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Organizers and their institutions
  • Vincent Andrearczyk (Institute of Information Systems, University of Applied Sciences Western Switzerland (HES-SO), Sierre, Switzerland)
  • Valentin Oreiller (Institute of Information Systems, University of Applied Sciences Western Switzerland (HES-SO), Sierre, Switzerland AND Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland)
  • Martin Vallières (Department of Computer Science, Université de Sherbrooke, Sherbrooke, Québec, Canada)
  • Clifton Dave Fuller (The University of Texas MD Anderson Cancer Center (MDA), Houston, Texas, USA)
  • Mohamed Naser (The University of Texas MD Anderson Cancer Center (MDA), Houston, Texas, USA)
  • Kareem Wahid (The University of Texas MD Anderson Cancer Center (MDA), Houston, Texas, USA)
  • Abdallah Mohamed (The University of Texas MD Anderson Cancer Center (MDA), Houston, Texas, USA)
  • Su Ruan (University of Rouen Normandy, Rouen, France)
  • Pierre Decazes (Henri Becquerel Cancer Center, Rouen, France)
  • Pierre Vera (Henri Becquerel Cancer Center, Rouen, France)
  • Habib Zaidi (University Hospitals of Geneva, HUG, Geneva, Switzerland)
  • Stephanie Tanadini-Lang (UniversitätsSpital Zürich, USZ, Zürich, Switzerland)
  • Catherine Cheze-Le Rest (Nuclear medicine department, CHU Poitiers, Poitiers, France and LaTIM, INSERM, UMR 1101, Univ Brest, Brest, France)
  • Olena Tankyevych (Nuclear medicine department, CHU Poitiers, Poitiers, France and LaTIM, INSERM, UMR 1101, Univ Brest, Brest, France)
  • Hesham Elhalawani (Brigham and Women's Hospital, Boston, Massachusetts, USA)
  • Joël Castelli (Centre Eugène Marquis, Rennes, France)
  • Mario Jreige (Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland)
  • Ricardo Dias-Correia (Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland)
  • Sarah Boughdad (Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland)
  • John O. Prior (Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland)
  • Mathieu Hatt (LaTIM, INSERM, UMR 1101, Univ Brest, Brest, France)
  • Adrien Depeursinge (Institute of Information Systems, University of Applied Sciences Western Switzerland (HES-SO), Sierre, Switzerland AND Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland)


Declaration of conflicts of interest

No conflict of interest applies.
Only the organizers will have access to the test case ground truth contours/outcomes.
The challenge is partly funded by the Swiss National Science Foundation (SNSF, grant 205320_179069).


More information on organizers [under construction]
  • Vincent Andrearczyk: Vincent Andrearczyk completed his PhD degree on deep learning for texture and dynamic texture analysis at Dublin City University in 2017. He is currently a senior researcher at the University of Applied Sciences and Arts Western Switzerland with a research focus on deep learning for texture analysis and medical imaging. Vincent co-organized ImageCLEF 2018 Caption detection and prediction challenge and his team at HES-SO Valais has extensive experience in organizing challenges (various tasks in ImageCLEF every year since 2012)
  • Valentin Oreiller: Valentin Oreiller received his M.Sc. degree in bioengineering from the Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland with a specialization in bioimaging. He is currently a PhD candidate at the University of Applied Sciences and Arts Western Switzerland with a research focus on radiomics.
  • Martin Vallières: Martin Vallières is an Assistant Professor in the Department of Computer Science of Université de Sherbrooke since April 2020. He received a PhD in Medical Physics from McGill University in 2017, and completed post-doctoral training in France and USA in 2018 and 2019. The overarching goal of Martin Vallières’ research is centered on the development of clinically-actionable models to better personalize cancer treatments and care (“precision oncology”). He is an expert in the field of radiomics (i.e. the high-throughput and quantitative analysis of medical images) and machine learning in oncology. Over the course of his career, he has developed multiple prediction models for different types of cancers. His main research interest is now focused on the graph-based integration of heterogeneous medical data types for improved precision oncology. He has shared various datasets on The Cancer Imaging Archive (TCIA), including Soft-tissue sarcoma: FDG-PET/CT and MR imaging data of 51 patients, with tumors contours (RTstruct) and clinical data, Low-grade gliomas: Tumour contours for MR images of 108 patients of the TCGA-LGG dataset in MATLAB format, and Head-and-neck: FDG-PET/CT imaging data of 300 patients, with RT plans (RTstruct, RTdose, RTplan) and clinical data. Moreover, he served on the organizing committee of the PET radiomics challenge: A MICCAI 2018 CPM Grand Challenge. 
  • Catherine Chez Le Rest: Nuclear medicine department, CHU Poitiers, Poitiers, France and LaTIM, INSERM, UMR 1101, Univ Brest, Brest, France
  • Hesham Elhalawani: Hesham Elhalawani, MD, MSc is a radiation oncology clinical fellow at Cleveland Clinic. He completed a 3-year quantitative imaging biomarker research fellowship at MD Anderson Cancer Center. His deep-rooted research focus is leveraging artificial intelligence, radiomics, and imaging informatics to personalize cancer patients care. He published more than 50 peer-reviewed articles and served as a reviewer for journals and conferences, including Radiotherapy & Oncology, Red Journal, European Radiology, and AMIA conferences. He is among the editorial board of Radiology: Artificial intelligence, an RSNA publication. He has been an advocate for FAIR principles of data management via contributing to the mission and goals of NCI Cancer Imaging Program. Collaboratively with The Cancer Imaging Archive (TCIA), they publicly shared two large curated head and neck cancer datasets that included matched clinical and multi-modal imaging data. Moreover, he served on the organizing committee for the 2016 and 2018 MICCAI radiomics challenges that were hosted on Kaggle in Class to fuel the growing trend in mass crowdsource innovation.
  • Sarah Boughdad: Dr. Boughdad is currently a Fellow at the Service of Nuclear Medicine and Molecular Imaging at Lausanne University Hospital, Switzerland. In 2014, she graduated from the Medical Faculty of Paris-Sud, Paris-Saclay. She obtained her PhD in medical physics in 2018 from EOBE, Orsay University. She is an active researcher in the field of Radiomics.
  • Mario Jreige: Mario Jreige, MD, is a nuclear medicine resident at Lausanne University Hospital, Switzerland. He has previously completed a specialization in radiology at the Saint-Joseph University, Beirut. He is a junior member of the Swiss Society of Nuclear Medicine.
  • John O. Prior: John O. Prior, PhD MD, FEBNM has been Professor and Head of Nuclear Medicine and Molecular Imaging at Lausanne University Hospital, Switzerland since 2010. After graduating with a MSEE degree from ETH Zurich, he received a PhD in Biomedical Engineering from The University of Texas Southwestern Medical Center at Dallas and a MD from the University of Lausanne. He underwent thereafter specialization training in nuclear medicine in Lausanne and a visiting associate professorship at the University of California at Los Angeles (UCLA). Prof. Prior is currently President of the Swiss Society of Nuclear Medicine, Member of the European Association of Nuclear Medicine, the Society of Nuclear Medicine and Molecular Imaging, as well as IEEE Senior Member.
  • Mathieu Hatt: Mathieu Hatt was trained as a computer scientist and received his Ms. Sc. degree in computer sciences in 2004 from the University of Strasbourg, France. He received his PhD in 2008 and his habilitation to supervise research in 2012 from the University of Brest, France. He was recruited as a junior researcher at INSERM in 2012 and was promoted to director of research in 2021. His main skills and expertise lie in radiomics, from automated image segmentation to features extraction, as well as machine (deep) learning methods, for PET/CT, MRI and CT modalities. He is in charge of a research group "radiomics modeling" in the team ACTION (therapeutic action guided by multimodal images in oncology) of the LaTIM (Laboratory of Medical Information Processing, INSERM UMR 1101, University of Brest, France). He is an elected member of the EANM physics committee, the SNMMI physics, data science and instrumentation council board of directors, and the IEEE nuclear medical and imaging sciences council.
  • Adrien Depeursinge: Adrien Depeursinge received the M.Sc. degree in electrical engineering from the Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland with a specialization in signal processing. From 2006 to 2010, he performed his Ph.D. thesis on medical image analysis at the University Hospitals of Geneva (HUG). He then spent two years as a Postdoctoral Fellow at the Department of Radiology of the School of Medicine at Stanford University. He has currently a joint position as an Associate Professor at the Institute of Information Systems, University of Applied Sciences Western Switzerland (HES-SO), and as a Senior Research Scientist at the Lausanne University Hospital (CHUV). A large experience in challenge organization (e.g. ImageCLEF, VISCERAL) exists in his group jointly led with Prof. Müller (MedGIFT). He also prepared a dataset of Interstitial Lung Disease (ILD) for comparison of algos open access dataset. The library contains 128 patients affected with ILDs, 108 image series with more than 41 liters of annotated lung tissue patterns as well as a comprehensive set of 99 clinical parameters related to ILDs. This dataset has become a reference for research on ILDs and the associated paper has >100 citation