Automatic brain lesion segmentation on standard magnetic resonance images: a scoping review

Emilia Gryska, Justin Schneiderman, Isabella Björkman-Burtscher, Rolf A Heckemann
2021 BMJ Open  
ObjectivesMedical 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.DesignScoping review.SettingThree databases (PubMed, IEEE Xplore and Scopus) were searched with tailored queries. Studies were included based on predefined
more » ... eria. 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.ResultsOut 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.ConclusionsThe 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.
doi:10.1136/bmjopen-2020-042660 pmid:33514580 pmcid:PMC7849889 fatcat:im46nmvzovemzk54m2i4grkuoa