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Title:
AUTOMATIC SEGMENTATION PROCESS OF A 3D MEDICAL IMAGE BY ONE OR SEVERAL NEURAL NETWORKS THROUGH STRUCTURED CONVOLUTION ACCORDING TO THE ANATOMIC GEOMETRY OF THE 3D MEDICAL IMAGE
Document Type and Number:
WIPO Patent Application WO/2019/138001
Kind Code:
A1
Abstract:
This invention concerns an automatic segmentation method of a medical image making use of a knowledge database containing information about the anatomical and pathological structures or instruments, that can be seen in a 3D medical image of a x b x n dimension, i.e. composed of n different 2D images each of a x b dimension. Said method being characterised in that it mainly comprises three process steps, namely: a first step consisting in extracting from said medical image nine sub-images (1 to 9) of a/2 x b/2 x n dimensions, i.e. nine partially overlapping a/2 x b/2 sub-images from each 2D image; a second step consisting in nine convolutional neural networks (CNNs) analysing and segmenting each one of these nine sub-images (1 to 9) of each 2D image; a third step consisting in combining the results of the nine analyses and segmentations of the n different 2D images, and therefore of the nine segmented sub-images with a/2 x b/2 x n dimensions, into a single image with a x b x n dimension, corresponding to a single segmentation of the initial medical image.

Inventors:
SOLER LUC (FR)
THOME NICOLAS (FR)
HOSTETTLER ALEXANDRE (FR)
MARESCAUX JACQUES (FR)
Application Number:
PCT/EP2019/050553
Publication Date:
July 18, 2019
Filing Date:
January 10, 2019
Export Citation:
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Assignee:
INSTITUT DE RECH SUR LES CANCERS DE LAPPAREIL DIGESTIF IRCAD (FR)
VISIBLE PATIENT (FR)
CONSERVATOIRE NAT DES ARTS ET METIERS C N A M (FR)
International Classes:
G06T7/11; G06V10/764
Foreign References:
US20160110632A12016-04-21
US20150238148A12015-08-27
EP2685363A12014-01-15
US20160174902A12016-06-23
US20150206319A12015-07-23
Other References:
O. RONNEBERGER ET AL.: "MICCAI", 2015, SPRINGER IPS, pages: 234 - 241
Attorney, Agent or Firm:
CABINET NUSS (FR)
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