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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