Overview of the HECKTOR Challenge at MICCAI 2022 : automatic head and neck tumor segmentation and outcome prediction in PET/CT
Andrearczyk, Vincent; Oreillerm Valentin; Abobakr, Moamen; Akhavanallaf, Azadeh; Balermpas, Panagiotis; Boughdad, Sarah; Capriotti, Leo; Castelli, Joel; Cheze Le Rest, Catherine; Decazes, Pierre; Correia, Ricardo; El-Habashy, Dina; Elhalawani, Hesham; Fuller, Clifton D.; Jreige, Mario; Khamis, Yomna; La Greca, Agustina; Mohamed, Abdallah; Naser, Mohamed; Prior, John O.; Ruan, Su; Tanadini-Lang, Stephanie; Tankyevych, Olena; Salimi, Yazdan; Vallières, Martin; Vera, Pierre; Visvikis, Dimitri; Wahid, Kareem; Zaidi, Habib; Hatt, Mathieu; Depeursinge, Adrien
2023

Résumé

This paper presents an overview of the third edition of the HEad and neCK TumOR segmentation and outcome prediction (HECKTOR) challenge, organized as a satellite event of the 25th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2022. The challenge comprises two tasks related to the automatic analysis of FDG-PET/CT images for patients with Head and Neck cancer (H &N), focusing on the oropharynx region. Task 1 is the fully automatic segmentation of H &N primary Gross Tumor Volume (GTVp) and metastatic lymph nodes (GTVn) from FDG-PET/CT images. Task 2 is the fully automatic prediction of Recurrence-Free Survival (RFS) from the same FDG-PET/CT and clinical data. The data were collected from nine centers for a total of 883 cases consisting of FDG-PET/CT images and clinical information, split into 524 training and 359 test cases. The best methods obtained an aggregated Dice Similarity Coefficient (DSCagg) of 0.788 in Task 1, and a Concordance index (C-index) of 0.682 in Task 2.

Détails

Titre Overview of the HECKTOR Challenge at MICCAI 2022 : automatic head and neck tumor segmentation and outcome prediction in PET/CT
Auteur(s)/ trice(s) Andrearczyk, Vincent (University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis))
Oreillerm Valentin (University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis) ; Department of Nuclear Medicine and Molecular Imaging, Lausanne University Hospital (CHUV), Lausanne, Switzerland)
Abobakr, Moamen (The University of Texas MD Anderson Cancer Center, Houston, USA)
Akhavanallaf, Azadeh (Geneva University Hospital, Geneva, Switzerland)
Balermpas, Panagiotis (University Hospital Zürich, Zurich, Switzerland)
Boughdad, Sarah (Department of Nuclear Medicine and Molecular Imaging, Lausanne University Hospital (CHUV), Lausanne, Switzerland)
Capriotti, Leo (Center Henri Becquerel, LITIS laboratory, University of Rouen Normandy, Rouen, France)
Castelli, Joel (Radiotherapy Department, Cancer Institute Eug`ene Marquis, Rennes, France ; INSERM, U1099, Rennes, France ; University of Rennes 1, LTSI, Rennes, France)
Cheze Le Rest, Catherine (Centre Hospitalier Universitaire de Poitiers (CHUP), Poitiers, France ; LaTIM, INSERM, UMR 1101, Univ Brest, Brest, France)
Decazes, Pierre (Center Henri Becquerel, LITIS laboratory, University of Rouen Normandy, Rouen, France)
Correia, Ricardo (Department of Nuclear Medicine and Molecular Imaging, Lausanne University Hospital (CHUV), Lausanne, Switzerland)
El-Habashy, Dina (The University of Texas MD Anderson Cancer Center, Houston, USA)
Elhalawani, Hesham (Cleveland Clinic Foundation, Department of Radiation Oncology, Cleveland, OH, USA)
Fuller, Clifton D. (The University of Texas MD Anderson Cancer Center, Houston, USA)
Jreige, Mario (Department of Nuclear Medicine and Molecular Imaging, Lausanne University Hospital (CHUV), Lausanne, Switzerland)
Khamis, Yomna (The University of Texas MD Anderson Cancer Center, Houston, USA)
La Greca, Agustina (University Hospital Zürich. Zurich, Switzerland)
Mohamed, Abdallah (The University of Texas MD Anderson Cancer Center, Houston, USA)
Naser, Mohamed (The University of Texas MD Anderson Cancer Center, Houston, USA)
Prior, John O. (Department of Nuclear Medicine and Molecular Imaging, Lausanne University Hospital (CHUV), Lausanne, Switzerland)
Ruan, Su (Center Henri Becquerel, LITIS laboratory, University of Rouen Normandy, Rouen, France)
Tanadini-Lang, Stephanie (University Hospital Zürich. Zurich, Switzerland)
Tankyevych, Olena (Centre Hospitalier Universitaire de Poitiers (CHUP), Poitiers, France ; LaTIM, INSERM, UMR 1101, Univ Brest, Brest, France)
Salimi, Yazdan (Geneva University Hospital, Geneva, Switzerland)
Vallières, Martin (Department of Computer Science, Université de Sherbrooke, Sherbrooke, Québec, Canada)
Vera, Pierre (Center Henri Becquerel, LITIS laboratory, University of Rouen Normandy, Rouen, France)
Visvikis, Dimitri (LaTIM, INSERM, UMR 1101, Univ Brest, Brest, France)
Wahid, Kareem (The University of Texas MD Anderson Cancer Center, Houston, USA)
Zaidi, Habib (Geneva University Hospital, Geneva, Switzerland)
Hatt, Mathieu (LaTIM, INSERM, UMR 1101, Univ Brest, Brest, France)
Depeursinge, Adrien (University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis) ; Department of Nuclear Medicine and Molecular Imaging, Lausanne University Hospital (CHUV), Lausanne, Switzerland)
Date 2023-03
Publié dans Head and neck tumor segmentation and outcome prediction
Volume March 2023, pp. 1–30
Editeur Cham, Springer
Pagination 31 p.
Présenté à 25th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2022), Singapore, 2022-09-18, 2022-09-22
ISBN 978-3-031-27420-6
DOI https://doi.org/10.1007/978-3-031-27420-6_1
ISSN 0302-9743
Collection et n° Lecture notes in computer science, vol. 13626
Mots-clés (libres) challenge ; medical imaging ; head and neck cancer ; segmentation ; radiomics ; deep learning ; machine learning
Type de papier published full paper
Domaine Economie et Services
Ecole HEG-VS
Institut Institut Informatique de gestion
Le document apparaît dans Documents de conférences
Global

Actions

PDF