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Sökning: WFRF:(Gustafsson Claes) > VAI-B: a multicente...

  • Cossío, FernandoKarolinska Institute, Department of Oncology-Pathology, Stockholm, Sweden (författare)

VAI-B: a multicenter platform for the external validation of artificial intelligence algorithms in breast imaging

  • Artikel/kapitelSvenska2023

Förlag, utgivningsår, omfång ...

  • SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS,2023
  • printrdacarrier

Nummerbeteckningar

  • LIBRIS-ID:oai:DiVA.org:liu-198302
  • https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-198302URI
  • https://doi.org/10.1117/1.jmi.10.6.061404DOI

Kompletterande språkuppgifter

  • Språk:svenska
  • Sammanfattning på:engelska

Ingår i deldatabas

Klassifikation

  • Ämneskategori:ref swepub-contenttype
  • Ämneskategori:art swepub-publicationtype

Anmärkningar

  • Funding: Regional Cancer Centers in Collaboration and Vinnova [21/00060, 2021-02617]; Medtechlabs, Stockholm, Sweden
  • Purpose: Multiple vendors are currently offering artificial intelligence (AI) computer-aided systems for triage detection, diagnosis, and risk prediction of breast cancer based on screening mammography. There is an imminent need to establish validation platforms that enable fair and transparent testing of these systems against external data.Approach: We developed validation of artificial intelligence for breast imaging (VAI-B), a platform for independent validation of AI algorithms in breast imaging. The platform is a hybrid solution, with one part implemented in the cloud and another in an on-premises environment at Karolinska Institute. Cloud services provide the flexibility of scaling the computing power during inference time, while secure on-premises clinical data storage preserves their privacy. A MongoDB database and a python package were developed to store and manage the data on-premises. VAI-B requires four data components: radiological images, AI inferences, radiologist assessments, and cancer outcomes.Results: To pilot test VAI-B, we defined a case-control population based on 8080 patients diagnosed with breast cancer and 36,339 healthy women based on the Swedish national quality registry for breast cancer. Images and radiological assessments from more than 100,000 mammography examinations were extracted from hospitals in three regions of Sweden. The images were processed by AI systems from three vendors in a virtual private cloud to produce abnormality scores related to signs of cancer in the images. A total of 105,706 examinations have been processed and stored in the database.Conclusions: We have created a platform that will allow downstream evaluation of AI systems for breast cancer detection, which enables faster development cycles for participating vendors and safer AI adoption for participating hospitals. The platform was designed to be scalable and ready to be expanded should a new vendor want to evaluate their system or should a new hospital wish to obtain an evaluation of different AI systems on their images.

Ämnesord och genrebeteckningar

Biuppslag (personer, institutioner, konferenser, titlar ...)

  • Schurz, HaikoKarolinska Institute, Department of Oncology-Pathology, Stockholm, Sweden (författare)
  • Engström, MathiasCollective Minds Radiology, Stockholm, Sweden (författare)
  • Barck-Holst, CarlWest Code Group, Stockholm, Sweden (författare)
  • Tsirikoglou, ApostoliaKarolinska Institute, Department of Oncology-Pathology, Stockholm, Sweden (författare)
  • Lundström, Claes,1973-Linköpings universitet,Medie- och Informationsteknik,Tekniska fakulteten,Centrum för medicinsk bildvetenskap och visualisering, CMIV(Swepub:liu)clalu03 (författare)
  • Gustafsson, Håkan,1976-Linköpings universitet,Medicinska fakulteten,Avdelningen för diagnostik och specialistmedicin,Centrum för medicinsk bildvetenskap och visualisering, CMIV,Region Östergötland, Medicinsk strålningsfysik(Swepub:liu)hakgu16 (författare)
  • Smith, KevinRoyal Institute of Technology (KTH), Division of Computational Science and Technology, Stockholm, Sweden (författare)
  • Zackrisson, SophiaLund University, Department of Diagnostic Radiology, Translational Medicine, Malmö, Sweden (författare)
  • Strand, FredrikKarolinska Institute, Department of Oncology-Pathology, Stockholm, Sweden (författare)
  • Karolinska Institute, Department of Oncology-Pathology, Stockholm, SwedenCollective Minds Radiology, Stockholm, Sweden (creator_code:org_t)

Sammanhörande titlar

  • Ingår i:Journal of Medical Imaging: SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS10:062329-43022329-4310

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