Bundle Analytics promises fast, robust, and flexible computational and statistical analyses for tractometric studies on clinical data. It uses information from both tractometry, and anatomy to analyze the extracted fiber bundles from challenging clinical datasets. It uses streamline-based efficient algorithms to register and extract fiber bundles from a tractogram, and applies linear mixed models in the extracted bundles to find significant differences at specific locations of the bundles across groups. Finally, the method does not require training, an important advantage over deep learning methods.
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