Objectives Medical image analysis practices face challenges that can potentially be addressed with algorithm-based segmentation tools. In this study, we map the field of automatic MR brain lesion segmentation to understand the clinical applicability of prevalent methods and study designs, as well as challenges and limitations in the field.
Design Scoping review.
Setting Three databases (PubMed, IEEE Xplore and Scopus) were searched with tailored queries. Studies were included based on predefined criteria. Emerging themes during consecutive title, abstract, methods and whole-text screening were identified. The full-text analysis focused on materials, preprocessing, performance evaluation and comparison.
Results Out of 2990 unique articles identified through the search, 441 articles met the eligibility criteria, with an estimated growth rate of 10% per year. We present a general overview and trends in the field with regard to publication sources, segmentation principles used and types of lesions. Algorithms are predominantly evaluated by measuring the agreement of segmentation results with a trusted reference. Few articles describe measures of clinical validity.
Conclusions The observed reporting practices leave room for improvement with a view to studying replication, method comparison and clinical applicability. To promote this improvement, we propose a list of recommendations for future studies in the field.
- radiology & imaging
- magnetic resonance imaging
- diagnostic radiology
Data availability statement
Data are available in a public, open access repository. DOI: 10.6084/m9.figshare.13651235
This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.
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Contributors EG conducted the study and led the writing of the article. RAH was the main supervisor and consultant of the study progress and design choices. JS provided input on the study plan and methodology at all stages. IB-B provided guidance on the interpretation of the findings from a clinical perspective. All coauthors collaborated on manuscript composition and editing.
Funding JFS is supported by the Swedish Childhood Cancer Foundation (MT2018-0020) and the ATTRACT project funded by the EC under Grant agreement 777222.
Competing interests None declared.
Provenance and peer review Not commissioned; externally peer reviewed.
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