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

Resultado final

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 Web Presence

Description of the project website and social media accounts.

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

Publicaciones

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

Autores: ESTHER CIARROCCHI; Emanuele Neri
Publicado en: European Radiology Experimental, Edición 25099280, 2022, ISSN 2509-9280
Editor: 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

Autores: Jamalzadeh S, Häkkinen A, Andersson N, Huhtinen K, Laury A, Hietanen S, Hynninen J, Oikkonen J, Carpén O, Virtanen A, Hautaniemi S
Publicado en: Laboratory Investigation, Edición February 2022, 2022, ISSN 1530-0307
Editor: Springer Nature
DOI: 10.1038/s41374-022-00743-5

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

Autores: 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.
Publicado en: Applied Sciences, Edición 20763417, 2022, ISSN 2076-3417
Editor: MDPI
DOI: 10.3390/app12178755

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

Autores: 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.
Publicado en: Eur Radiol Exp, 2023, ISSN 2509-9280
Editor: SpringerOpen
DOI: 10.1186/s41747-023-00336-x

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

Autores: Iman Hesso; Reem Kayyali; Andreas Charalambous; Maria Lavdaniti; Evangelia Stalika; Maria Lelegianni; Shereen Nabhani-Gebara
Publicado en: Frontiers in Oncology, Edición 2234943X, 2022, ISSN 2234-943X
Editor: 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

Autores: Protonotarios NE, Katsamenis I, Sykiotis S, Dikaios N, Kastis GA, Chatziioannou SN, Metaxas M, Doulamis N, Doulamis A.
Publicado en: Biomed Phys Eng Express, Edición February 2022, 2022, ISSN 2057-1976
Editor: Pub.Med.gov
DOI: 10.1088/2057-1976/ac53bd

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

Autores: 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
Publicado en: Insights into Imaging, Edición 2022, 2022, ISSN 1869-4101
Editor: Springer Science and Business Media Deutschland GmbH
DOI: 10.1186/s13244-022-01220-9

H&E image analysis pipeline for quantifying morphological features

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

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

Autores: Prvulovic Bunovic N, Sveljo O, Kozic D, Boban J.
Publicado en: Frontiers in Oncology, Edición September 2021, 2021, ISSN 2234-943X
Editor: Frontiers Media S. A.
DOI: 10.3389/fonc.2021.610354

Tensor-Based Learning for Detecting Abnormalities on Digital Mammograms

Autores: Ioannis N. Tzortzis; Agapi Davradou; Ioannis Rallis; Maria Kaselimi; Konstantinos Makantasis; Anastasios Doulamis; Nikolaos Doulamis
Publicado en: Diagnostics, Vol 12, Iss 10, p 2389 (2022), Edición 1, 2022, ISSN 2075-4418
Editor: Diagnosis
DOI: 10.3390/diagnostics12102389

Information extraction from clinical records: an example for breast cancer

Autores: I. Lazic, N. Jakovljevic, J. Boban, I. Nosek and T. Loncar-Turukalo
Publicado en: IEEE 21st Mediterranean Electrotechnical Conference (MELECON), 2022
Editor: 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

Autores: E. Stalika, K. Gavrilaki, I. Koziokos, I. Chouvarda, M. Lavdaniti
Publicado en: Annals of Oncology, 2022
Editor: Elsevier
DOI: 10.1016/j.annonc.2022.07.319

A deep-learning based diagnostic framework for Breast Cancer.

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

Distributing Deep Learning Hyperparameter Tuning for 3D Medical Image Segmentation

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

Towards Data Integration for AI in Cancer Research

Autores: Kosvyra A, Filos D, Fotopoulos D, Olga T and Chouvarda I.
Publicado en: Annu Int Conf IEEE Eng Med Biol Soc, Edición November 2021, 2021
Editor: Pub.Med.gov
DOI: 10.1109/embc46164.2021.9629675

Towards Lung Cancer Staging via Μultipositional Radiomics and Machine Learning

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

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

Autores: Alexandra Kosvyra; Dimitrios Filos; Dimitrios Fotopoulos; Olga Tsave; Ioanna Chouvarda
Publicado en: 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022
Editor: 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

Autores: Ntzioni E, Chouvarda I.
Publicado en: Stud Health Technol Inform, 2022
Editor: IOS Press
DOI: 10.3233/shti210965

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

Autores: 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
Publicado en: arXiv, 2021
Editor: arXiv
DOI: 10.48550/arxiv.2109.09658

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

Autores: 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
Publicado en: arXiv, Edición 1, 2023, ISSN 2331-8422
Editor: Cornell University
DOI: 10.48550/arxiv.2309.12325

Pseudonymization and anonymization of personal data in scientific research projects

Autores: Pseudonymization and anonymization of personal data in scientific research projects
Publicado en: KWARTALNIK PRAWO NOWYCH TECHNOLOGII, Edición July 2021, 2021, ISSN 2720-1600
Editor: C.H. Beck

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