公开(公告)号：US12272063B2

公开(公告)日：2025-04-08

申请号：US18807820

申请日：2024-08-16

Applicant: Median Technologies

Inventor： Benoit Huet ,  Pierre Baudot ,  Elias Munoz ,  Ezequiel Geremia ,  Jean-Christophe Brisset ,  Vladimir Groza

IPC: G06T7/00 ,  G06T7/11 ,  G06T7/62 ,  G06V10/26 ,  G06V10/764 ,  G06V10/77 ,  G06V10/774

Abstract: An apparatus and method for training and using a computing operation for digital image processing are provided. The apparatus and method may be used for 3-dimensional medical images. An exemplary method for digital image processing comprises: receiving an image displaying at least one detectable structure, determining the detectable structure; segmenting the image to obtain a segmentation mask that is associated with a geometric shape and comprises at least one quantifiable visual feature; generating a mesh based on the quantifiable visual feature; computing at least on quantifiable visual parameter based on the mesh; extracting quantifiable visual data from the image based on the quantifiable visual parameter; training the computing operation with the quantifiable visual data. The method for digital image processing further comprises: receiving another image; segmenting, generating a mesh, computing quantifiable visual parameters, and extracting quantifiable visual data; and classifying the extracted quantifiable visual data with the trained computing operation.

公开(公告)号：US11810299B1

公开(公告)日：2023-11-07

申请号：US18351699

申请日：2023-07-13

Applicant: MEDIAN TECHNOLOGIES

Inventor： Benoît Huet ,  Danny Francis ,  Pierre Baudot

IPC: G06T7/00 ,  G06V10/25 ,  G06V10/26 ,  G06V10/774 ,  G06V10/82 ,  G06T7/73 ,  G06V10/32 ,  G06V10/776 ,  G16H50/20

CPC classification number: G06T7/0012 ,  G06T7/73 ,  G06V10/25 ,  G06V10/26 ,  G06V10/32 ,  G06V10/774 ,  G06V10/776 ,  G06V10/82 ,  G16H50/20 ,  G06T2200/04 ,  G06T2207/10081 ,  G06T2207/10088 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30096 ,  G06V2201/03

Abstract: A method for generating a machine learning model for characterizing a plurality of Regions Of Interest ROIs based on a plurality of 3D medical images and an associated method for characterizing a Region Of Interest ROI based on at least one 3D medical image. The methods proposed here aim to provide complementary strategies to enable a classification of ROIs from 3D medical images which could take profit of the advantageous and complementarity of both 2D and 3D CNNs to improve the accuracy of the prediction. More precisely, the present disclosure proposes a 2D model that complements the 3D model so that the sensitivity/specificity of the diagnosis is improved by taking advantage of complementary notions.

公开(公告)号：US20240412363A1

公开(公告)日：2024-12-12

申请号：US18807820

申请日：2024-08-16

Applicant: Median Technologies

Inventor： Benoit Huet ,  Pierre Baudot ,  Elias Munoz ,  Ezequiel Geremia ,  Jean-Christophe Brisset ,  VIadimir Groza

IPC: G06T7/00 ,  G06T7/11 ,  G06T7/62 ,  G06V10/26 ,  G06V10/764 ,  G06V10/77 ,  G06V10/774

Abstract: An apparatus and method for training and using a computing operation for digital image processing are provided. The apparatus and method may be used for 3-dimensional medical images. An exemplary method for digital image processing comprises: receiving an image displaying at least one detectable structure, determining the detectable structure; segmenting the image to obtain a segmentation mask that is associated with a geometric shape and comprises at least one quantifiable visual feature; generating a mesh based on the quantifiable visual feature; computing at least on quantifiable visual parameter based on the mesh; extracting quantifiable visual data from the image based on the quantifiable visual parameter; training the computing operation with the quantifiable visual data. The method for digital image processing further comprises: receiving another image; segmenting, generating a mesh, computing quantifiable visual parameters, and extracting quantifiable visual data; and classifying the extracted quantifiable visual data with the trained computing operation.