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FIESTA: Autoencoders for accurate fiber segmentation in tractography
Our proposed method improves bundle segmentation coverage by recovering hard-to-track bundles with generative sampling through the latent space seeding of the subject bundle and the atlas bundle.
Tractography and machine learning: Current state and open challenges
Supervised machine learning (ML) algorithms have recently been proposed as an alternative to traditional tractography methods in order to address some of their weaknesses.
Within-Brain Classification for Brain Tumor Segmentation
Purpose: In this paper, we investigate a framework for interactive brain tumor segmentation which, at its core, treats the problem of interactive brain tumor segmentation as a machine learning problem.
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