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Abstract #5204

Biases in classical structural parcellation

Michael Hejselbak Jensen1, Henrik Thomsen1, Sune Darkner1, Matthew Liptrot2, Niklas Kasenburg1, Karl-Anton Dorph-Petersen3, and Aasa Feragen4

1University of Copenhagen, Copenhagen, Denmark, 2University of Copenhagen and DTU Compute, Copenhagen, Denmark, 3Aarhus University and University of Pittsburgh, Aarhus, Denmark, 4Computer Science, University of Copenhagen, Copenhagen, Denmark

The classical structural parcellation algorithm by Behrens et al1 remains widely used in clinical research, largely thanks to its simplicity and availability in standard MRI processing software. However, its construction and dependency on tractography leads to several biases that can severely affect the conclusions drawn from it, but which are not well known. We illustrate these biases via the original thalamus parcellation experiment on Human Connectome Project (HCP) data3. Based on our experiments, we outline open problems for future structural parcellation algorithms, and possible directions for overcoming them.

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