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Abstract #3263

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 GIRARD1,2, Benoit TESTUD1,3, and Jan-Patrick STELLMANN1,3
1Neuroradiology, APHM, Marseille, France, 2CRMBM-CEMEREM, Aix-Marseille Université, Marseille, France, 3CNRS, CRMBM-CEMEREM, UMR 7339, Aix-Marseille Université, Marseille, France

AI brain tumor segmentation and brain extraction algorithms are an essential step in image processing, however they are mainly developed in adults. Here, we aimed to explore the usability of these algorithms in a heterogenous pediatric population. In 42 brain pediatric tumor MRI, we compared manual mask with mask generated by the algorithms. Results were excellent for brain extraction, moderate for segmentation of contrast-enhancing tumors, and weak for non-enhancing T2-signal abnormalities. Some improvements are necessary to adapt this algorithm to pediatric brain tumors. However, borrowing strength from adults might be a feasible approach for AI implementation in rare pediatric populations.

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