Common methods for tractogram filtering are based on signal reconstruction, a principled approach, but unable to consider the knowledge of brain anatomy. In this work, we address the problem of tractogram filtering as a supervised learning problem by exploiting the ground truth annotations obtained ...
Tractography aims at describing the most likely neural fiber paths in white matter. A general issue of current tractography methods is their large false-positive rate. An approach to deal with this problem is tractogram filtering in which anatomically im
Methods: We propose a novel framework to quantify tractogram redundancy based on filtering tractogram subsets without endorsing a specific filtering algorithm. Our approach defines redundancy based on the anatomical plausibility and diffusion signal representation of streamlines, establishing both lower and ...
Bundle-specific tractogram distributionHigh-order streamline differential equationStreamline tractography locally traces peak directions extracted from fiber orientation distribution (FOD) functions, lacking global information about the trend of the whole fiber bundle. Therefore, it is prone to producing ...
The GSGA provides a common set of eigenvectors for the graphs formed by topographic proximity of nearby tracts, which gives rises to the group graph spectral distance, or G2SD, for measuring the topographic regularity of each fiber tract in a tractogram. Based on this novel model of ...
The GSGA provides a common set of eigenvectors for the graphs formed by topographic proximity of nearby tracts, which gives rises to the group graph spectral distance, or G2SD, for measuring the topographic regularity of each fiber tract in a tractogram. Based on this novel model of ...
Incorporating outlier information into diffusion MR tractogram filtering for robust structural brain connectivity and microstructural analysesdoi:10.1101/2021.06.09.447697SairanenOcampo-Pineda MGranziera CSchiavi SDaducci ACold Spring Harbor Laboratory
For instance, a 11.5GB tractogram can be compressed to a 1.02GB file and decompressed in 11.3 seconds. Moreover, our method allows for the compression and decompression of individual streamlines, reducing the need for a costly out-of-core algorithm with heavy datasets. Last, we open a way ...
In this chapter, we review the main approaches and methods from literature that are relevant for the application of tractogram filtering. Moreover, we give a perspective on the central challenges for the development of new methods, including modern machine learning techniques, in this field in ...
Gas embolismHydrogen peroxideHyperbaric oxygen therapydoi:10.1016/j.ajem.2020.09.040Timothy C. BackusEmily T. CohenAmerican Journal of Emergency Medicine