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Extract from the Register of European Patents

EP About this file: EP4334900

EP4334900 - TRAINING A MACHINE LEARNING MODEL FOR SIMULATING IMAGES AT HIGHER DOSE OF CONTRAST AGENT IN MEDICAL IMAGING APPLICATIONS [Right-click to bookmark this link]
StatusRequest for examination was made
Status updated on  19.12.2025
Database last updated on 30.03.2026
FormerGrant of patent is intended
Status updated on  14.11.2025
FormerRequest for examination was made
Status updated on  09.02.2024
FormerThe international publication has been made
Status updated on  03.05.2023
Formerunknown
Status updated on  21.11.2022
Most recent event   Tooltip19.12.2025Deletion - Disapproval of the communication of intention to grant the patent by the applicant or resumption of examination proceedings by the EPO 
Applicant(s)For all designated states
Bracco Imaging S.p.A.
Via Egidio Folli 50
20134 Milano / IT
[2024/11]
Inventor(s)01 / VALBUSA, Giovanni
10010 Colleretto Giacosa (TO) / IT
02 / COLOMBO SERRA, Sonia
10010 Colleretto Giacosa (TO) / IT
03 / FRINGUELLO MINGO, Alberto
10010 Colleretto Giacosa (TO) / IT
04 / TEDOLDI, Fabio
10010 Colleretto Giacosa (TO) / IT
05 / BELLA, Davide
10010 Colleretto Giacosa (TO) / IT
 [2024/11]
Representative(s)Pezzoli, Ennio, et al
c/o Maccalli & Pezzoli S.r.l.
Via Settembrini 40
20124 Milano / IT
[2024/11]
Application number, filing date22801818.014.10.2022
[2024/11]
WO2022EP78668
Priority number, dateEP2021020301915.10.2021         Original published format: EP 21203019
[2024/11]
Filing languageEN
Procedural languageEN
PublicationType: A1 Application with search report
No.:WO2023062196
Date:20.04.2023
Language:EN
[2023/16]
Type: A1 Application with search report 
No.:EP4334900
Date:13.03.2024
Language:EN
The application published by WIPO in one of the EPO official languages on 20.04.2023 takes the place of the publication of the European patent application.
[2024/11]
Search report(s)International search report - published on:EP20.04.2023
ClassificationIPC:G06T11/00
[2024/11]
CPC:
G06N3/088 (EP,KR); G16H50/20 (KR); G06T7/0012 (US);
A61B6/481 (KR); G01R33/5601 (KR); G01R33/5608 (KR);
G06N3/0455 (EP,KR); G06N3/0464 (EP,KR); G06N3/0475 (EP,KR);
G06N3/094 (KR); G06T11/00 (EP,US); G16H30/40 (KR);
G16H50/50 (KR); G06N3/047 (EP); G06T2207/20081 (US);
G06T2207/20084 (US) (-)
Designated contracting statesAL,   AT,   BE,   BG,   CH,   CY,   CZ,   DE,   DK,   EE,   ES,   FI,   FR,   GB,   GR,   HR,   HU,   IE,   IS,   IT,   LI,   LT,   LU,   LV,   MC,   ME,   MK,   MT,   NL,   NO,   PL,   PT,   RO,   RS,   SE,   SI,   SK,   SM,   TR [2024/11]
TitleGerman:TRAINIEREN EINES MASCHINENLERNMODELLS ZUR SIMULATION VON BILDERN MIT HÖHERER KONTRASTMITTELDOSIS IN MEDIZINISCHEN BILDGEBUNGSANWENDUNGEN[2025/50]
English:TRAINING A MACHINE LEARNING MODEL FOR SIMULATING IMAGES AT HIGHER DOSE OF CONTRAST AGENT IN MEDICAL IMAGING APPLICATIONS[2024/11]
French:FORMATION D'UN MODÈLE D'APPRENTISSAGE MACHINE POUR SIMULER DES IMAGES À UNE DOSE PLUS ÉLEVÉE D'AGENT DE CONTRASTE DANS DES APPLICATIONS D'IMAGERIE MÉDICALE[2025/50]
Former [2024/11]TRAINIEREN EINES MASCHINENLERNMODELLS ZUR SIMULATION VON BILDERN BEI HÖHERER KONTRASTMITTELDOSIS IN MEDIZINISCHEN BILDGEBUNGSANWENDUNGEN
Former [2024/11]ENTRAÎNEMENT D'UN MODÈLE D'APPRENTISSAGE MACHINE POUR SIMULER DES IMAGES À UNE DOSE SUPÉRIEURE D'AGENT DE CONTRASTE DANS DES APPLICATIONS D'IMAGERIE MÉDICALE
Entry into regional phase06.12.2023National basic fee paid 
06.12.2023Designation fee(s) paid 
06.12.2023Examination fee paid 
Examination proceduredeletedCommunication of intention to grant the patent
06.12.2023Examination requested  [2024/11]
06.12.2023Date on which the examining division has become responsible
02.04.2024Amendment by applicant (claims and/or description)
14.11.2025Communication of intention to grant the patent
17.12.2025Disapproval of the communication of intention to grant the patent by the applicant or resumption of examination proceedings by the EPO
17.12.2025Observations by third parties
Fees paidRenewal fee
28.10.2024Renewal fee patent year 03
27.10.2025Renewal fee patent year 04
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Cited inInternational search[A] CN112470190  (SUBTLE MEDICAL INC et al.)
 [A] US2019108634  (ZAHARCHUK GREG et al.)
 [A]   ENHAO GONG ET AL: "Deep learning enables reduced gadolinium dose for contrast-enhanced brain MRI : Deep Learning Reduces Gadolinium Dose", JOURNAL OF MAGNETIC RESONANCE IMAGING, vol. 48, no. 2, 13 February 2018 (2018-02-13), US, pages 330 - 340, XP055656267, ISSN: 1053-1807, DOI: 10.1002/jmri.25970

DOI:   http://dx.doi.org/10.1002/jmri.25970
 [A]   DEY AYON: "Machine Learning Algorithms: A Review", INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND INFORMATION TECHNOLOGIES, vol. 7, no. 3, 3 May 2016 (2016-05-03), XP055967000
Examination  HAUBOLD JOHANNES ET AL: "Contrast agent dose reduction in computed tomography with deep learning using a conditional generative adversarial network", EUROPEAN RADIOLOGY, SPRINGER BERLIN HEIDELBERG, BERLIN/HEIDELBERG, vol. 31, no. 8, 25 February 2021 (2021-02-25), pages 6087 - 6095, XP037503087, ISSN: 0938-7994, [retrieved on 20210225], DOI: 10.1007/S00330-021-07714-2

DOI:   http://dx.doi.org/10.1007/s00330-021-07714-2
by applicantWO2022129633
 WO2022129634
   ENHAO GONG ET AL.: "Deep learning enables reduced gadolinium dose for contrast-enhanced brain MRI", JOURNAL OF MAGNETIC RESONANCE IMAGING, vol. 48, no. 2, 13 February 2018 (2018-02-13), pages 330 - 340, XP055656267, DOI: 10.1002/jmri.25970

DOI:   http://dx.doi.org/10.1002/jmri.25970
   JOHANNES HAUBOLD ET AL.: "Contrast agent dose reduction in computed tomography with deep learning using a conditional generative adversarial network", EUROPEAN RADIOLOGY, vol. 31, 2021, pages 6087 - 6095, XP037503087, DOI: 10.1007/s00330-021-07714-2

DOI:   http://dx.doi.org/10.1007/s00330-021-07714-2
otherWO2021061710
   MONTALTTORDERA JAVIER, QUAIL MICHAEL, STEEDEN JENNIFER A, MUTHURANGU VIVEK: "Angiography with Deep Learning", JOURNAL OF MAGNETIC RESONANCE IMAGING, vol. 54, no. 3, 22 February 2021 (2021-02-22), US , pages 795 - 805, XP093348702, ISSN: 1053-1807, DOI: 10.1002/jmri.27573

DOI:   http://dx.doi.org/10.1002/jmri.27573
   ENHAO GONG, JOHN M. PAULY, MAX WINTERMARK, GREG ZAHARCHUK: "Deep learning enables reduced gadolinium dose for contrast-enhanced brain MRI", JOURNAL OF MAGNETIC RESONANCE IMAGING, vol. 48, no. 2, 1 August 2018 (2018-08-01), US , pages 330 - 340, XP055656267, ISSN: 1053-1807, DOI: 10.1002/jmri.25970

DOI:   http://dx.doi.org/10.1002/jmri.25970
   HAUBOLD JOHANNES; HOSCH REN; UMUTLU LALE; WETTER AXEL; HAUBOLD PATRIZIA; RADBRUCH ALEXANDER; FORSTING MICHAEL; NENSA FELIX; KOITK: "Contrast agent dose reduction in computed tomography with deep learning using a conditional generative adversarial network", EUROPEAN RADIOLOGY, vol. 31, no. 8, 25 February 2021 (2021-02-25), Berlin/Heidelberg, pages 6087 - 6095, XP037503087, ISSN: 0938-7994, DOI: 10.1007/s00330-021-07714-2

DOI:   http://dx.doi.org/10.1007/s00330-021-07714-2
The EPO accepts no responsibility for the accuracy of data originating from other authorities; in particular, it does not guarantee that it is complete, up to date or fit for specific purposes.