methods for assisting in anomaly identification relating to a dysmorphology analysis comprise retrieving and/or generating a sequence of progressively changing images that depict morphing of at least a subject's first physical feature, between at least a first state representing an identification of a first anomaly relating to a dysmorphology and a second state representing lack of the identification of the first anomaly. The number of images in the sequence is selected to provide a substantially continuous transition between the first and second states. The retrieved and/or generated images are displayed on a display of a processing device, and a user interface on the processing device is provided for a user to make an image selection, which can then be used to determine identification or lack of identification of the anomaly.

公开(公告)号：US11869182B2

公开(公告)日：2024-01-09

申请号：US17252217

申请日：2019-06-14

Applicant: Fuel 3D Technologies Limited

Inventor： Chris Kane ,  Leonardo Rubio Navarro ,  Adeala Zabair ,  Anna Chabokdast ,  James Klatzow

IPC: G06T7/00 ,  G06T7/11 ,  G06T7/12 ,  G06T7/174 ,  G06T7/187 ,  G06T7/64 ,  G06T7/62 ,  G06T7/50 ,  A61B5/00 ,  G06T3/40 ,  G06T7/40 ,  G06T19/20 ,  G06F18/2431

CPC classification number: G06T7/0012 ,  A61B5/004 ,  A61B5/444 ,  A61B5/7264 ,  G06F18/2431 ,  G06T3/40 ,  G06T7/11 ,  G06T7/12 ,  G06T7/187 ,  G06T7/40 ,  G06T7/50 ,  G06T7/62 ,  G06T7/64 ,  G06T19/20 ,  A61B2503/40 ,  G06T7/174 ,  G06T2207/10048 ,  G06T2207/20084 ,  G06T2207/30088 ,  G06T2207/30096 ,  G06T2219/2021 ,  G06V2201/03 ,  G06V2201/032

Abstract: A method is proposed for identifying (“segmenting”) at least one portion of the skin of an animal which is a region of interest (e.g. a portion which is subject to an abnormality such as a tumor). The method uses at least a temperature dataset obtained by measuring the temperature of each of a plurality of points of a region of the skin. An initial segmentation may be performed using the temperature data based on a statistical model, in which each point is segmented based on its temperature and optionally that of its neighbors. The initial segmentation based on the temperature data may be improved using a three-dimensional model of the profile of the skin, and the enhanced segmentation may be used to improve the three-dimensional model.

公开(公告)号：US20230377149A1

公开(公告)日：2023-11-23

申请号：US18366628

申请日：2023-08-07

Applicant: FUJIFILM Corporation

Inventor： Yuta HIASA

IPC: G06T7/00 ,  G06T7/11 ,  G06T7/70 ,  G06V10/25 ,  G06V20/70 ,  G06V10/774 ,  G06V10/776

CPC classification number: G06T7/0012 ,  G06T7/11 ,  G06T7/70 ,  G06V10/25 ,  G06V20/70 ,  G06V10/774 ,  G06V10/776 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30096 ,  G06T2207/10116 ,  G06V2201/032 ,  G06V2201/031 ,  G06T2207/30101 ,  G06T2207/30061 ,  G06T2207/30048

Abstract: Provided are a learning apparatus, a learning method, a trained model, and a program capable of efficiently performing learning for disease detection with high accuracy while suppressing a cost. A learning apparatus (100) includes a processor (129), a memory (114) that stores a data set of a medical image and lesion information included in the medical image, and a learning model (126) with an attention mechanism (128) that estimates a disease from an input medical image. The processor performs processing of specifying a position of a region of interest indicated by an attention map (208) in organ labeling information (206), and outputting a specification result (210), processing of calculating an error by comparing an estimation result (212) with lesion information (204), processing of setting the error on the basis of the specification result (210), and processing of causing the learning model (126) to perform learning by using the set error.