A multimodal AI-based toolbox and an interoperable health imaging repository for the empowerment of imaging analysis related to the diagnosis, prediction and follow-up of cancer

Leistungen

Report on the dissemination activities carried out during the first reporting period

Clustering Events Proceedings and Raising Awareness Campaigns Results V1

Proceedings of the clustering events including relevant material eg presentations etc along with the strategy presentation and results of the campaign regarding the panEuropean repository of health images

Second Dissemination Activities Report

Report on the dissemination activities carried out during the second reporting period

INCISIVE Training Material

The material used for the training of INCISIVE users participating in pilot studies.

Evaluation of INCISIVE Blind Studies

Assessment of INCISIVE blind interventions, including feedback for the prototype developments.

Data Donation Legal Framework

Provides the guidelines and terms for data donors to participate in INCISIVE’s data providers ecosystem.

Evaluation of INCISIVE Interventional studies

Assessment of INCISIVE interventional studies, including recommendations for the future

Clustering Events Proceedings and Raising Awareness Campaigns Results V2

Proceedings of the clustering events, including relevant material (e.g. presentations etc.), along with the strategy presentation and results of the campaign regarding the pan-European repository of health images.

Best Practices for Wider Use and Applicability

Best practices, strategies and open challenges for the wide AI solutions adoption in medical imaging.

Standardization Suggestions

report describing the INCISIVE’s contribution to standards.

Final Dissemination Activities Report

Report on the dissemination activities carried out during the final reporting period.

INCISIVE integrated Prototypes - Final Version

INCISIVE integrated prototypes for the pre-pilot validations and pilot studies.

INCISIVE Pan-European Repository of Health Images - Final Version

final version to be integrated to the final prototype and to be launched as a stand-alone system.

INCISIVE AI Toolbox, Data Analytics and User Services - Final Version

final version of the AI models, data analytics and user services incorporating feedback from the pilots.

INCISIVE Web Presence

Description of the project website and social media accounts.

Final Data Management Report

This report will describe the research data generated in the project and how they will be published. In particular it will include (1) the data and data format, (2) Metadata content and format, (3) Policies for access, sharing and re-use, and (4) Long-term storage and data management.

Initial Data Management Plan

This report will describe the research data generated in the project and how they will be published In particular it will include 1 the data and data format 2 Metadata content and format 3 Policies for access sharing and reuse and 4 Longterm storage and data management

Veröffentlichungen

Position of the AI for Health Imaging (AI4HI) network on metadata models for imaging biobanks

Autoren: ESTHER CIARROCCHI; Emanuele Neri
Veröffentlicht in: European Radiology Experimental, Ausgabe 25099280, 2022, ISSN 2509-9280
Herausgeber: Springer
DOI: 10.1186/s41747-022-00281-1

QuantISH: RNA in situ hybridization image analysis framework for quantifying cell type-specific target RNA expression and variability

Autoren: Jamalzadeh S, Häkkinen A, Andersson N, Huhtinen K, Laury A, Hietanen S, Hynninen J, Oikkonen J, Carpén O, Virtanen A, Hautaniemi S
Veröffentlicht in: Laboratory Investigation, Ausgabe February 2022, 2022, ISSN 1530-0307
Herausgeber: Springer Nature
DOI: 10.1038/s41374-022-00743-5

The Holistic Perspective of the INCISIVE Project—Artificial Intelligence in Screening Mammography.

Autoren: Lazic I, Agullo F, Ausso S, Alves B, Barelle C, Berral JL, Bizopoulos P, Bunduc O, Chouvarda I, Dominguez D, Filos D, Gutierrez-Torre A, Hesso I, Jakovljević N, Kayyali R, Kogut-Czarkowska M, Kosvyra A, Lalas A, Lavdaniti M, Loncar-Turukalo T, Martinez-Alabart S, Michas N, Nabhani-Gebara S, Raptopoulos A, Roussakis Y, Stalika E, Symvoulidis C, Tsave O, Votis K, Charalambous A.
Veröffentlicht in: Applied Sciences, Ausgabe 20763417, 2022, ISSN 2076-3417
Herausgeber: MDPI
DOI: 10.3390/app12178755

Data infrastructures for AI in medical imaging: a report on the experiences of five EU projects

Autoren: Kondylakis, H., Kalokyri, V., Sfakianakis, S., Marias, K., Tsiknakis, M., Jimenez-Pastor, A., Camacho-Ramos, E., Blanquer, I., Segrelles, J. D., López-Huguet, S., Barelle, C., Kogut-Czarkowska, M., Tsakou, G., Siopis, N., Sakellariou, Z., Bizopoulos, P., Drossou, V., Lalas, A., Votis, K., Mallol, P., … Lekadir, K.
Veröffentlicht in: Eur Radiol Exp, 2023, ISSN 2509-9280
Herausgeber: SpringerOpen
DOI: 10.1186/s41747-023-00336-x

Cancer care pathways across seven countries in Europe: What are the current obstacles? And how can artificial intelligence help?

Autoren: Iman Hesso, Reem Kayyali, Lithin Zacharias, Andreas Charalambous, Maria Lavdaniti, Evangelia Stalika, Tarek Ajami, Wanda Acampa, Jasmina Boban, Shereen Nabhani Gebara
Veröffentlicht in: Journal of Cancer Policy, 2023, Seite(n) Volume 39, 2024, 100457, ISSN 2213-5383
Herausgeber: Elsevier BV
DOI: 10.1016/j.jcpo.2023.100457

Experiences of cancer survivors in Europe: Has anything changed? Can artificial intelligence offer a solution?

Autoren: Iman Hesso; Reem Kayyali; Andreas Charalambous; Maria Lavdaniti; Evangelia Stalika; Maria Lelegianni; Shereen Nabhani-Gebara
Veröffentlicht in: Frontiers in Oncology, Ausgabe 2234943X, 2022, ISSN 2234-943X
Herausgeber: Frontiers Media S. A.
DOI: 10.3389/fonc.2022.888938

A few-shot U-Net deep learning model for lung cancer lesion segmentation via PET/CT imaging

Autoren: Protonotarios NE, Katsamenis I, Sykiotis S, Dikaios N, Kastis GA, Chatziioannou SN, Metaxas M, Doulamis N, Doulamis A.
Veröffentlicht in: Biomed Phys Eng Express, Ausgabe February 2022, 2022, ISSN 2057-1976
Herausgeber: Pub.Med.gov
DOI: 10.1088/2057-1976/ac53bd

Considerations for artificial intelligence clinical impact in oncologic imaging: an AI4HI position paper

Autoren: Luis Marti‑Bonmati, Dow‑Mu Koh, Katrine Riklund, Maciej Bobowicz, Yiannis Roussakis, Joan C. Vilanova, Jurgen J. Fütterer, Jordi Rimola, Pedro Mallol, Gloria Ribas, Ana Miguel, Manolis Tsiknakis, Karim Lekadir and Gianna Tsakou
Veröffentlicht in: Insights into Imaging, Ausgabe 2022, 2022, ISSN 1869-4101
Herausgeber: Springer Science and Business Media Deutschland GmbH
DOI: 10.1186/s13244-022-01220-9

Cancer care at the time of the fourth industrial revolution: an insight to healthcare professionals’ perspectives on cancer care and artificial intelligence

Autoren: Iman Hesso, Reem Kayyali, Debbie-Rose Dolton, Kwanyoung Joo, Lithin Zacharias, Andreas Charalambous, Maria Lavdaniti, Evangelia Stalika, Tarek Ajami, Wanda Acampa, Jasmina Boban & Shereen Nabhani-Gebara
Veröffentlicht in: Radiation Oncology, 2023, ISSN 0360-3016
Herausgeber: Elsevier BV
DOI: 10.1186/s13014-023-02351-z

H&E image analysis pipeline for quantifying morphological features

Autoren: Valeria, Ariotta; Oskari, Lehtonen; Shams, Salloum; Giulia, Micoli; Kari, Lavikka; Ville, Rantanen; Johanna, Hynninen; Anni, Virtanen; Sampsa, Hautaniemi
Veröffentlicht in: Journal of Pathology Informatics, Vol 14, Iss , Pp 100339- (2023), Ausgabe 1, 2023, ISSN 2153-3539
Herausgeber: Elsevier
DOI: 10.1016/j.jpi.2023.100339

Is Elevated Choline on Magnetic Resonance Spectroscopy a Reliable Marker of Breast Lesion Malignancy?

Autoren: Prvulovic Bunovic N, Sveljo O, Kozic D, Boban J.
Veröffentlicht in: Frontiers in Oncology, Ausgabe September 2021, 2021, ISSN 2234-943X
Herausgeber: Frontiers Media S. A.
DOI: 10.3389/fonc.2021.610354

Tensor-Based Learning for Detecting Abnormalities on Digital Mammograms

Autoren: Ioannis N. Tzortzis; Agapi Davradou; Ioannis Rallis; Maria Kaselimi; Konstantinos Makantasis; Anastasios Doulamis; Nikolaos Doulamis
Veröffentlicht in: Diagnostics, Vol 12, Iss 10, p 2389 (2022), Ausgabe 1, 2022, ISSN 2075-4418
Herausgeber: Diagnosis
DOI: 10.3390/diagnostics12102389

Information extraction from clinical records: an example for breast cancer

Autoren: I. Lazic, N. Jakovljevic, J. Boban, I. Nosek and T. Loncar-Turukalo
Veröffentlicht in: IEEE 21st Mediterranean Electrotechnical Conference (MELECON), 2022
Herausgeber: IEEE Xplore
DOI: 10.1109/melecon53508.2022.9842995

CN9 Mapping the Functional Assessment of Cancer Therapy (FACT-G) in Greek patients with neoplasm: An interplay of statistical and bioinformatics approach

Autoren: E. Stalika, K. Gavrilaki, I. Koziokos, I. Chouvarda, M. Lavdaniti
Veröffentlicht in: Annals of Oncology, 2022
Herausgeber: Elsevier
DOI: 10.1016/j.annonc.2022.07.319

HealthMesh: An Architectural Framework for Federated Healthcare Data Management

Autoren: Aniol Bisquert, Achraf Hmimou, Josep Ll. Berral, Alberto Gutierrez-Torre, Oscar Romero
Veröffentlicht in: CEUR Workshop Proceedings. 26th International Workshop on Design, Optimization, Languages and Analytical Processing of Big Data, 2024
Herausgeber: CEUR Workshop Proceedings

A deep-learning based diagnostic framework for Breast Cancer.

Autoren: Stavros Sykiotis, Ioannis Tzortzis, Aikaterini Angeli, Nikolaos Doulamis, and Dimitrios Kalogeras.
Veröffentlicht in: Proceedings of the 15th International Conference on PErvasive Technologies Related to Assistive Environments (PETRA '22), 2022
Herausgeber: Association for Computing Machinery
DOI: 10.1145/3529190.3534769

Distributing Deep Learning Hyperparameter Tuning for 3D Medical Image Segmentation

Autoren: Berral JL, Aranda O, Dominguez JL, Torres J.
Veröffentlicht in: IPDPS 36th IEEE International Parallel & Distributed Processing Symposium, Workshop on Scalable Deep Learning (ScaDL)- IEEE Xplore, Ausgabe October 2021 (Arxiv), May 2022 (Conference), 2021
Herausgeber: IEEExplore Library
DOI: 10.48550/arxiv.2110.15884

Towards Data Integration for AI in Cancer Research

Autoren: Kosvyra A, Filos D, Fotopoulos D, Olga T and Chouvarda I.
Veröffentlicht in: Annu Int Conf IEEE Eng Med Biol Soc, Ausgabe November 2021, 2021
Herausgeber: Pub.Med.gov
DOI: 10.1109/embc46164.2021.9629675

Towards Lung Cancer Staging via Μultipositional Radiomics and Machine Learning

Autoren: Fotopoulos, D, Filos D, Xinou E, and Chouvarda I
Veröffentlicht in: In Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies, 2023, ISBN 978-989-758-631-6
Herausgeber: BIOSIGNALS
DOI: 10.5220/0011781500003414

Data Quality Check in Cancer Imaging Research: Deploying and Evaluating the DIQCT Tool

Autoren: Alexandra Kosvyra; Dimitrios Filos; Dimitrios Fotopoulos; Olga Tsave; Ioanna Chouvarda
Veröffentlicht in: 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022
Herausgeber: IEEE Xplore
DOI: 10.1109/embc48229.2022.9871018

Combining Machine Learning and Network Analysis Pipelines: The Case of Microbiome and Metabolomics Data in Colorectal Cancer

Autoren: Ntzioni E, Chouvarda I.
Veröffentlicht in: Stud Health Technol Inform, 2022
Herausgeber: IOS Press
DOI: 10.3233/shti210965

Anonymisation: The Trap for Biobanking (Part II)

Autoren: Magdalena Kogut-Czarkowska
Veröffentlicht in: Springer, 2023, ISBN 978-3-031-42943-9
Herausgeber: Springer
DOI: 10.1007/978-3-031-42944-6_4

FUTURE-AI: Guiding Principles and Consensus Recommendations for Trustworthy Artificial Intelligence in Medical Imaging

Autoren: Lekadir, Karim; Osuala, Richard; Gallin, Catherine; Lazrak, Noussair; Kushibar, Kaisar; Tsakou, Gianna; Auss��, Susanna; Alberich, Leonor Cerd��; Marias, Kostas; Tsiknakis, Manolis; Colantonio, Sara; Papanikolaou, Nickolas; Salahuddin, Zohaib; Woodruff, Henry C; Lambin, Philippe; Mart��-Bonmat��, Luis
Veröffentlicht in: arXiv, 2021
Herausgeber: arXiv
DOI: 10.48550/arxiv.2109.09658

FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare

Autoren: Lekadir, Karim; Feragen, Aasa; Fofanah, Abdul Joseph; Frangi, Alejandro F; Buyx, Alena; Emelie, Anais; Lara, Andrea; Porras, Antonio R; Chan, An-Wen; Navarro, Arcadi; Glocker, Ben; Botwe, Benard O; Khanal, Bishesh; Beger, Brigit; Wu, Carol C; Cintas, Celia; Langlotz, Curtis P; Rueckert, Daniel; Mzurikwao, Deogratias; Fotiadis, Dimitrios I; Zhussupov, Doszhan; Ferrante, Enzo; Meijering, Erik; Weick
Veröffentlicht in: arXiv, Ausgabe 1, 2023, ISSN 2331-8422
Herausgeber: Cornell University
DOI: 10.48550/arxiv.2309.12325

Pseudonymization and anonymization of personal data in scientific research projects

Autoren: Pseudonymization and anonymization of personal data in scientific research projects
Veröffentlicht in: KWARTALNIK PRAWO NOWYCH TECHNOLOGII, Ausgabe July 2021, 2021, ISSN 2720-1600
Herausgeber: C.H. Beck

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