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What we can learn from adults: Usability of two AI algorithms for Brain and tumor segmentation in a pediatric population.

Maxime DRAI¹, GILLES BRUN¹, Nadine GIRARD^1,2, Benoit TESTUD^1,3, and Jan-Patrick STELLMANN^1,3
¹Neuroradiology, APHM, Marseille, France, ²CRMBM-CEMEREM, Aix-Marseille Université, Marseille, France, ³CNRS, CRMBM-CEMEREM, UMR 7339, Aix-Marseille Université, Marseille, France

Borrowing strength from adult population might allow developing AI based segmentation algorithms for routine clinical care in rare pediatric populations such as brain tumors.

Figure 2 – Comparison of Dice coefficients between the tumor segmentation algorithm (HD-GLIOMA) and expert masks: Histograms showing the distribution of the values (100% indicates a perfect overlap and 0 a complete lack of overlap).

Figure 1 – Comparison of Dice coefficients between different brain extraction tools HD-BET and expert masks: Histograms showing the distribution of the values where values of 100% indicate e perfect overlap and 0 a complete lack of overlap.