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Where is VALDO? VAscular Lesions Detection and segmentatiOn challenge at MICCAI 2021.
Sudre, Carole H; Van Wijnen, Kimberlin; Dubost, Florian; Adams, Hieab; Atkinson, David; Barkhof, Frederik; Birhanu, Mahlet A; Bron, Esther E; Camarasa, Robin; Chaturvedi, Nish; Chen, Yuan; Chen, Zihao; Chen, Shuai; Dou, Qi; Evans, Tavia; Ezhov, Ivan; Gao, Haojun; Girones Sanguesa, Marta; Gispert, Juan Domingo; Gomez Anson, Beatriz; Hughes, Alun D; Ikram, M Arfan; Ingala, Silvia; Jaeger, H Rolf; Kofler, Florian; Kuijf, Hugo J; Kutnar, Denis; Lee, Minho; Li, Bo; Lorenzini, Luigi; Menze, Bjoern; Molinuevo, Jose Luis; Pan, Yiwei; Puybareau, Elodie; Rehwald, Rafael; Su, Ruisheng; Shi, Pengcheng; Smith, Lorna; Tillin, Therese; Tochon, Guillaume; Urien, Hélène; van der Velden, Bas H M; van der Velpen, Isabelle F; Wiestler, Benedikt; Wolters, Frank J; Yilmaz, Pinar; de Groot, Marius; Vernooij, Meike W; de Bruijne, Marleen.
Affiliation
  • Sudre CH; MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science and Experimental Medicine, University College London, London, United Kingdom; Centre for Medical Image Computing, University College London, London, United Kingdom; School of Biomedical Engineering and Imaging Sciences,
  • Van Wijnen K; Biomedical Imaging Group Rotterdam, Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands.
  • Dubost F; Biomedical Imaging Group Rotterdam, Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands.
  • Adams H; Department of Clinical Genetics and Radiology, Erasmus MC, Rotterdam, The Netherlands.
  • Atkinson D; Centre for Medical Imaging, University College London, London, United Kingdom.
  • Barkhof F; Centre for Medical Image Computing, University College London, London, United Kingdom; Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centre, Amsterdam, The Netherlands.
  • Birhanu MA; Biomedical Imaging Group Rotterdam, Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands.
  • Bron EE; Biomedical Imaging Group Rotterdam, Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands.
  • Camarasa R; Biomedical Imaging Group Rotterdam, Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands.
  • Chaturvedi N; MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science and Experimental Medicine, University College London, London, United Kingdom.
  • Chen Y; Department of Radiology, University of Massachusetts Medical School, Worcester, USA.
  • Chen Z; School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
  • Chen S; Biomedical Imaging Group Rotterdam, Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands.
  • Dou Q; Department of Computer Science and Engineering, The Chinese University of Hong Kong, China.
  • Evans T; Department of Clinical Genetics and Radiology, Erasmus MC, Rotterdam, The Netherlands.
  • Ezhov I; Department of Informatics, Technische Universitat Munchen, Munich, Germany; TranslaTUM - Central Institute for Translational Cancer Research, Technical University of Munich, Germany.
  • Gao H; Department of Radiology, Zhejiang University, Hangzhou, China.
  • Girones Sanguesa M; Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Gispert JD; Barcelonaß Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain; Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain; Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Barcelona, Spain.
  • Gomez Anson B; Department of Radiology, Hospital San Pau i santa Creu, Barcelona, Spain.
  • Hughes AD; MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science and Experimental Medicine, University College London, London, United Kingdom.
  • Ikram MA; Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands.
  • Ingala S; Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centre, Amsterdam, The Netherlands.
  • Jaeger HR; Institute of Neurology, University College London, London, United Kingdom.
  • Kofler F; Department of Informatics, Technische Universitat Munchen, Munich, Germany; Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Germany; TranslaTUM - Central Institute for Translational Cancer Research, Technical U
  • Kuijf HJ; Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Kutnar D; Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Lee M; Neurophet, South Korea.
  • Li B; Biomedical Imaging Group Rotterdam, Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands.
  • Lorenzini L; Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centre, Amsterdam, The Netherlands.
  • Menze B; Department of Informatics, Technische Universitat Munchen, Munich, Germany; Department of Quantitative Biomedicine, University of Zurich, Switzerland.
  • Molinuevo JL; Barcelonaß Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain; H. Lundbeck A/S, Copenhagen, Denmark.
  • Pan Y; Department of Electronic and Information Engineering, Harbin Institute of Technology at Shenzhen, Shenzhen, China.
  • Puybareau E; LRDE, EPITA, Paris, France.
  • Rehwald R; Institute of Neurology, University College London, London, United Kingdom.
  • Su R; Biomedical Imaging Group Rotterdam, Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands.
  • Shi P; Department of Electronic and Information Engineering, Harbin Institute of Technology at Shenzhen, Shenzhen, China.
  • Smith L; University College London, United Kingdom.
  • Tillin T; MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science and Experimental Medicine, University College London, London, United Kingdom.
  • Tochon G; LRDE, EPITA, Paris, France.
  • Urien H; ISEP-Institut Supérieur d'Électronique de Paris, Issy-les-Moulineaux, France.
  • van der Velden BHM; Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands.
  • van der Velpen IF; Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands; Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands.
  • Wiestler B; Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Germany.
  • Wolters FJ; Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands; Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands.
  • Yilmaz P; Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands.
  • de Groot M; Biomedical Imaging Group Rotterdam, Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands; GlaxoSmithKline Research, Stevenage, United Kingdom.
  • Vernooij MW; Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands; Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands.
  • de Bruijne M; Biomedical Imaging Group Rotterdam, Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands; Department of Computer Science, University of Copenhagen, Copenhagen, Denmark.
Med Image Anal ; 91: 103029, 2024 Jan.
Article in En | MEDLINE | ID: mdl-37988921
ABSTRACT
Imaging markers of cerebral small vessel disease provide valuable information on brain health, but their manual assessment is time-consuming and hampered by substantial intra- and interrater variability. Automated rating may benefit biomedical research, as well as clinical assessment, but diagnostic reliability of existing algorithms is unknown. Here, we present the results of the VAscular Lesions DetectiOn and Segmentation (Where is VALDO?) challenge that was run as a satellite event at the international conference on Medical Image Computing and Computer Aided Intervention (MICCAI) 2021. This challenge aimed to promote the development of methods for automated detection and segmentation of small and sparse imaging markers of cerebral small vessel disease, namely enlarged perivascular spaces (EPVS) (Task 1), cerebral microbleeds (Task 2) and lacunes of presumed vascular origin (Task 3) while leveraging weak and noisy labels. Overall, 12 teams participated in the challenge proposing solutions for one or more tasks (4 for Task 1-EPVS, 9 for Task 2-Microbleeds and 6 for Task 3-Lacunes). Multi-cohort data was used in both training and evaluation. Results showed a large variability in performance both across teams and across tasks, with promising results notably for Task 1-EPVS and Task 2-Microbleeds and not practically useful results yet for Task 3-Lacunes. It also highlighted the performance inconsistency across cases that may deter use at an individual level, while still proving useful at a population level.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Magnetic Resonance Imaging / Cerebral Small Vessel Diseases Limits: Humans Language: En Journal: Med Image Anal Journal subject: DIAGNOSTICO POR IMAGEM Year: 2024 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Magnetic Resonance Imaging / Cerebral Small Vessel Diseases Limits: Humans Language: En Journal: Med Image Anal Journal subject: DIAGNOSTICO POR IMAGEM Year: 2024 Document type: Article
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