In this work, we propose a novel behavioural comparison strategy specifically oriented to accuracy assessment in MRI glial tumour segmentation studies. A salient aspect of the proposed strategy is the use of the fuzzy set framework in modelling visual inspection and interpretation processes. In particular, a reference estimation strategy based on fuzzy connectedness principles is designed to merge individual labels and produce a common segmentation. The estimation is based exclusively on highly reliable partial information provided by experts. Interaction is then drastically limited compared with a complete manual tracing, leaving the estimation of the complete segmentation to the fuzzy connectedness method. A set of experiments was conceived and conducted to evaluate the contribution of the solutions proposed in the process of truth label collection and reference data estimation. A comparison analysis was also developed to see whether our method could constitute a worthy alternative to well-known and state-of-the-art solutions.

Collection and fuzzy estimation of truth labels in glial tumour segmentation studies

BINAGHI, ELISABETTA;BALBI, SERGIO
2016-01-01

Abstract

In this work, we propose a novel behavioural comparison strategy specifically oriented to accuracy assessment in MRI glial tumour segmentation studies. A salient aspect of the proposed strategy is the use of the fuzzy set framework in modelling visual inspection and interpretation processes. In particular, a reference estimation strategy based on fuzzy connectedness principles is designed to merge individual labels and produce a common segmentation. The estimation is based exclusively on highly reliable partial information provided by experts. Interaction is then drastically limited compared with a complete manual tracing, leaving the estimation of the complete segmentation to the fuzzy connectedness method. A set of experiments was conceived and conducted to evaluate the contribution of the solutions proposed in the process of truth label collection and reference data estimation. A comparison analysis was also developed to see whether our method could constitute a worthy alternative to well-known and state-of-the-art solutions.
2016
http://www.tandfonline.com/doi/abs/10.1080/21681163.2014.947006?journalCode=tciv20
MRI segmentation; validation; manual labelling; fuzzy connectedness; reference estimation; common agreement
Binaghi, Elisabetta; Pedoia, V.; Balbi, Sergio
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11383/1945522
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