Where is VALDO? VAscular Lesions Detection and segmentatiOn challenge at MICCAI 2021

Carole H. Sudre, Kimberlin Van Wijnen, Florian Dubost, Hieab Adams, David Atkinson, Frederik Barkhof, Mahlet A. Birhanu, Esther E. Bron, Robin Camarasa, Nish Chaturvedi, Yuan Chen, Zihao Chen, Shuai Chen, Qi Dou, Tavia Evans, Ivan Ezhov, Haojun Gao, Marta Girones Sanguesa, Juan Domingo Gispert, Beatriz Gomez AnsonAlun D. Hughes, M. Arfan Ikram, Silvia Ingala, H. Rolf Jaeger, Florian Kofler, Hugo J. Kuijf, Denis Kutnar, Minho Lee, Bo Li, Luigi Lorenzini, Bjoern Menze, Jose Luis Molinuevo, Yiwei Pan, Elodie Puybareau, Rafael Rehwald, Ruisheng Su, Pengcheng Shi, Lorna Smith, Therese Tillin, Guillaume Tochon, Helene Urien, Bas H. M. van der Velden, Isabelle F. van der Velpen, Benedikt Wiestler, Frank J. Wolters, Pinar Yilmaz, Marius de Groot, Meike W. Vernooij, Marleen de Bruijne

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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 benet 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.
Keywords: CSVD, brain, MRI, microbleeds, enlarged perivascular spaces, lacunes, automated,
segmentation, detection, challenge
Original languageEnglish
JournalAdvances in Computer Vision and Pattern Recognition
DOIs
Publication statusPublished - 15 Aug 2022

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