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1. WO2022117470 - MACHINE LEARNING OF EDGE RESTORATION FOLLOWING CONTRAST SUPPRESSION/MATERIAL SUBSTITUTION

Publication Number WO/2022/117470
Publication Date 09.06.2022
International Application No. PCT/EP2021/083264
International Filing Date 28.11.2021
IPC
G06T 7/00 2017.1
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
7Image analysis
G06T 5/00 2006.1
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
5Image enhancement or restoration
G06V 10/44 2022.1
G06V 10/82 2022.1
CPC
G06T 2207/10081
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
2207Indexing scheme for image analysis or image enhancement
10Image acquisition modality
10072Tomographic images
10081Computed x-ray tomography [CT]
G06T 2207/10088
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
2207Indexing scheme for image analysis or image enhancement
10Image acquisition modality
10072Tomographic images
10088Magnetic resonance imaging [MRI]
G06T 2207/20081
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
2207Indexing scheme for image analysis or image enhancement
20Special algorithmic details
20081Training; Learning
G06T 2207/20084
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
2207Indexing scheme for image analysis or image enhancement
20Special algorithmic details
20084Artificial neural networks [ANN]
G06T 2207/30028
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
2207Indexing scheme for image analysis or image enhancement
30Subject of image; Context of image processing
30004Biomedical image processing
30028Colon; Small intestine
G06T 2207/30101
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
2207Indexing scheme for image analysis or image enhancement
30Subject of image; Context of image processing
30004Biomedical image processing
30101Blood vessel; Artery; Vein; Vascular
Applicants
  • KONINKLIJKE PHILIPS N.V. [NL]/[NL]
Inventors
  • WIEMKER, Rafael
  • GOSHEN, Liran
  • CAROLUS RUPPERTSHOFEN, Heike
  • KLINDER, Tobias
Agents
  • PHILIPS INTELLECTUAL PROPERTY & STANDARDS
Priority Data
20211551.503.12.2020EP
Publication Language English (en)
Filing Language English (EN)
Designated States
Title
(EN) MACHINE LEARNING OF EDGE RESTORATION FOLLOWING CONTRAST SUPPRESSION/MATERIAL SUBSTITUTION
(FR) APPRENTISSAGE AUTOMATIQUE DE LA RESTAURATION DES BORDS À LA SUITE D’UNE SUPPRESSION DE CONTRASTE/SUBSTITUTION DE MATÉRIAU
Abstract
(EN) The present invention relates to edge restoration. In order to improve a restoration of the artificially created cleansed edges, an apparatus is proposed to automatically restore image edges after digital subtraction of digital material substitution to optimally resemble image edges in unmodified locations. The appearance of edges is machine-learned in an unsupervised non-analytical way from unmodified locations, and then, after digital suppression or digital material substitution, applied to the artificially created cleansed edges.
(FR) La présente invention concerne la restauration des bords. Afin d’améliorer une restauration des bords nettoyés créés artificiellement, il est proposé un appareil capable de restaurer automatiquement des bords d’image, après une soustraction numérique de substitution de matériau numérique, pour offrir une ressemblance optimale à des bords d’image situés dans des emplacements non modifiés. L’apparence des bords est apprise automatiquement d’une manière non analytique et non supervisée à partir d’emplacements non modifiés, puis, après une suppression numérique ou une substitution de matériau numérique, elle est appliquée aux bords nettoyés créés artificiellement.
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